Has the cost of building software dropped 90%?

https://martinalderson.com/posts/has-the-cost-of-software-just-dropped-90-percent/

by martinald • 8 months ago

421 702 8 months ago

mwkaufma• 8 months ago

Feels almost too on-the-nose to write "Betteridge's Law of Headlines" but the answer is obviously no. Look no further than the farce of their made-up "graph" of cost over time with no units or evidence.

more_corn• 8 months ago

Ask someone who builds software for a fee. Are you able to do 90% more? Fire 9/10 engineers? Produce 90% faster?

No, no, and no.

recursive2• 8 months ago

It's even worse. If the cost drops by 90%, the corresponding productivity increase should be 900%, not 90%.

bdangubic10• 8 months ago

90% more - nope. 35-55% more, just about on average. I am 30-year in though, not sure what these numbers are for junior devs

nottorp• 8 months ago

https://arstechnica.com/ai/2025/07/study-finds-ai-tools-made...

They thought they were faster too.

Yes, I know, AGI is just around the corner, we just need to wait more because "agents" are improving every day.

In the mean time, LLMs are kinda useful instead of web searches, mostly because search is both full of spam and the search providers are toxic.

recursive2• 8 months ago

Did I miss something or is there actually no evidence provided that costs have dropped?

isoprophlex2• 8 months ago

Well... evidence, but there's obviously a graph with a line going places!

TheRoque2• 8 months ago

Especially if you factor-in the fact that the AI companies are losing money for now, and that it's not sustainable.

djmips3• 8 months ago

Yeah, when does the other shoe drops and after being addicted to AI coding we suddenly have the rug pulled on price.

BigHatLogan3• 8 months ago

Good write-up. I don't disagree with any of his points, but does anybody here have practical suggestions on how to move forward and think about one's career? I've been a frontend (with a little full stack) for a few years now, and much of the modern landscape concerns me, specifically with how I should be positioning myself.

I hear vague suggestions like "get better at the business domain" and other things like that. I'm not discounting any of that, but what does this actually mean or look like in your day-to-day life? I'm working at a mid-sized company right now. I use Cursor and some other tools, but I can't help but wonder if I'm still falling behind or doing something wrong.

Does anybody have any thoughts or suggestions on this? The landscape and horizon just seems so foggy to me right now.

isoprophlex2• 8 months ago

Sheep farming sounds nice. Or making wooden furniture. Something physical.

martinald7• 8 months ago

Author here, thanks for your kind words!

I think it's about looking at what you're building and proactively suggesting/prototyping what else could be useful for the business. This does get tricky in large corps where things are often quite siloed, but can you think "one step ahead" of the product requirements and build that as well?

I think regardless if you build it, it's a good exercise to run on any project - what would you think to build next, and what does the business actually want. If you are getting closer on those requests in your head then I think it's a positive sign you are understanding the domain.

BigHatLogan3• 8 months ago

I think you're right about trying to stay one step ahead of product requirements. Maybe my issue here is that I'm looking for another "path" where one might not exist, at least not a concretely defined one. From childhood to now, things were set in front of me and I just sort of did them, but now it feels like we're entering a real fog of war.

It would be helpful, as you suggest, to start shifting away from "I code based on concrete specs" to "I discover solutions for the business."

Thanks for the reply (and for the original essay). It has given me a lot to chew on.

satisfice• 8 months ago

ARE you the author? Or did you prompt AI to get this?

catigula• 8 months ago

Nobody knows the answer.

Answers I see are typically "be a product manager" or "start your own business" which obviously 95% of developers can't/don't want to do.

embedding-shape• 8 months ago

Don't chase specific technologies, especially not ones driven by for-profit companies. Chase ideas, become great in one slice of the industry, and the very least you can always fall back on that. Once established within a domain, you can always try to branch out, and feel a lot more comfortable doing so.

Ultimately, software is for doing something, and that something can be a whole range of things. If you become really good at just a slice of that, things get a lot easier regardless of the general state of the industry.

BigHatLogan3• 8 months ago

Thanks for the response. When you say "one slice of the industry", is the suggestion to understand the core business of whatever I'm building instead of being the "specs to code" person? I guess this is where the advice starts to become fuzzy and vague for me.

colonCapitalDee• 8 months ago

Blind leading the blind, but my thinking is this:

1. Use the tools to their fullest extend, push boundaries and figure out what works and what doesn't

2. Be more than your tools

As long as you + LLM is significantly more valuable than just an LLM, you'll be employed. I don't know how "practical" this advice is, because it's basically what you're already doing, but it's how I'm thinking about it.

ares623• 8 months ago

Realistically, someone else + LLM at -10% compensation will be employed

MrPapz• 8 months ago

My suggestion would be to move to a higher level of abstraction, change the way which you view the system.

Maybe becoming full stack? Maybe understanding the industry a little deeper? Maybe analyzing your company's competitors better? That would increase your value for the business (a bit of overlap with product management though). Assuming you can now deliver the expected tech part more easily, that's what I'd do.

As for me, I've moved to a permanent product management position.

nick486• 8 months ago

Its always been foggy. Even without AI, you were always at risk of having your field disrupted by some tech you didn't see coming.

AI will probably replace the bottom ~30-70%(depends who you ask) of dev jobs. Dont get caught in the dead zone when the bottom falls out.

Exactly how we'll train good devs in the future, if we don't give them a financially stable environment environment to learn in while they're bad, is an open question.

ronald_petty• 8 months ago

Great question, hard to quickly answer.

My .02$. Show you can tackle harder problems. That includes knowing which problems matter. That happens with learning a "domain", versus just learning a tool (e.g. web development) in a domain.

Change is scary, but thats because most aren't willing to change. Part of the "scare" is the fear of lost investment (e.g. pick wrong major or career). I can appreciate that, but with a little flexibility, that investment can be repurposed quicker today that in pre-2022 thanks to AI.

AI is just another tool, treat it like a partner not a replacement. That can also include learning a domain. Ask AI how a given process works, its history, regulations, etc. Go confirm what it says. Have it break it down. We now can learn faster than ever before. Trust but verify.

You are using Cursor, that shows a willingness to try new things. Now try to move faster than before, go deeper into the challenges. That is always going to be valued.

samdoesnothing• 8 months ago

Also blind leading the blind here but I see two paths.

1) Specialize in product engineering, which means taking on more business responsibility. Maybe it means building your own products, or maybe it means trying to get yourself in a more customer-facing or managerial role? Im not very sure. Probably do this if you think AI will be replacing most programmers.

2) Specialize in hard programming problems that AI can't do. Frontend is probably most at risk, low level systems programming least at risk. Learn Rust or C/C++, or maybe backend (C#\Java\Go) if you don't want to transition all the way to low level systems stuff.

That being said I don't think AI is really going to replace us anytime soon.

dclnbrght2• 8 months ago

https://news.ycombinator.com/item?id=46197349

rramadass• 8 months ago

but wonder if I'm still falling behind or doing something wrong.

This is normal with all that is going on in the industry and the AI/ML hype. But, one should not allow that to lead to "analysis paralysis".

specifically with how I should be positioning myself. ... Does anybody have any thoughts or suggestions on this?

You have a stable job; hence your entire focus (for now) should be to "grow" in your job/organization. This means taking more responsibilities both technical/non-technical and demonstrating your long-term commitment to management. On the technical side, start with "full stack development" both frontend and backend so you can contribute end-to-end to the entire product line. Learn/Use all available tools (AI and otherwise) to demonstrate independent initiative. Step up for any tasks which might not have a owner (eg. CI/CD etc.). Keep your boss/higher-ups informed so as to maintain visibility throughout the organization. Learn more about the problem domain, interact more with Marketing/Sales so as to become the liaison between Engineering and rest of the organization/clients.

Generally, all higher management look for initiative and independent drive so that they can delegate work with the assurance that it will be taken care of and that is what you need to provide.

theshrike7913• 8 months ago

Use the best tools, the lowest tier of Claude Code is perfect for the stuff you do at home in the evenings and weekends. It's also by far the best at being a "pair coder" as it's chatty and tells you what it's doing and doesn't get confused if you hit ESC and tell it to do something else.

Build your own tools, need a small utility? Use an LLM to create it with you.

Create LLM-focused tools and adjust your workflows to be LLM-friendly.

I personally have a Taskfile setup that follows the same formula regardless of language. "task build" runs lint+test+build. Test and lint are kinda self-evident. All output is set to minimum, only errors are verbose (don't waste context on fancy output).

I also have tools for LLMs to use to find large code files, large and overly complex functions etc.

All project documentation lives in docs/ as markdown files with Mermaid charts.

This way I can just have the general "how to use a taskfile" instructions in my global WHATEVER.md and it'll work in every project.

Learn project management. Working with LLMs is exactly like project managing a bunch of smart and over eager junior coders who want to use every trick and pattern they learned at school for every tiny shell script.

Do a few test projects where you just pretend you're a non-techinical project lead and know WHAT you want but not HOW you want it done. Plan the project, split it into tasks (github tasks or beads[0] both work pretty well). Then have the LLM(s) tackle the tasks one by one and test the end result like a non-techical PM would do in a demo. Comment, critique and ask them to change stuff that doesn't work.

If you can afford it, bring in an outside consultant (Codex or Gemini), both of which are _really_ good at evaluating large codebases for duplication, test coverage, repetition, bad patterns etc. Give their responses verbatim to Claude and ask what it thinks about them.

Working with LLMs is a skill you just need to use to get a feel for it, it's not a science and more like an art. For example I can "feel" when Claude is doing its thing and being either overeager or trying to complete a task while ignoring the burning pile of unit tests it leaves behind and interrupt. it before it gets too far.

[0] https://github.com/steveyegge/beads

prescriptivist• 8 months ago

Another thing I'd suggest: look into and use non-coding AI tools that improve productivity. For example:

Zoom meeting transcriptions and summaries or Granola. A lot of context is lost when you take manual notes in meetings. If you use a tool that turns a meeting into notes automatically, you can use those notes to bootstrap a prompt/plan for agents.

andrewstuart• 8 months ago

If you’re quicker then competition heats up management wants more done, efficiencies are soon forgotten and new expectations and baselines set.

foxglacier• 8 months ago

Sure but that's the good of it. Lower labor cost = more productivity. The customer wins in the end because the equivalent product is cheaper or a better product costs the same. Businesses and employees still have to compete against each other so things won't get easier for them in the long term.

Draiken• 8 months ago

Except this is capitalism, so any improvements will go disproportionately to the owners. This narrative of improvements for customers has been repeated for decades and it keeps being wrong.

More stock buybacks and subscriptions!

AngryData• 8 months ago

The customer only wins if the customer is the one using the tools directly, otherwise it leaves all the power in the hands of businesses who's only real goal is maximum profits. And without already possessing domain knowledge to be able to guide, judge, and correct AI along the way, its existence will be of limited use to consumers and business will not feel much pressure to make anything cheaper, it just leaves more margin to funnel to the top.

qwertyastronaut3• 8 months ago

I don’t know if it’s 90%, but I’m shipping in 2 days things that took 2-4 weeks before.

Opus 4.5 in particular has been a profound shift. I’m not sure how software dev as a career survives this. I have nearly 0 reason to hire a developer for my company because I just write a spec and Claude does it in one shot.

It’s honestly scary, and I hope my company doesn’t fail because as a developer I’m fucked. But… statistically my business will fail.

I think in a few years there will only be a handful of software companies—the ones who already have control of distribution. Products can be cloned in a few weeks now; not long until it’s a few minutes. I used to see a new competitor once every six months. Now I see a new competitor every few hours.

martinald7• 8 months ago

Agreed. Opus 4.5 does feel like a real shift and I have had exactly your experience. I've shipped stuff that would have taken me weeks in days. And really to a much higher quality standard - test suites would have been far smaller if I'd built manually. And probably everything in MVP Bootstrap CSS.

bdangubic10• 8 months ago

this is roughly same for me

llmslave• 8 months ago

Yeah, I really think software engineering is over. Not right now, but Opus 4.5 is incredible, it wont be long before 5 and 5.5 are released.

They wont automate everything, but the bar for being able to produce working software will plummet.

throwaway311312• 8 months ago

Just out of curiosity, what software product were you making in two weeks before using AI? Or maybe I’m misunderstanding your use of shipping.

qwertyastronaut3• 8 months ago

Shipping features, not entire products.

LPisGood2• 8 months ago

I feel like I have have heard this exact statement about model FooBar X.Y about a half dozen times over the last couple of years.

IceDane2• 8 months ago

I'd love to hear what sort of software you are building.

qwertyastronaut3• 8 months ago

This is my anon account so I prefer not to leave any identifying details. Niche solo-dev SaaS that makes $50k a month.

pessimizer• 8 months ago

I have no idea how you could debug something in two days that is sufficient to ship. I certainly think that an LLM could write a few thousand lines, but who could read them?

Are you shipping things you haven't reviewed at all, and pronouncing them high quality?

I find these threads baffling. I haven't seen a glut of new software anywhere. I certainly haven't seen a bunch of companies fixing the same bugs that have been sitting in their trackers for years. People keep telling me there's this deluge of LLM code happening, but it (the actual code) is all a secret and behind closed doors. Why in the world would you keep it a secret? Why would any multibillion dollar company that ships AI features have any known bugs left in their flagship products?

I haven't seen a difference anywhere when looking outwards. I personally find it useful, but I have to constantly force refactors and rearchitecting to make the code intelligible. When I add features, bugs get reinserted, refactors get reverted, and instrumentation silently disappears. If I don't do the constant refactors, I wouldn't even notice this was happening half the time.

neilv• 8 months ago

Copying GPL code, with global search&replace of the brand names, has always lowered the cost of software 'development' dramatically.

bdangubic10• 8 months ago

I would love to see where I can find a full test coverage to paste in for an internal too that I can search&replace on to get it working…

JohnMakin2• 8 months ago

This article mentions cost to ship, but ignores that the largest cost of any software project isn't consumed by how long it takes to get to market, but by maintenance and addition of new features. How is agentic coding doing there? I've only seen huge, unmaintainable messes so far.

bdangubic10• 8 months ago

one year in, AI slop > Human-written slop

JohnMakin2• 8 months ago

I am highly skeptical of this claim.

jimbokun2• 8 months ago

Does this mean the AI slop is higher quality or that there's more of it?

p2detar2• 8 months ago

While this is true, I think some fields like game development may not always have this problem. If your goal is to release a non-upgradable game - fps, arcade, single-player titles, maintenance may be much less important than shipping.

edit: typos

liampulles4• 8 months ago

I think that is an applicable domain, but the problem is that every gamer I know who is not in the tech industry is vehemently opposed to AI.

krupan3• 8 months ago

I'm trying to understand where this kind of thinking comes from. I'm not trying to belittle you, I sincerely want to know: Are you aware that everyone writing software has the goal of releasing software so perfect it never needs an upgrade? Are you aware that we've all learned that that's impossible?

pjc50• 8 months ago

Nobody wants to ship that! They want perpetually upgraded live service games instead, because that's recurring revenue.

an0malous2• 8 months ago

Then why is all my software slower, buggier, and with a worse UX?

HumblyTossed• 8 months ago

Right? Past couple years software quality has taken a shit.

256_• 8 months ago

I think this reflects one of the biggest fallacies behind LLM adoption; the idea that reducing costs for producers improves the state of affairs for consumers too. I've seen someone compare it to the steam engine.

With the steam engine, though, consumers made a trade-off: You pay less, and get (in most cases, I presume) a worse product. With LLMs and other machine learning technologies, maybe if you're paying for the software there's a trade-off (if the software is actually cheaper anyway), but otherwise it doesn't exist. It costs the same amount of money for you to read an LLM-generated article as to read a real one; your internet bill doesn't go down. Likewise for gratis software. It's just worse, with no benefit.

Hacker News is full of producers, in this sense, who often benefit from cutting corners, and LLMs allow them to cut corners, so obviously there are plenty of evangelists here. I saw someone else in this comment section mention that gamers who are not in the tech industry don't like "AI". That's to be expected; they're not the producers, so they're not the ones who benefit.

Covenant0028• 8 months ago

To reinforce that point: we've got the world's most prominent AI promoting company (MSFT), that has finally realized that Windows Explorer is too slow to start.

And this company, with all the formidable powers of AI behind them, can find no way to optimize that other than pre loading the app in memory. And that's for a app that's basically a GUI for `ls`

paoaoaks• 8 months ago

written an entire unit/integration test suite in a few hours

It’s often hard to ground how “good” blog writers are, but tidbits like this make it easy to disregard the author’s opinions. I’ve worked in many codebases where the test writers share the authors sentiment. They are awful and the tests are at best useless and often harmful.

Getting to this point in your career without understanding how to write effective tests is a major red flag.

p1necone• 8 months ago

I've used llms to help me write large sets of test cases, but it requires a lot of iteration and the mistakes it makes are both very common and insidious.

Stuff like reimplementing large amounts of the code inside the tests because testing the actual code is "too hard", spending inordinate amounts of time covering every single edge case on some tiny bit of input processing unrelated to the main business logic, mocking out the code under test, changing failing tests to match obviously incorrect behavior... basically all the mistakes you expect to see totally green devs who don't understand the purpose of tests making.

It saves a shitload of time setting up all the scaffolding and whatnot, but unless they very carefully reviewed and either manually edited or iterated a lot with the LLM I would be almost certain the tests were garbage given my experiences.

(This is with fairly current models too btw - mostly sonnet 4 and 4.5, also in fairness to the LLM a shocking proportion of tests written by real people that I've read are also unhelpful garbage, I can't imagine the training data is of great quality)

IceDane2• 8 months ago

But we have 500% code coverage?!?!

debo_• 8 months ago

I'm sure every organisation has hundreds if not thousands of Excel sheets tracking important business processes that would be far better off as a SaaS app.

Far better off for who? People constantly dismiss spreadsheets, but in many cases, they are more powerful, more easily used by the people who have the domain knowledge required to properly implement calculations or workflow, and are more or less universally accessible.

nesarkvechnep• 8 months ago

I’m yet to see a spreadsheet workflow successfully replaced by something else.

crubier2• 8 months ago

Streamlit apps or similar are doing a great job at this where I'm at.

As simple to build and deploy as Excel, but with the right data types, the right UI, the right access and version control, the right programming language that LLMs understand, the right SW ecosystem and packages, etc.

tehjoker4• 8 months ago

maybe the strategy in those cases is to augment the core spreadsheet with tools that can unit test it and broadcast changes etc

esafak• 8 months ago

Programming in a spreadsheet is an anti-pattern. Does anyone review your workflow? Write tests for it? Use a real programming language; a notebook at least.

martinald7• 8 months ago

Author here. Of course not everything needs to be a web app. But I'm meaning a lot of core sheets I see in businesses need more structure round them.

Especially for collaboration, access controls, etc. Not to mention they could do with unit testing.

tonyarkles• 8 months ago

Counterpoint: if a small part of the process is getting tweaked, how responsive can the team responsible for these apps be? That’s the killer feature of spreadsheets for business processes: the accountants can change the accounting spreadsheets, the shipping and receiving people can change theirs, and there’s no team in the way to act as a bottleneck.

That’s also the reason that so-called “Shadow IT” exists. Teams will do whatever they need to do to get their jobs done, whether or not IT is going to be helpful in that effort.

swatcoder2• 8 months ago

It's rare than a third-party SaaS can approximate one of these "core sheets" and most of the exceptions have already been explored over the last several decades years.

You have to remember that an SaaS, just like shrink-wrap software, reflects someone else's model of of a process or workflow and the model and implementation evolve per the timeline/agenda of its publisher.

For certain parts of certain workflows, where there's a highly normative and robust industry standard, like invoicing or accounting or inventory tracking, that compromise is worthwhile and we've had both shrink-wrap and SaaS products servicing those needs for a very very long time. We see churn in which application is most popular and what it's interface and pricing look like, but the domains being served have mostly been constant (mostly only growing as new business lines/fashions emerge and mature).

Most of the stuff that remains in a "core sheet" could benefit from the attention of a practiced engineer who could make it more reliable and robust, but almost always reflects that the represented business process is somehow peculiar to the organization. As Access and FoxPro and VBA and Zapier and so many tools have done before, LLM coding assistants and software building tools offer some promise in shaking some of these up by letting orgs convert their "core sheets" to "internal applications".

But that's not an opportunity for SaaS entrepreneurs. It's an opportunity for LLM experts to try to come in and pitch private, bespoke software solutions for a better deal than whatever the Access guy had promised 20 years ago. Because of the long-term maintenance challenges that still plague code that's too LLM-colored, I wouldn't want to be that expert pitching that work, but it's an opportunity for some ambitious folks for sure.

ASalazarMX2• 8 months ago

a lot of core sheets I see in businesses need more structure round them

We had this decades ago, it was called dBase, but FoxPro (pre-Microsoft) was great too. Visual For Pro or MS Access were a brutal downgrade of every good aspect of it.

Imagine if today some startup offered a full-stack(TM) platform that included IDE, a language with SQL-like features, visual UI designer, database; generated small standalone binarires, was performant, and was smaller than most web homepages.

There are modern options, like Servoy or Lianja, but they're too "cloudy" to be considered equivalents.

Edit: seems like there's OpenXava too, but that is Java-based, too hardcore for non-professional programmers IMO. The beauty of xBase was that even a highschooler could whip out a decent business application if the requirements were modest.

robotresearcher2• 8 months ago

Spreadsheets are an incredible tool. They were a key innovation in the history of applications. I love them and use them.

But it's very hard to have a large conventional cell-formula spreadsheet that is correct. The programming model / UI are closely coupled, so it's hard to see what's going on once your sheet is above some fairly low complexity. And many workplaces have monstrous sheets that run important things, curated lovingly (?) for many years. I bet many or most of them have significant errors.

ASalazarMX2• 8 months ago

It's astounding how useful and intuitive they are, but my biggest gripe is how easy is for anyone to mess calculations, say, SUM(<RANGE>), by simply adding one row/column/cell.

I use Google Worksheets frequently to track new things that fit into lists/tables, and giving someone else editor access without them knowing a few worksheet nuances means I have to recheck and correct them every month or two.

MrDresden• 8 months ago

This happened not so many years ago, in a certain small European nation, where official government housing valuation numbers were incorrect for some years due to a flaw in a spreadsheet.

I remember my apartment got a ~10% bump in value one year due to this flaw being fixed (fix didn't apply to all housing, just those who were on floors 5 or above).

I don't think though that a SaaS would have solved anything here.

jimbokun2• 8 months ago

Better security. Better availability. Less chance of losing data.

Assuming the SaaS is implemented competently, of course. Otherwise there's not much advantage.

frm88• 8 months ago

I disagree. I have seen many such Excel applications in many companies, paticularly in the finance and controlling departments that were delivering key numbers to the C-class which would never have allowed the sheets, applications or calculations out of the house, let alone to a cloud service or an out-of-company consultant/programmer. There were always backups managed by the department themselves and in one case, even entry to the room with the relevant machine was restricted to authorised personnel only. If I have learned anything in my 30 years of consulting, it's that you always take Finance at its word when they tell you No to your SaaS or ERP solution.

croes• 8 months ago

And often the are unmaintainable because the original author left the company and the users don’t really know what the spreadsheet does which leads to unrecognized bugs and errors especially in spreadsheets with lots of data

tgv• 8 months ago

Let's not forget: it's pretty unlikely that two orgs come up with the same administration/data-analyis for which they use those spreadsheets, so most of those proposed SaaS applications would have just one customer.

There is of course SAP for common problems.

jl6• 8 months ago

Spreadsheets are absolutely the right solution for a great many problems. The important thing to recognize is when a problem has outgrown a spreadsheet solution. That’s usually when you start to use a spreadsheet as a database, or when it has more than a handful of users.

It’s a rare spreadsheet that survives its original creator.

trashb• 8 months ago

Spreadsheets are powerful, but often abused. They are great for economics but horrible for logic.

Most medium to large complex spreadsheets are better implemented in a high level programming language.

Spreadsheets seem useful for people that are scared of programming syntax but quickly become so much less maintainable and janky that I believe its almost always easier to just start with learning to program already.

Especially excel is 100% jank.

on_the_train3• 8 months ago

Ai saves me like an hour per month tops. I still don't understand the hype. It's a solution in search of a problem. It can't solve the hard coding problems. And it doesn't say when it can't solve the essay ones either. It's less valuable than resharper. So the business value is maybe $10 a month. That can't finance this industry.

averageRoyalty• 8 months ago

I read these sort of comments every so often and I do not understand them. You are in a sea of people telling you that they are developing software much quicker which ticks the required boxes. I understand that for some reason this isn't the case for your work flow, but obviously it has a lot more value for others.

If you are a chairmaker and everyone gains access to a machine that can spit out all the chair components but sometimes only spits out 3 legs or makes a mistake on the backs, you might find it pointless. Maybe it can't do all the nice artisan styles you can do. But you can be confident others will take advantage of this chair machine, work around the issues and drive the price down from $20 per chair to $2 per chair. In 24 months, you won't be able to sell enough of your chairs any more.

throwaway311312• 8 months ago

Maybe, or maybe the size of the chair market grows because with $2 chairs more buyers enter. The high end is roughly unaffected because they were never going to buy a low end chair.

on_the_train3• 8 months ago

You are in a sea of people telling you that they are developing software much quicker which ticks the required boxes

But that's exactly not the case. Everyone is wondering what tf this is supposed to be for. People are vehemently against this tech, and yet it gets shoved down our throats although it's prohibitively expensive.

Coding should be among the easiest problems to tackle, yet none of the big models can write basic "real" code. They break when things get more complex than pong. And they can't even write a single proper function with modern c++ templating stuff for example.

nine_k• 8 months ago

Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.

From where I sit, right now, this does not seem to be the case.

This is as if writing down the code is not the biggest problem, or the biggest time sink, of building software.

martinald7• 8 months ago

It is happening though internally in businesses I've worked with. A few of them are starting to replace SaaS tools with custom built internal tooling. I suspect this pattern is happening everywhere to a varying level.

Often these SaaS tools are expensive, aren't actually that complicated (or if they are complicated, the bit they need isn't) and have limitations.

For example, a company I know recently got told their v1 API they relied on on some back office SaaS tool was being deprecated. V2 of the API didn't have the same features.

Result = dev spends a week or two rebuilding that tool. It's shipped and in production now. It would have taken similar amount of time to work around the API deprecation.

lossolo• 8 months ago

It is happening though internally in businesses I've worked with

How many samples do you have?

Which industries are they from?

Which SaaS products were they using, exactly and which features?

...a company I know recently got told their v1 API they relied on on some back office SaaS tool was being deprecated. V2 of the API didn't have the same features ... dev spends a week or two rebuilding that tool

Was that SaaS the equivalent of the left-pad Node.js module?

nugger• 8 months ago

I don't understand the timelines here at all.

renewiltord• 8 months ago

I know of at least two multi-billion corps that are moving to internal ETL tools instead of 5tran now because the cost to maintain internally is much lower and you can customize for cheap. SaaS as a model is at risk without something tying someone down.

thot_experiment2• 8 months ago

To be fair, writing a SaaS software is like an order, perhaps two orders of magnitude more effort than writing software that runs on a computer and does the thing you want. There's a ton of stuff that SaaS is used for now that's basically trivial and literally all the "engineering" effort is spent on ensuring vendor lock in and retaining control of the software so that you can force people to keep paying you.

layer8• 8 months ago

We should also get a flurry of low-cost, decent-quality native local-first software, but I’m not seeing any.

sofixa2• 8 months ago

With a SaaS, you have one platform that you fully control. Broken dependency? Need to update/rollback? It's all in your hands.

Local software has to target multiple OSes, multiple versions of those OSes, and then a million different combinations of environments that you as a developer have no control over. Windows update whatever broke your app, but the next one fixed it? Good luck getting your user base to update instead of being pissed at you

paulddraper3• 8 months ago

Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.

NODS HEAD VIGOROUSLY

Last 12 months: Docusign down 37%, Adobe down 38%, Atlassian down 41%, Asana down 41%, Monday.com down 44%, Hubspot down 49%. Eventbrite being bought for pennies.

They are being replaced by newer, smaller, cheaper, sometimes internal solutions.

BobbyJo2• 8 months ago

Stock prices down or revenue down? The former would do very little to support your point.

xnx2• 8 months ago

Had the cost of building custom software dropped 90%

It definitely has for me. I'm creating toolS and utilities every week easily that I never would've attempted in the past.

This is as if writing down the code is not the biggest problem, or the biggest time sink, of building software.

Lots of people can think logically and organize a process flow, but don't know all the ridiculous code incantations (and worse development and hosting environment details) to turn their plans into tools.

It's trivial to one-shot all kinds of impressive toys in Gemini now, but it's going to be an even bigger deal when Google adds some type of persistent data storage. It will be like the rebirth of a fully modern Microsoft Access.

kenjackson5• 8 months ago

It has dropped by maybe MORE than 90%. My sons school recently asked me to build some tools for them -- I did this over a decade ago for them, for free. I did it again using AI tools (different problem though) and I had it mostly done in 30 minutes (after I got the credentials set up properly -- that took up more time than the main coding part). This was probably several days of work for me in the past.

TheRoque2• 8 months ago

But in the past, you knew the codebase very well, and it was trivial to implement a fix and upgrade the software. Can the same be done with LLMs ? Well from what I see, it depends on your luck. But if the LLMs can't help you, then you gotta read the whole codebase that you've never read before and you quickly lose the initial benefits. I don't doubt someday we'll get there though.

bloppe• 8 months ago

"Building software" is a bit too general, though. I believe "Building little web apps for my son's school" has gotten at least 10x easier. But the needle has not moved much on building something like Notion, or Superhuman, or Vercel, or <insert name of any non-trivial project with more than 1000 man-hours of dev work>.

Even with perfect prompt engineering, context rot catches up to you eventually. Maybe a fundamental architecture breakthrough will change this, but I'm not holding my breath.

codegeek• 8 months ago

The keyword is "building". Yes costs may have dropped 90% just to build software. But there are 1000 other things that comes after it to run a successful software for months let alone years.

- Maintenance, Security

- Upgrades and patches

- Hosting and ability to maintain uptime with traffic

- Support and dealing with customer complexities

- New requirements/features

- Most importantly, ability to blame someone else (at least for management). Politics plays a part. If you build a tool in-house and it fails, you are on the chopping block. If you buy, you at least can say "Hey everyone else bought it too and I shouldn't be fired for that".

Customers pay for all of the above when they buy a SAAS subscription. AI may come for most of the above at some point but not yet. I say give it 3-5 years to see how it all pans out.

socketcluster3• 8 months ago

Good points but this list is missing the most critical problem which AI does not solve; exposure.

What you've listed are the easy parts that are within people's control. You didn't list the most critical part, the actual bottleneck which is not within people's control.

The market is now essentially controlled by algorithms. I predict there will be amazing software... Which will end up ignored by the markets completely until their features are copied by big tech and nobody will know where the idea originated.

Building is absolutely worthless in the context of a monopolized marketplace.

almosthere3• 8 months ago

llms do all that too

MangoToupe3• 8 months ago

All of this can be written off as "building software", though. What this reveals is that the costs in a given market are likely not software at all

klntsky• 8 months ago

People vibe one-off solutions for themselves all the time. They just don't have the desire to productionalize them. Frankly, product knowledge is something LLMs are not that good at

RajT884• 8 months ago

Low code solutions like PowerApps I bang out stuff like this all the time. If your use case is limited enough, it makes lazy developers very productive.

viraptor3• 8 months ago

Same. I hate doing mobile coding, but just in the last few months I AI-coded 3 apps specifically for my needs. They'll never get released publicly, because they'd need polish and features that I don't care about personally. They potentially replace some SaaS too.

jayd16• 8 months ago

I mean, we have had the tech to crank out some little app for a long time. The point of the Saas used to be that you had a neck to strangle when things went south. I guess these days that's just impossible anyhow and the prices aren't worth it so we're rediscovering that software can be made instead of bought?

There have been a lot of little blogs about "home cooking" style apps that you make for yourself. Maybe AI is the microwave meal version.

phantasmish2• 8 months ago

Something weird happened to software after the 90s or so.

You had all these small-by-modern-standards teams (though sometimes in large companies) putting out desktop applications, sometimes on multiple platforms, with shitloads of features. On fairly tight schedules. To address markets that are itty-bitty by modern standards.

Now people are like “We’ll need (3x the personnel) and (2x the time) and you can forget about native, it’s webshit or else you can double those figures… for one platform. What’s that? Your TAM is only (the size of the entire home PC market circa 1995)? Oh forget about it then, you’ll never get funded”

It seems like we’ve gotten far less efficient.

I’m skeptical this problem has to do with code-writing, and so am skeptical that LLMs are going to even get us back to our former baseline.

mattgreenrocks2• 8 months ago

Yep. Software construction was branded a team sport. Hence, social coding, tool quality being considered more important (good thing for sure), and, arguably, less emphasis on individual skill and agency.

This was in service of a time when tech was the great equalizer, powered by ZIRP. It also dovetailed perfectly with middle managers needing more reports in fast growing tech companies. Perhaps the pendulum is swinging back from the overly collective focus we had during the 2010s.

dghlsakjg2• 8 months ago

Something weird happened to software after the 90s or so.

Counterpoint: What might have happened is that we expect software to do a lot more than we did in the 90s, and we really don't expect our software features to be static after purchase.

I agree that we sometimes make things incredibly complex for no purpose in SE, but also think that we do a rose-colored thing where we forget how shitty things were in the 1990s.

PaulHoule2• 8 months ago

Circa 2005 my boss and I would pitch that the relational database + HTML forms paradigm was a breakthrough that put custom software within reach of more customers: for one thing you could just delete all the Installshield engineers but also memory safety was a big problem in the Win95 era not so much about being hacked and more about application state in applications would get corrupted over time so you just expected Word to crash once an hour or so.

anonymars• 8 months ago

Some thoughts:

1. Personally I find writing software for the web far more difficult/tedious than desktop. We sure settled on the lowest common denominator

1a. Perhaps part of that is that the web doesn't really afford the same level of WYSIWYG?

2. Is it perhaps more difficult (superlinear) to write one cloud SaaS product that can scale to the whole world, rather than apps for which each installation only needed to scale to one client? Oh and make sure to retain perfect separation between clients

2a. To make everything scale, it's super distributed, but having everything so distributed has a huge cost

3. Some level of DLL hell, but something different (update hell?) I barely do any programming in my free time anymore because I would end up spending almost the whole time needing to deal with some barrage of updates, to the IDE, to the framework, to the libraries, to the build infrastructure

3a. There's always a cost to shipping, to the development team and/or the users. With releases so frequent, that cost is paid constantly and/or unpredictably (from the development or user perspective)

3b. Is there any mental sense of completion/accomplishment anymore or just a never-ending always-accelerating treadmill?

3c. I wish I could find the source but there was some joke that said "software developers are arrogant or naïve enough to think that if you take a marathon and just break it up into smaller parts you can 'sprint' the whole way"

strken• 8 months ago

Part of this is the huge ZIRP-driven salary bubble in the US. If good software engineers were as cheap as good structural engineers, you'd be able to stick three of them in a room for $500k a year and add a part-time manager and they'd churn out line-of-business software for some weird little niche that saves 50 skilled-employee-years per year and costs $20k a seat.

The bubble means that a) the salaries are higher, b) the total addressable market has to justify those salaries, c) everyone cargo cults the success stories, and so d) the best practices are all based on the idea that you're going to hyperscale and therefore need a bazillion microservices hooked up to multiple distributed databases that either use atomic clocks or are only eventually consistent, distributed queues and logs for everything, four separate UIs that work on web/iOS/android/desktop, an entire hadoop cluster, some kind of k8s/mesos/ECS abomination, etc.

The rest of the world, and apparently even the rest of the US, has engineering that looks a little more like this, but it's still influenced by hyperscaler best practices.

torginus2• 8 months ago

This needs to be said more. Software used to be so much better, and so was tooling.

While it wasn't perfect, I'd argue software got much worse, and I blame SaaSification and the push for web-based centralization.

Take for example, Docker. Linux suffered from an issue of hosting servers in a standardized, and isolated manner.

The kernel already had all those features to make it work, all we needed was a nice userland to take advantage of it.

What was needed was a small loader program that set up the sandbox and then started executing the target software.

What we got was Docker, which somehow came with its own daemon (what about cron, systemd etc), way of doing IPC (we had that), package distribution format (why not leave stuff on the disk), weird shit (layers wtf), repository (we had that as well), and CLI (why).

All this stuff was wrapped into a nice package you have to pay monthly subscription fees for.

Duplicating and enshittifying standard system functions, what a way to go.

zahlman2• 8 months ago

Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.

Don't forget the second-order effect of clients deciding they could do it in-house.

PaulHoule2• 8 months ago

In fact that is where AI could win. An in house system only needs to serve the needs of one customer whereas the SAAS has to be built for the imagined needs of many customers —- when you’re lucky you can “build one to throw away” and not throw it away.

socketcluster3• 8 months ago

This is assuming the marketplace works perfectly... Which is an incorrect assumption. Reality is that the marketplace is highly controlled by algorithms. New platforms will struggle to get exposure... No exposure, no credibility, no word of mouth, no users, catch 22... You think the big players will allow small SaaS projects to gain traction on their platforms? Have you seen how centralized the Internet is these days? Have you seen how afraid people are of betting on no-name platforms? If they choose the wrong no-name platforms and tools, they will lose their (increasingly precious) jobs. As the saying goes "Nobody lost their job for choosing IBM." As for B2C; it's dead, consumers don't have money and will have less of it in the future; the mass-market game is over.

My bet is if there were a lot of great apps being built, even excellent quality, nobody would even hear about them. The big players would copy them before anyone even found out about them.

IMO, the market is not even a playing field anymore, this is why everyone is getting into politics now, though politics is also somewhat monopolized, there is still more potential for success because there is such an abundance of dissatisfied people willing to look outside of mainstream channels. It's much easier to sell political ideologies than to sell products.

acessoproibido3• 8 months ago

"Everything is controlled by algorithms" doesnt make any sense - its like saying everything is subject to entropy - well sure but also what?

almosthere3• 8 months ago

LLMs, long term, have killed most SaaS.

Most SaaS used to be killed by bespoke software engineers that would build some custom thing, and it was integrated perfectly into the legacy system.

Then all those people decided to be managers and go on "i dont care" autopilot mode and hired a bunch of teens that still do care, to some extent. But those teens suck at it, and the old guys just don't really care anymore.

Now with agentic code, instead of "buy splunk" or "buy jira" or whatever thing they are trying to do, they have one of those "teens now in their mid twenties" that are SUPER excited about Agentic flows, either write an agentic tool or simply use an agentic tool to code up the 300 lines of code that would replace their need for a Jira or a Splunk or whatever. Since most people only use 5% of the total features of any product, there's no reason to buy tools anymore, just build it for a fraction of the cost.

I don't know if the above is where we're at right now, but it's coming.

actionfromafar• 8 months ago

Creating code sprawl, weird ball of twine systems etc until someone says, enough, we will just buy this SAAS solution which integrates it all. Rinse, repeat.

myk9001• 8 months ago

that would replace their need for a Jira or a Splunk

Or a JS runtime like Bun. Oh, wait...

roncesvalles2• 8 months ago

Nobody is replacing Jira or Splunk with anything coming out of an LLM.

bmikaili• 8 months ago

Yeahh, right, I'm not sure splunk is that simple.

heavyset_go• 8 months ago

This is "people will 3D print cars in their garage, manufacturing is over!" level of hype

raw_anon_11117• 8 months ago

Well, because no self interested decision maker in any company of size is going to ever trust their business to an unknown company run by a one person operation.

And why would the benefits of being able to code faster accrue to a small independent developer over a large company that already has an established reputation and a customer base?

“No one ever got fired for buying Salesforce”.

I once had influence over the buying decision to support an implementation I was leading. I found this perfect SaaS product by a one man shop who was local.

Working with my CTO and lawyers, we made a proposal to the founder. We would sign with him and be 70% of his post signing revenue if he agreed to give us our own self hosted instance and put his latest code in escrow with a third party (Green Mountain) and we would have non exclusive rights to use the code (but not distribute it) under certain circumstances.

pdimitar9• 8 months ago

Did he agree?

benjiro3• 8 months ago

He never said that companies will trust a one man shop. His point was clearly that people and companies will make products designed for themselves, using LLMs.

Why pay for a piece of software that you really only use 5% of all the features, and still may need customizations for. Vs just internally have somebody code a custom solution for your company.

The only benefit of a outside solution is that you can blame a outsider. Internal solution used to be bad because if the person with the knowledge of the codebase left, you ended up screwed. But with LLMs and "vibe" coding, there becomes a disconnect between the code and whoever wrote it. Making it easier to later make modifications on that same codebase, using ... LLMs.

eirikbakke• 8 months ago

I'd also expect to see a lot more AI-generated PRs on open source projects.

(Or at least AI-assisted to the point where the author feels like they should mention it.)

vidarh2• 8 months ago

For a lot of SaaS projects building the software is the simplest part.

roncesvalles2• 8 months ago

There is also the missing explosion of App Store app submissions and other such metrics.

trollbridge4• 8 months ago

Astute observation. From where I sit, the market (at least for business software; I am not very familiar with the consumer market) seems to be wide open, and businesses in the 5 - 200 employee range seem to be particularly underserved.

The marketplace for software for single-owner shops or 1-5 employee size places does seem to be quite strong, and then there's enterprise software, but small business seems to have a software marketplace that is atrociously bad. Here is the typical thing a prospective customer asks me to fix for them:

- They are using some piece of software that is essential to their business. - There really isn't much good competition for that software, and it would be a large cost to convert to another platform that also has all the same downsides below. - The software vendor used to be great, but seems to have been sold several times. - The vendor has recently switched to a subscription-only model and keeps on raising subscription prices in the 12% or so range every year, and the cost of this has started to become noticeable in their budget. - They were accustomed to software being a capital investment with a modest ongoing cost for support, but now it's becoming just an expense. - Quality has taken a nosedive and in particular new features are buggy. Promised integrations seem quite lacking and new features/integrations feel bolted on. - Support is difficult to get ahold of, and the formerly good telephone support then got replaced by being asked to open tickets/emails and now has been replaced by an AI chatbot frontend before they can even open a ticket. Most issues go unresolved.

There are literally millions of software packages in existence, and the bulk of them by numbers are niche products used by small businesses. (Think of a software package which solely exists to help you write custom enhancements for another software package which is used by a specific sector of the furniture-manufacturing business, to get an example.) The quality of this sector is not improving.

This is a field that is absolutely ripe for improvement. If the cost of building software really were dropping 90%, this would be a very easy field to move into and simply start offering for $6,000 a year the product that your competition is charging $12,000 a year for, for an inferior product. Before you bring up things like vendor lock-in or the pain of migration... why can't you write software to solve those problems, too? After all, the cost of writing a migration tool should be 90% cheaper now, too, right?

pizzafeelsright• 8 months ago

I found that the time (1-4 hours) is enough to build any SaaS for myself

Kerrick• 8 months ago

"We use AI to build the tools because we use them in cursor or Visual Studio or code or wherever else people are making our stuff. I use AI a bunch." https://37signals.com/podcast/listener-questions/

"Today we’re introducing Fizzy. Kanban as it should be, not as it has been. [...] we’ll host your account for just $20/month for unlimited cards and unlimited users. [...] And here’s a surprise... Fizzy is open source! If you’d prefer not to pay us, or you want to customize Fizzy for your own use, you can run it yourself for free forever." https://x.com/jasonfried/status/1995886683028685291

weird-eye-issue2• 8 months ago

Your comment contradicts itself

You are saying there aren't more low cost alternatives coming out

You also say writing code isn't the big problem (which I agree with)

But both can be true and in fact the reason is because the second is true! You aren't seeing the alternate because marketing is hard. People generally don't care about new products and aren't willing to save a little bit of money risking their time on something new

Madmallard• 8 months ago

barrier to entry is more problematic than anything else

make something decent in the same space as an existing mega-corporation's tool? prepare to get sued and they also steal your good ideas and implement them themselves because you don't have the money to fight them in court

codyswann• 8 months ago

Code isn't the moat and it hasn't been for quite some time. Data is the moat.

theshrike7913• 8 months ago

No no, that's not how it works.

The crap I build _replaces_ someone else's SaaS (or free open source) product.

They solve my exact problem and nothing else and they follow the ways I like to use my software, with no fancy Dockerised WebUIs etc.

I have exactly zero intention of putting any of that shit out there as any kind of service with user accounts and billing and all of the associated stress. A few of them might be something I could sell as a SaaS offering, but I'm not interested in it at all.

Most of them are on my Github though for anyone to get and use as they see fit, but then it's up to them if the vibe coded program does something it shouldn't :)

mbesto• 8 months ago

Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.

Aha. Are developers finally realizing that just writing code doesn't make a business? We actually have a ton of SaaS companies being born right now but they're not making headway, because functionality and good code don't necessarily mean good businesses. Building a business is hard.

pllbnk• 8 months ago

I have seen it commonly cited (although haven't bothered to check the actual sources, mostly because I believe they should be taken with a grain of salt) that developers spend somewhere in the ballpark of 50-60% of their time doing "coding work" - that is writing the code, thinking about the solution in terms of technical aspects, reading code reviews. The rest are meetings, coordination, administrative tasks, being blocked or whatever else you can think of. Even if, wishfully thinking, the value of the act of "coding work" fell by 90%, the act of doing "software engineering" work would still cost no less than 50% of what it currently does. Headlines like these are alarmist and have little substance.

Edit: I also feel stumped why so many people give in to this hype that LLMs are good at coding when they can't even do seemingly simple tasks of plain English language summarization accurately as evidenced in https://www.youtube.com/watch?v=MrwJgDHJJoE. If the AI summarizes the code in its own context incorrectly then it will not be able to write it correctly either.

burnerRhodov2• 7 months ago

from my perspective, this is exactly where we are. Have you ever watched starter story? There's hundreds of people with 5,6+ apps making 100k+ MRR. The VC model is broken because of it.

bdavid21wnec3• 8 months ago

I keep seeing articles like these popup. I am in the industry but not in the “AI” industry. What I have no concept of, is the current subsidized, VC funded, anywhere close to what the final product will be? I always fall back to the Uber paradox. Yes it was great at first, now it’s 3x what it cost and has only given cabs pricing power. This was good for consumers to start but now it’s just another part of the k shaped economy. So is that ultimately where AI goes? Top percent can afford a high monthly subscription and the not so fortunate get there free 5 minutes per month

martinald7• 8 months ago

But even if that did happen, the open source models are excellent and cost virtually nothing?

Like I prefer Opus 4.5 and Gemini 3 to the open weights models, but if Anthropic or Google upped the pricing 10x then everyone would switch to the open weights models.

Arguably you could say that the Chinese labs may stop releasing them, true, but even if all model development stopped today then they'd still be extremely useful and a decent competitor.

bdavid21wnec3• 8 months ago

Again I’m not in the “AI” industry so I don’t fully understand the economics and don’t run open models locally.

What’s the cost to run this stuff locally, what type of hardware is required. When you say virtually nothing, do you mean that’s because you already have a 2k laptop or gpu?

Again I am only asking because I don’t know. Would these local models run OK on my 2016 Mac Pro intel or do I need to upgrade to the latest M4 chip with 32GB memory for it to work correctly?

e10jc• 8 months ago

I totally agree with you. I am working on a new platform right now for a niche industry. Maybe theres $10m ARR to make total in the industry. Last year, it wouldn’t be worth the effort to raise, hire a PM, a few devs, QA, etc. But for a solo dev like myself with AI, it definitely is worth it now.

jdmoreira3• 8 months ago

I must be holding wrong then because I do use Claude Code all the time and I do think its quite impressive… still I cant see where the productivity gains go nor am I even sure they exist (they might, I just cant tell for sure!)

hurturue2• 8 months ago

if you back and forth with the model, and discuss/approve every change it does, that's the problem.

you need to give it a bigish thing so it can work 15 min on it. and in those 15 min you prepare the next one(s)

jdmoreira3• 8 months ago

Sure. But am I supposed to still understand that code at some point? Am I supposed to ask other team members to review and approve that code as if I had written it?

I'm still trying to ship quality work by the same standards I had 3 or 5 years ago.

azov• 8 months ago

If the cost of building software dropped so much - where is that software?..

Was there an explosion of useful features in any software product you use? A jump in quality? Anything tangible an end user can see?..

Anamon5• 7 months ago

This is also one of my arguments. I'm exaggerating, of course, but to me it feels like major software products and services haven't been adding new features for years now. What we get with updates these days are new restrictions on use, and "streamlining", i.e. the removal of features. Usually with the justification that the effort to maintain them was too high.

I used to look at release notes excited about what new features I might get. Now I read them with some level of anxiety. I hope none of the inevitably removed features are ones I used.

The AI evangelist talks to me about 10×. Meanwhile, all the software I use is becoming less functional, less configurable, less powerful, less secure, less stable, and in general crappier by the day.

atmavatar• 8 months ago

Has the cost of building software just dropped 90%?

I believe Betteridge's law of headlines [1] applies here:

No.

1. https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...

zackmorris• 8 months ago

*90% so far..

I've only been working with AI for a couple of months, but IMHO it's over. The Internet Age which ran 30 years from roughly 1995-2025 has ended and we've entered the AI Age (maybe the last age).

I know people with little programming experience who have already passed me in productivity, and I've been doing this since the 80s. And that trend is only going to accelerate and intensify.

The main point that people are having a hard time seeing, probably due to denial, is that once problem solving is solved at any level with AI, then it's solved at all levels. We're lost in the details of LLMs, NNs, etc, but not seeing the big picture. That if AI can work through a todo list, then it can write a todo list. It can check if a todo list is done. It can work recursively at any level of the problem solving hierarchy and in parallel. It can come up with new ideas creatively with stable diffusion. It can learn and it can teach. And most importantly, it can evolve.

Based on the context I have before me, I predict that at the end of 2026 (coinciding with the election) America and probably the world will enter a massive recession, likely bigger than the Housing Bubble popping. Definitely bigger than the Dot Bomb. Where too many bad decisions compounded for too many decades converge to throw away most of the quality of life gains that humanity has made since WWII, forcing us to start over. I'll just call it the Great Dumbpression.

If something like UBI is the eventual goal for humankind, or soft versions of that such as democratic socialism, it's on the other side of a bottleneck. One where 1000 billionaires and a few trillionaires effectively own the world, while everyone else scratches out a subsistence income under neofeudalism. One where as much food gets thrown away as what the world consumes, and a billion people go hungry. One where some people have more than they could use in countless lifetimes, including the option to cheat death, while everyone else faces their own mortality.

"AI was the answer to Earth's problems" could be the opening line of a novel. But I've heard this story too many times. In those stories, the next 10 years don't go as planned. Once we enter the Singularity and the rate of technological progress goes exponential, it becomes impossible to predict the future. Meaning that a lot of fringe and unthinkable timelines become highly likely. It's basically the Great Filter in the Drake equation and Fermi paradox.

This is a little hard for me to come to terms with after a lifetime of little or no progress in the areas of tech that I care about. I remember in the late 90s when people were talking about AI and couldn't find a use for it, so it had no funding. The best they could come up with was predicting the stock market, auditing, genetics, stuff like that. Who knew that AI would take off because of self-help, adult material and parody? But I guess we should have known. Every other form of information technology followed those trends.

Because of that lack of real tech as labor-saving devices to help us get real work done, there's been an explosion of phantom tech that increases our burden through distraction and makes our work/life balance even less healthy as underemployment. This is why AI will inevitably be recruited to demand an increase in productivity from us for the same income, not decrease our share of the workload.

What keeps me going is that I've always been wrong about the future. Maybe one of those timelines sees a great democratization of tech, where even the poorest people have access to free problem solving tech that allows them to build assistants that increase their leverage enough to escape poverty without money. In effect making (late-stage) capitalism irrelevent.

If the rate of increasing equity is faster than the rate of increasing excess, then we have a small window of time to catch up before we enter a Long Now of suffering, where wealth inequality approaches an asymptote making life performative, pageantry for the masses who must please an emperor with no clothes.

In a recent interview with Mel Robbins in episode 715 of Real Time, Bill Maher said "my book would be called: It's Not Gonna Be That" about the future not being what we think it is. I can't find a video, but he describes it starting around the 19:00 mark:

https://podcasts.musixmatch.com/podcast/real-time-with-bill-...

Our best hope for the future is that we're wrong about it.

keybored• 8 months ago

It’s over. I’ve been writing FUD manually since the 60’s. But people fresh out of FB troll boot camp are already rolling it out 99% faster than me.

weregiraffe• 8 months ago

Fudpocalypse is upon us. All is lost.

SoftTalker• 8 months ago

Where are the billions of dollars spent on GPUs and new data centers accounted for in this estimation?

bdavid21wnec3• 8 months ago

Ya completely agree, these companies will eventually push these costs to the consumer, might be in 1-2yrs, but it will eventually happen and though regulatory capture make it harder and harder to run local AI models because of “security” reasons.

tschellenbach• 8 months ago

It depends. For AI to work for large projects (did a post on this forever ago in AI terms. https://getstream.io/blog/cursor-ai-large-projects/)

But you need: a staff level engineer to guide it, great standardization and testing best practices. And yes in that situation you can go 10-50x faster. Many teams/products are not in that environment though.

andybak• 8 months ago

I work on a big ball of open source spaghetti and AI has become invaluable in helping me navigate my way through it. Even when it's wrong - it gives me valuable clues.

Agingcoder2• 8 months ago

One objection I hear a lot is that LLMs are only good at greenfield projects. I'd push back hard on this. I've spent plenty of time trying to understand 3-year-old+ codebases where everyone who wrote it has left.

Where I am, 3 year old is greenfield, and old and large is 20 years old and has 8million lines of nasty c++. I’ll have to wait a bit more I think …

glouwbug2• 8 months ago

The argument is building anew is 90% cheaper.

I can’t see LLMs contributing to anything this size when they can’t remember what I said 4 messages ago

devnull3• 8 months ago

I think the cost of prototyping has definitely gone down.

Developing production grade software which you want to people to rely on and pay for it is not gone down so much. The "weak" link is still human.

Debugging complex production issues needs intimate knowledge of the code. Not gonna happen in next 3-4 years atleast.

glouwbug2• 8 months ago

These tools do two things:

1. Rob one’s understanding of the design and implementation

2. Give the unqualified enough confidence to contribute

vb-84482• 8 months ago

It's not just about "building" ... who is going to maintain all this new sub-par code pushed to production every day?

Who is going to patch all bugs, edge cases and security vulnerabilities?

soco• 8 months ago

The theory goes very simple, you tell the agent to patch the bug. Now the practice though...

fullstackwife2• 8 months ago

yeah, in practice: would you like to onboard a Boeing 747 where some of the bugs were patched by some agents,

what is the percentage risk of malfunction you are going to accept as a passenger?

Havoc4• 8 months ago

You are a senior expert. SENIOR EXPERT :D

[0] https://www.youtube.com/shorts/64TNGvCoegE

sdoering• 8 months ago

I happily got rid of a legacy application (lost the pitch, another agency now must deal with the shit) I inherited as a somewhat technically savvy person about a year ago.

It was built by real people. Not a single line of AI slop in it. It was the most fragile crap I had ever the misfortune to witness. Even in my wildest vibe coding a prototype moments I was not able to get the AI to produce that amount of anti patterns, bad shit and code that would have had Hitchcock running.

I think we would be shocked to see what kind of human slop out there is running in production. The scale might change, but at least in this example, if I had rebuilt the app purely by vibe coding the code quality and the security of the code would actually have improved. Even with the lowest vibe coding effort thinkable.

I am not in any way condoning (is this the right word) bad practices, or shipping vibe code into prod without very, very thorough review. Far from it. I am just trying to provide a counter point to the narrative, that at least in the medium sized business I got to know in my time consulting/working in agencies, I have seen quite a metric ton of slop, that would make coding agents shiver.

geon2• 8 months ago

The argument isn’t that all slop is AI, but that all AI is slop.

vb-84482• 8 months ago

AI doesn't overcome the limits of the one who is giving the input, like in pre-ai era SW, if the input sucks the output sucks.

What changed is the speed: AI and vibe coding just gave a turboboost to all you described. The amount of code will go parabolic (maybe it's already parabolic) and, in the mid-term, we will need even more swe/sre/devops/security/ecc to keep up.

neom3• 8 months ago

DigitalOcean version 1 was a duck taped together mash of bash, chron jobs and perl, 2 people out of 12 understood it, 1 knew how to operate it. It worked, but it was insane, like really, really insane. 0% chance the original chatgpt would have written something as bad as DO v1.

mountainriver2• 8 months ago

I hear this argument all the time but it seems to leave out code reviews

nsxwolf• 8 months ago

In teams of high performers who have built a lot of mutual trust, code reviews are mostly a formality and a stop gap against the big, obvious accidental blunders. "LGTM!"

I do not know or trust the agents that are putting out all this code, and the code review process is very different.

Watching the Copilot code review plugin complain about Agent code on top of it all has been quite an experience.

bagacrap5• 8 months ago

like a vibe coder knows what a code review is, or an LLM knows how to take feedback

Havoc4• 8 months ago

Nobody.

In fact looking at the vibecoders enthusiasm for serverless I’m expecting a sharp spike in surprise cloud bills never mind thinking about edge case

sublinear• 8 months ago

Perhaps the cost will drop over time, but it will be because writing code is becoming more accessible. It's not just because of AI, but the natural progress of education and literacy on the topic that would have happened anyway.

What I see are salaries stagnating and opportunity for new niche roles or roles being redefined to have more technical responsibility. Is this not the future we all expected before AI hype anyway? People need to relax and refocus on what matters.

cloogshicer• 8 months ago

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests)

I'd love to see someone do this, or a similar task, live on stream. I always feel like an idiot when I read things like this because despite using Claude Code a lot I've never been able to get anything of that magnitude out of it that wasn't slop/completely unusable, to the point where I started to question if I hadn't been faster writing everything by hand.

Claiming that software is now 90% cheaper feels absurd to me and I'd love to understand better where this completely different worldview comes from. Am I using the tools incorrectly? Different domains/languages/ecosystems?

fraud• 8 months ago

100% agreed. I use Claude Code to write 90% of my code at this point, but have found that it is genuinely worse than a junior at writing meaningful test cases. Most of the time it will make up interfaces or mock things incorrectly etc to the point where I just give up and write them myself. The bulk of the “tests” it writes test things which are meaningless (does the interface exist etc). This is with typescript + vitest with opus 4.5.

nonameiguess• 8 months ago

I don't really build software any more and have moved into other parts of the business. But I'm still a huge user of software and I'd just echo all the other comments asking if it's so easy to get all these great tools built and shipped, where are they? I can see that YouTube is flooded with auto-generated content. I can see that blogspam has skyrocketed beyond belief. I can see that the number of phishing texts and voicemails I get every day has gone through the roof. I don't see any flood of new CNCF incubating projects. I don't see that holy grail entire OS comparable to Linux but written in Rust. I don't see the other holy grail new web browser that can compete with Firefox, Chrome, and Safari. It's possible people are shipping more of the stripped down Jira clones designed for a team of ten that gets 60 customers and stops receiving updates after 2 years but that's not the kind of software that would be visible to me.

If you're replacing spreadsheets with a single-purpose web UI with proper access control and concurrent editing that doesn't need Sharepoint or Google Workspaces, fine, but if you're telling me that's going to revolutionize the entire industry and economy and justify trillions of dollars in new data centers, I don't think so. I think you need to actually compete with Sharepoint and Google Workspaces. Supposedly, Google and Microsoft claim to be using LLMs internally more than ever, but they're publicly traded companies. If it's having some huge impact, surely we'll see their margins skyrocket when they have no more labor costs, right?

Normal_gaussian• 8 months ago

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool. This would take me, or many developers I know and respect, days to write by hand.

I'm not sure about this. The tests I've gotten out in a few hours are the kind I'd approve if another dev sent then but haven't really ended up finding meaningful issues.

torben-friis• 8 months ago

Have you noticed how it's never "I got this awesome code!"? It's always "I got good code, trust me".

People say their prompts are good, awesome code is being generated, it solved a month's worth of work in a minute. Nobody comes with receipts.

dboreham2• 8 months ago

I keep seeing posts like this so I decided to video record all my LLM coding sessions and post them on YouTube. Early days, I only had the idea on Saturday.

Aeolun• 8 months ago

I find I get better tests if I use agents to generate tests.

martinald7• 8 months ago

Just to be clear, they weren't stupid 'is 1+1=2' type tests.

I had the agent scan the UX of the app being built, find all the common flows and save them to a markdown file.

I then asked the agent to find edge cases for them and come up with tests for those scenarios. I then set off parallel subagents to develop the the test suite.

It found some really interesting edge cases running them - so even if they never failed again there is value there.

I do realise in hindsight it makes it sound like the tests were just a load of nonsense. I was blown away with how well Claude Code + Opus 4.5 + 6 parallel subagents handled this.

blauditore• 8 months ago

These kind of future prediction posts keep coming, and I'm tired of them. Reality is always more boring, less extreme, and slower at changing, because there are too many factors involved, and the authors never account for everything.

Maybe we should collect all of these predictions, then go back in 5-10 years and see if anyone was actually right.

tobyjsullivan• 8 months ago

Despite a couple forward-looking statements, I didn’t read this as a prediction. It seems more of a subjective/anecdotal assessment of where things are in December 2025. (Yes, with some conjecture about the implications for next year.)

Overall, it echos my experience with Claude Opus 4.5 in particular. We’ve passed a threshold (one of several, no doubt).

aeonfox3• 8 months ago

Just to test out the OP articles theory, I was about to write some unit tests. I decided to let Opus 4.5 have a go. It did a pretty good job, but I spent probably as much time parsing what it had done as I would have writing the code from scratch. I still needed to clean it up, and of course, unsurprisingly, it had made a few tests that only really exercised the mocking it had made. A kind of mistake I wouldn't be caught dead sending in for peer review.

I'm glad the OP feels fine just letting Opus do whatever it wants without a pause to look under the covers, and perhaps we all have to learn to stop worrying and love the LLM? But I think really, here and now, we're witness to just another hype article written by a professional blogger and speaker, who's highly motivated to write engagement bait like this.

noodletheworld• 8 months ago

Yeah nah.

People posting stuff like this are clearly not doing it; they’re reading LinkedIn posts, toying with the tech and projecting what it looks like at scale.

That’s fair; but it’s also misguided.

Either try it yourself, or go and watch people (eg. @ArminRonacher) doing this at a reasonable scale and you can ground yourself in reality, instead of hype.

The tldr is: currently it doesn’t scale.

Not personally. Not at Microsoft. Not at $AI company.

Currently, as the “don’t change existing behaviour” constraint list goes up, the unsupervised agent capability goes down, and since most companies / individual devs don’t appreciate “help” that does something while breaking something else, this causes a significant hole in the “everyone can 10x” bed time story.

As mentioned in other threads; the cost and effort to produce new code is down, but the cost of producing usable code is, I guess, moderately on par with existing scaffolding tools.

Some domains where the constraints are more relaxed like image generation (no hands? Who cares?) and front end code (wrong styles? Not consistent? Who cares?) are genuinely experiencing a revolution like the OP was talking about.

…but generalising it to “all coding” appears to be like the self driving car problem.

Solvable? Probably.

…but a bit harder than people who don’t understands or haven’t tried to solve it themselves thought, or blogged about or speculated about.

Probably, there’s a much smaller set of problems that are much easier to solve… but it’s not happening in 2026; certainly not at the scale and rate the OP was describing.

You’ll notice, neither of us have self driving cars yet.

(Despite some companies providing cars that do drive themselves into things from time to time, but that’s always “user error” as I understand it…)

rprend• 8 months ago

In your heart you either believe something or you don’t. I am happy to live in a world where so many people follow the courage of their convictions, even if they sound insane or uncomfortable.

the_overseer• 8 months ago

Yeah yeah there is this guy with a weird moustache with some crazy ideas that we are being held down by these other group of people. We should definitely follow him. He sounds crazy but he seems so convincing. And look at the cool insignia and symbols! Did you know this salute was back from the Romans? - You circa 1920.

bitwize4• 8 months ago

Maybe I'm holding it wrong, but I don't actually see the huge productivity gains from LLM-assisted software development. Work is leaning on us to use AI—not requiring it yet, but we're at DEFCON 3, borderline 2 (DEFCON 1 being a Shopify situation). My team's experience is that it needs LOTS of handholding and manual fixing to produce even something basic that's remotely fit for production use.

I closed a comment from ~2.5y ago (https://news.ycombinator.com/item?id=36594800) with this sentence: "I'm not sure that incorporating LLMs into programming is (yet) not just an infinite generator of messes for humans to clean up." My experience with it is convincing me that that's just what it is. When the bills come due, the VC money dries up, and the AI providers start jacking up their prices... there's probably going to be a boom market for humans to clean up AI messes.

rmnclmnt2• 8 months ago

Can we also take into account the mental cost associates with building software? Because how I see it, managing output from agents is way more exhausting than doing it ourself.

And obviously the cost of not upskilling in intricate technical details as much as before (aka staying at the high level perspective) will have to be paid at some point

djmips3• 8 months ago

It is pretty hard work huh! I was surprised. In my case, I was doing a personal project but in the end I felt a little crispy although the result was succesful.

rmnclmnt2• 8 months ago

Honestly now I only use agents for very narrow surgical scopes to avoid feeling numbed. It removed the fun of actually dreaming and building things

MangoToupe3• 8 months ago

No. Not unless your business wasn't competitive to begin with

dclnbrght2• 8 months ago

Domain knowledge is the moat, we need to rethink career planning https://news.ycombinator.com/item?id=46197349

criemen2• 8 months ago

This takes a fairly large mindset shift, but the hard work is the conceptual thinking, not the typing.

But the hard work always was the conceptual thinking? At least at and beyond the Senior level, for me it was always the thinking that's the hard work, not converting the thoughts into code.

liampulles4• 8 months ago

I contracted briefly on a post-LLM-boom Excel modernization project (which ended up being consulting mainly, because I had to spend all my time explaining key considerations for a long-running software project that would fit their domain).

The company had already tried to push 2 poor data analysts who kind of new Python into the role of vibe coding a Python desktop application that they would then distribute to users. In the best case scenario, these people would have vibe coded an application where the state was held in the UI, with no concept of architectural seperation and no prospects of understanding what the code was doing a couple months from inception (except through the lens of AI sycophancy), all packaged as a desktop application which would generate excel spreadsheets that they would then send to each other via Email (for some reason, this is what they wanted - probably because it is what they know).

You can't blame the business for this, because there are no technical people in these orgs. They were very smart people in this case, doing high-end consultancy work themselves, but they are not technical. If I tried to do vibe chemistry, I'm sure it would be equally disastrous.

The only thing vibe coding unlocks for these orgs by themselves is to run headfirst into an application which does horrendous things with customer data. It doesn't free up time for me as the experienced dev to bring the cost down, because again, there is so much work needed to bring these orgs to the point where they can actually run and own an internal piece of software that I'm not doing much coding anyway.

Havoc4• 8 months ago

post-LLM-boom Excel modernization project

Well there is a terrifying thought

henning• 8 months ago

By making up numbers and not supplying any evidence, you can come to any conclusion you like! Then you get to draw a graph with no units on it. Finally, you can say things that are objectively false like "These assertions are rapidly becoming completely false".

bob1029• 8 months ago

In context of B2B SaaS products that require a high degree of customization per client, I think there could be an argument for this figure.

The biggest bottleneck I have seen is converting the requirements into code fast enough to prove to the customer that they didn't give us the right/sufficient requirements. Up until recently, you had to avoid spending time on code if you thought the requirements were bad. Throwing away 2+ weeks of work on ambiguity is a terrible time.

Today, you could hypothetically get lucky on a single prompt and be ~99% of the way there in one shot. Even if that other 1% sucks to clean up, imagine if it was enough to get the final polished requirements out of the customer. You could crap out an 80% prototype in the time it takes you to complete one daily standup call. Is the fact that it's only 80% there bad? I don't think so in this context. Handing a customer something that almost works is much more productive than fucking around with design documents and ensuring requirements are perfectly polished to developer preferences. A slightly wrong thing gets you the exact answer a lot faster than nothing at all.

sharpy• 8 months ago

I think AI can be really powerful tool. I am more productive with it than not, but a lot of my time interacting with AI is reviewing its code, finding problems with it (I always find some issues with it), and telling it what to do differently multiple times, and eventually giving up, and fixing up the code by hand. But it definitely has reduced average time it takes me to implement features. But I also worry that not everyone would be responsible and check/fix AI generated code.

CobrastanJorji3• 8 months ago

Man, that's a big title. I can't wait to see the data on how the cost has dropped so far.

AI Agents however in my mind massively reduce...

Nevermind. It's a vibe 90%.

marcosdumay2• 8 months ago

That. I was expecting some overview of the last couple of decades in a "There's no Silver Bullet" fashion.

Instead it's some guy that claims it takes a team to make CI/CD for something he can vibe-code in a day, and that agentic code totally solves the complexity problems caused by too much React.

bitwize4• 8 months ago

Even if that were true, so we've made development needlessly more complicated, only to gain back the time lost by running numberwang across enough datacenters to fill a small country? You haven't abstracted anything away, Morty, just created another layer of shit.

https://news.ycombinator.com/item?id=22601623

mlhpdx• 8 months ago

If software actually is 90% cheaper to build in 2026 there will be 10x the simple apps and abandonware to follow. Throwaway software like throwaway phones. It’ll be weird.

krupan3• 8 months ago

I love how LLMs have made everyone forget how hard it is to verify software correctness and how hard it is to maintain existing software. There is endless gushing about how quickly LLMs can write code. Whenever I point out the LLMs make a lot of mistakes people just wave their hands and say software is easy to validate. The huge QA departments at all software shops would beg to disagree, along with the CVE database, the zero day brokers, etc. But you know, whatever, they're just boomers right?

simonw2• 8 months ago

The cost of writing simple code has dropped 90%.

If you can reduce a problem to a point where it can be solved by simple code you can get the rest of the solution very quickly.

Reducing a problem to a point where it can be solved with simple code takes a lot of skill and experience and is generally still quite a time-consuming process.

mountainriver2• 8 months ago

I’ve found they are able to compose well, let it build small components and stitch them together

visarga• 8 months ago

That is a good approach, bottom up, manage complexity. But the general picture is - you set the direction and hold the model responsible, it does the actual work. Think of it as your work is the negative of the AI work, it writes the code, you ensure it tests that code. The better test harness you create, the better the AI works. The real task is to constrain the AI into a narrow channel of valid work.

loandbehold7• 8 months ago

Most of software work is maintaining "legacy" code, that is older systems that have been around for a long time and get a lot of use. I find Claude Code in particular is great at grokking old code bases and making changes to it. I work on one of those old code bases and my productivity increased 10x mostly due to Claude Code's ability to research large code bases, make sense of it, answer questions and making careful surgical changes to it. It also helps with testing and debugging which is huge productivity boost. It's not about its ability to churn out lots of code quickly: it's an extra set of eyes/brain that works much faster that human developer.

nuclearnicer• 8 months ago

This is great. Asking questions of library code is a big pattern of mine too.

Here's an example I saw on twitter. Asking an LLM to document a protocol from the codebase:

https://ampcode.com/threads/T-f02e59f8-e474-493d-9558-11fddf...

Do you think you will be able to capture any of this extra value? I think I'm faster at coding, but the overall corporate project timeline feels about the same. I feel more relaxed and confident that the work can be done. Not sure how to get a raise out of this.

dleeftink• 8 months ago

Although many tools exist, there still seems to a large context gap here: we need better tools to orient ourselves and to navigate large (legacy) codebases. While not strictly a a source graph or the like, I do think Enso like interface may prove successful here[0].

zmmmmm• 8 months ago

I've found this as well. In some cases we aren't fully authorised to use the AI tools for actual coding but even just asking "how would you make this change" or "where would you look to resolve this bug" or "give me an overview of how this process works" is amazingly helpful.

hello12343214• 8 months ago

this was really interesting to read.

locknitpicker5• 8 months ago

It's not about its ability to churn out lots of code quickly: it's an extra set of eyes/brain that works much faster that human developer.

This is the key take right here. LLMs excel at parsing existing content, summarizing it, and use it to explore scenarios and hypotheticals.

Even the best coding agents out there such as Claude Code or Gemini often fail to generate at the first try code that actually compiles, let alone does what it is expected to do.

Apologists come up with excuses such as the legacy software is not architected well enough to be easily parseable by LLMs but that is a cheap excuse. The same reference LLMs often output utter crap in greenfield projects they themselves generated, and do so after a hand full of prompts. The state of a project is not the issue.

The world is coming to the realization that the AI hype is not delivering. The talk of AI bubble is already mainstream. But like IDEs with auto complete, agents might not solve every problem but they are nevertheless useful and are here to stay. They are more a kin to a search engine where a user doesn't need to copy/paste code snippets to apply a code change.

The sooner we realize this, the better.

locknitpicker5• 8 months ago

Most of software work is maintaining "legacy" code, that is older systems that have been around for a long time and get a lot of use.

That's not the definition of legacy. Being there for a long time and getting lots of use is not what makes a legacy project "legacy".

Legacy projects are characterized by not being maintained and having little to no test coverage. The term "legacy" means "I'm afraid to touch it because it might break and I doubt I can put it back together". Legacy means resistance to change.

You can and do have legacy projects created a year or two ago. Most vibecoded apps fit the definition of legacy code.

That is why legacy projects are a challenge to agentic coding. Agents already output huge volumes of code changes that developers struggle to review, let alone assert it's correctness. On legacy projects that are in production, this is disastrous.

lambdaone• 8 months ago

Claude is insanely good at grunt-work maintenance coding, which is a fairly formulaic exercise that mostly requires RTFM and simple code changes that look a lot likw the surrounding code. Designing new things from scratch based on human specs is something which Claude still struggles with.

curiousgal• 8 months ago

I honestly don't know what code bases you guys are working with, for me I tried it with a large quant library (C++ 97) in an effort to modernize it and so far it's been nothing hit a waste of time. Similarly for a medium sized python quant codebase (3.6) trying to port it to 3.12, and it's also been a headache.

Jean-Papoulos• 8 months ago

I have the opposite experience. Claude can't get it all in the context window and make changes that will completely break something on the other side of the program.

Granted that's because the program is incredibly poorly written, but still, context window will stay a huge barrier for quite some time.

gcanyon• 8 months ago

The cost of writing simple code has dropped 90%.

Need to add, “…and what ‘simple’ means is getting broader by the day.”

qazxcvbnmlp• 8 months ago

and varies person to person

especially based on their prompting skills

RajT884• 8 months ago

I would add "predictable" to that as well.

I fed Claude Pro a REST API spec and told it to spit out a Powershell module and well... So far that 27k lines of code largely checks out (minus the undocumented stuff I knew about).

Getting it to write the pester scripts was a very different matter...

almosthere3• 8 months ago

Most code is simple, the fact that large complex systems are layers of simple code on top of itself, like garbage heaps at the dump, makes it complex. Sticking with the garbage analogy, the LLM is like upgrading from one shovel to an crew of 10 people with excavators to look for a lost Bitcoin hard drive.

Your project is still going to fail, but it will fail faster with the 10 excavators.

tclancy• 8 months ago

And pollute the world. Really good analogy.

shigawire• 8 months ago

Sometimes you just need to move trash around with low accuracy... In that case the excavator swarm is good enough.

edg5000• 8 months ago

The analogy I use is going from hand-farming or farm animals to large combines overnight. You still need all the knowledge abouw farming, but it amplifies and multiplies your ability.

ngc248• 8 months ago

Every use case has necessary complexity. The only things simple are CRUD apps.

dabockster• 8 months ago

And not everyone wants to use a cloud AI either. Remember that when tons of cash is on the table, things like license agreements become less enforceable and more of a "don't get caught in the cookie jar" thing. All it would take is something similar to what's going on with book authors/publishers - a major AI provider exposed as using other firms' proprietary code without even considering to get a license - to totally blow up the "safety" of cloud based coding agents.

Local models are becoming more and more capable but the tooling still needs to get better for those.

Terr_• 8 months ago

The cost of writing simple code has dropped 90%.

Plus there's a lot of simple code you shouldn't be writing either way, because it's in a library by now.

By their nature, LLMs will do their best with things that could be plagiarized.

mewpmewp22• 8 months ago

Aren't we having major issues with there being too many small libraries right now and dependency chain that grows exponentially? I have thought LLMs will actually benefit us a lot here, with not having to use a lib for every little thing (leftpad etc?).

vidarh2• 8 months ago

LLMs work great at identifying libraries I'd never have otherwise found and use them, as long as you ask them for solutions instead of micromanage how they should get things done.

freedomben• 8 months ago

Completely agree. In the past 12 months, I've had five or six use cases that I would not have bothered scripting or automating before, but I've cranked out scripts or even small web services in under an hour that get the job done using AI. It has really revolutionized the super small bite-sized issues

KellyCriterion3• 8 months ago

exactly this! You can do things nearby with one prompt which would have taken weeks before to tinker around; esp. ClaudeAI is very good with "give a detailed first prompt and some context sourcefiles and create a working example on first shot".

E.g. I have to deal with lot of reports and those are usually "never fully developed" because "we can add this one row/feature later" because "management want us to ship early". Now I can enhance our reports by whatever metric just by handing over a current XLSX-exportcode and tell the LLM: "now i want additionally XY here...."

manquer• 8 months ago

Yes, but for experienced engineers that is still a huge huge change .

Even 12 months ago simplifying tasks alone was insufficient, you still needed a large group engineers to actually write, review and maintain a typical product for solid startup offering. This came with the associated overhead of hiring and running mid sized teams.

A lot of skilled people (y)our age/experience are forced into doing people management roles because there was no other way to deliver a product that scales(in team and complexity not DAU).

A CTO of mid-stage startup had to be good architect, a decent engineering manager, be deeply involved in product and also effectively communicate with internal and external customers.

Now for startups setting up new you can either defer the engineering manager and people complexity lot latter than you did before. You could have a very senior but small team who can be truly 10x level and be more productive without the overhead of communication, alignment and management that comes with large teams.

----

tldr; Skilled engineers can generate outsized returns to orgs that set them up to be successful(far more than before), I can't say if compensation is reflecting this yet, if not it soon will.

conductr• 8 months ago

The funny thing is a lot of that was never really necessary per se. Tons of stories about great projects coming out of tiny teams. They’re not likely geniuses, they just had focus and clarity and a drive to GSD without excessive unproductive activity. I’ve long been a proponent of offshore developers for cost savings. You have to manage the process and people differently, but the output per dollar (pre AI) was phenomenal and when managing them I could put my brand of low touch management in place. Usually consisting of one weekly 1 hour meeting for everyone, then emphasizing nobody spins their wheels ever for more than an hour during the week without asking for help, then just making sure everyone was crystal clear on what we were working on and the priorities. I’ve never been a fan of sprints or really any unit of time block as a milestone because I don’t think it incentivizes people to finish early. I’m also not a perfectionist. If it’s spaghetti code and it works, great, we can clean it up on the next pass (within reason of course, but spirit is build, test, operationalize, then if it’s useful and has some staying power then refactor later. For all this, hiring cheap labor overseas has always made much more sense than hiring locally (in US) based on cost but also based one working style/culture. Somehow as labor rates shot up here in last couple of decades, people found excuses not to offshore. Some of it valid if you can’t manage the project correctly as it is different, but for me the solution has been to adapt my management style versus crying about it being difficult and hiring locally to be lazy. It always struck me as odd that startups and investors hadn’t leveraged the labor rate arbitrage opportunity that exists.

interstice• 8 months ago

While I would love for this to be true for financial and egotistical reasons, I have a growing feeling that this might not be true for long unless progress really starts to stall.

dimal• 8 months ago

I've actually gone in the other direction. A year ago, I had that feeling, but since then I've gotten more certain that LLMs are never going to be able to handle complexity. And complexity is still the real problem of developing software.

We keep getting more cool features in the tools, but I don't see any indication that the models are getting any better at understanding or managing complexity. They still make dumb mistakes. They still write terrible code if you don't give them lots of guardrails. They still "fix" things by removing functionality or adding a ts-ignore comment. If they were making progress, I might be convinced that eventually they'll get there, but they're not.

realusername• 8 months ago

Progress has stalled already, I didn't see much improvement in the past year for my real world tasks

cryptonector• 8 months ago

Yes, well, I think this makes that skill of problem reduction a very valuable skill.

TacticalCoder• 8 months ago

The cost of writing simple code has dropped 90%.

The cost of writing code has dropped 90%. The cost of maintaining code, which has always been the hardest part, has grown 90% ; )

trollbridge4• 8 months ago

Well said. The cost of building a CRUD has dropped 90%.

The open question is why people needed fancy AI tools like Claude to write CRUDs in the first place. These kind of tasks ought to be have been automated a long time ago.

sothatsit• 8 months ago

These kind of tasks ought to be have been automated a long time ago.

It’s much easier to write business logic in code. The entire value of CRUD apps is in their business logic. Therefore, it makes sense to write CRUD apps in code and not some app builder.

And coding assistants can finally help with writing that business logic, in a way that frameworks cannot.

IshKebab3• 8 months ago

These kind of tasks ought to be have been automated a long time ago.

People have been trying for literally decades. The problem is that there is just enough uniqueness to every CRUD app that you can't really have "the CRUD app".

I guess it's the sweet spot for AI at the moment because they're 95% all the same but with some fairly simple unique aspects.

raxxorraxor• 8 months ago

CRUD as a concept is flawed. It is more or less any computational system with input -> process -> output. Just as this abstract system can have any complexity, the same is true for any CRUD app.

You don't need Claude to write it. But you cannot generate solid web forms with the same speed. What usually would have taken you a few hours is now solved in much less time.

I doubt software will get cheaper though, requirements will adapt.

eloisant• 8 months ago

That went 90% down even before AI, Rails and the other frameworks, libraries, tooling have made a big difference compared to earlier years.

The number of lines of code to be written is much, much lower than in the early 2000's.

rsynnott2• 8 months ago

These kind of tasks ought to be have been automated a long time ago

They have been, repeatedly, since the 70s. See dBase, Clipper, Microsoft Access, Hypercard, Ruby on Rails, stretching Wordpress to within an inch of its life, all manner of "no-code" things...

And, honestly, Excel. People do all manner of terrifying things with Excel, and it is unquestionably the most successful, and arguably the _only_ successful, "we can do this thing instead of employing a programmer" tool.

Generally, one of two things has happened. Either (a) the products of such automation become unmaintainable nightmares (common for the more automated approaches like MS Access) or (b) they become complex enough that they tend towards 'normal' programming (common with, say, Rails, where you could get a simple CRUD with basically just DSL, but realistically eventually you're gonna be writing lots of Ruby).

I feel like LLM-produced stuff is probably going to fall into column A.

janpmz• 8 months ago

At the leafs of the branches I'm comfortable to just generate code (e.g. a popup dialog). But I want to have a good grasp of code that is central of the application.

danmaz74• 8 months ago

I wouldn't say that the distinction is so much about code being "simple", but about code being made of patterns common enough in online examples. Claude Code and similar can write even very complex code, as long as it's something they have been trained on.

dzonga• 8 months ago

pretty decent article - but what it misses is most of these agents are trained on bad code - which is open source.

so what does this mean in practice? for people working on proprietary systems (cost will never go down) - the code is not on github, maybe hosted on an internal VCS - bitbucket etc. the agents were never trained on that code - yeah they might help with docs (but are they using the latest docs?)

for others - the agents spit bad code, make assumptions that don't exist, call api's that don't exist or have been deprecated ?

each of those you need an experienced builder who has 1. technical know-how 2. domain expertise ? so has the cost of experienced builder(s) gone down ? I don't think so - I think it has gone up

what people are vibecoding out there - is mostly tools / apps that deal in closed systems (never really interact with the outside world), scripts were ai can infer based on what was done before etc but are these people building anything new ?

I have also noticed there's a huge conflation with regards to - cost & complexity. zirp drove people to build software on very complex abstractions eg kubernetes, nextjs, microservices etc - hence people thought they needed huge armies of people etc. however we also know the inverse is true that most software can be built by teams of 1-3 people. we have countless proof of this.

so people think to reduce cost is to use a.i agents instead of addressing the problem head-on - built software in a simpler manner. will ai help - yeah but not to the extent of what is being sold or written daily.

simonw2• 8 months ago

The idea that LLMs were trained on miscellaneous scraped low quality code may have been true a year ago, but I suspect it is no longer true today

All of the major model vendors are competing on how well their models can code. The key to getting better code out of the model is improving the quality of the code that it is trained on.

Filtering training data for high quality code is easier than filtering for high quality data if other types.

My strong hunch is that the quality of code being used to train current frontier models is way higher than it was a year ago.

Tepix• 8 months ago

these agents are trained on bad code - which is open source.

This is doubtful and not what I've seen in over 30 years in the industry. People who are ashamed of their source code don't make it Open Source. In general, Open Source will be higher quality than closed source.

Sure, these days you will need to avoid github repositories made by students for their homework assignments. I don't think that's a problem.

samlinnfer• 8 months ago

The cost of writing software had dropped by 90% since outsourcing was invented and all the software jobs have moved to India was I was told 15 years ago.

lisbbb2• 8 months ago

This article was more of an advertisement for...something than any meaningful commentary.

How good are tests written by AI, really? The junk "coverage" unit tests sure, but well thought out integration tests? No way. Testing code is difficult, some AI slop isn't going to make that easier because someone has to know the code and the infrastructure it is going in to and reason about all of it.

xdc0• 8 months ago

Betteridge's law proven correct once again. The answer to the headline is: no. Perhaps it will be true in the future, nobody knows.

I'm skeptical the extent to which people publishing articles like this use AI to build non-trivial software, and by non-trivial I mean _imperfect_ codebases that have existed for a few years, battle tested, with scars from hotfixes to deal with fires and compromises to handle weird edge cases/workarounds and especially a codebase where many developers have contributed to it over time.

Just this morning I was using Gemini 3 Pro working on some trivial feature, I asked it about how to go about solving an issue and it completely hallucinated a solution suggesting to use a non-existing function that was supposedly exposed by a library. This situation has been the norm in my experience for years now and, while this has improved over time, it's still very, very common occurrence. If it can't get these use cases down to an acceptable successful degree, I just don't see how much I can trust it to take the reins and do it all with an agentic approach.

And this is just a pure usability perspective. If we consider the economics aspect, none of the AI services are profitable, they are all heavily subsidized by investor cash. Is it sustainable long term? Today it seems as if there is an infinite amount of cash but my bet is that this will give in before the cost of building software drops by 90%.

Pannoniae• 8 months ago

I asked it about how to go about solving an issue and it completely hallucinated a solution suggesting to use a non-existing function that was supposedly exposed by a library.

Yeah, that's a huge pain point in LLMs. Personally, I'm way less impacted by them because my codebase is only minimally dependent on library stuff (by surface area) so if something doesn't exist or whatever, I can just tell the LLM to also implement the thing it hallucinated :P

These hallucinations are usually a good sign of "this logically should exist but it doesn't exist yet" as opposed to pure bs.

CobrastanJorji3• 8 months ago

I love the hand drawn chart. Apparently "Open Source" was invented around 2005, which significantly reduced development cost, then AWS was invented in 2011 or so and made development even cheaper, but then, oh no, in 2018 "complexity" happened and development became harder!

zqna• 8 months ago

In 2018 We had kubernetes, which improved the development speed another 300%!

RajT884• 8 months ago

Kubernetes with production workloads allowed companies to finally realize the "fail fast" ethos.

jcelerier• 8 months ago

I don't read this as when open-source was invented, but when it happened for the corporate world. In 2002 it was a very reasonable choice for $BIG_COMPANY to use a proprietary web server, e.g. IIS. In 2008 that would have been really be weird.

CobrastanJorji3• 8 months ago

But why did that make development cheaper? An enterprise copy of Windows with IIS cost maybe a thousand bucks, right? Maybe there were more costs, my knowledge is, y'know, 23 years out of date.

lelanthran• 7 months ago

In the 90s windows was shipping with components cribbed from open source (and properly attributed).

It's not something new.

khannn• 8 months ago

AI drawn chart and AI written article

alex-ross• 8 months ago

The cost of building "something" has dropped 90%. The cost of building "something good" has maybe dropped 30%.

The gap between a demo and a product is still enormous.

rudedogg• 8 months ago

The author teaches AI workshops. Nothing wrong with that, but I think it should be disclosed here. A lot of money is riding on LLMs being financially successful which explains a lot of the hype.

hoppp• 8 months ago

The cost of training agents is in the billions so Im not sure the cost dropped, it just shifted and now the cost distribution is different

hjaveed• 8 months ago

the cost of creating a great product and amount of time it takes to get infront of the customers has still not reduced

codyb• 8 months ago

Writing a giant unit test suite being the primary example that stuck out to me from that article really doesn't give a lot of credence to the question?

And yet, the conclusion seems to be as if the answer is yes?

Until AI can work organizationally as opposed to individually it'll necessarily be restricted in its abilities to produce gains beyond relatively marginal improvements (Saved 20 hours of developer time on unit tests) for a project that took X weeks/months/years to work it's way through Y number of people.

So sure, simple projects, simple asks, unit tests, projects handled by small teams of close knit coworkers who know the system in and out and already have the experience to differentiate between good code and bad? I could see that being reduced by 90%.

But, it doesn't seem to have done much for organizational efficiency here at BigCo and unit tests are pretty much the very tip of a project's iceberg here. I know a lot of people are using the AI agents, and I know a lot of people who aren't, and I worry for the younger engineers who I'm not sure have the chops to distinguish between good, bad, and irrelevant and thus leave in clearly extraneous code, and paragraphs in their documents. And as for the senior engineers with the chops, they seem to do okay with it although I can certainly tell you they're not doing ten times more than they were four years ago.

I kinda rambled at the end there, all that to say... organizational efficiency is the bug to solve.

(It's very difficult, I believe the 2D interfaces we've had for the last 40 years or whatever are not truly meeting the needs of the vast cathedrals of code we're working in, same thing for our organizations, our code reviews, everything man)

shusson• 8 months ago

The cost of generating lines of code which look good has dropped 90%.... Take that as you will.

ed_elliott_asc• 8 months ago

Im really liking it for writing boring code.

As an example I wanted a plugin for visual studio. In the past I would have spent hours on it or just not bothered but I used Claude code to write it, it isn’t beautiful or interesting code, it lacks tests but it works and saves me time. It isn’t worth anything, won’t ever be deployed into production, I’ll likely share it but won’t try to monetise it, it is boring ugly code but more than good enough for its purpose.

Writing little utility apps has never been simpler and these are probably 90% cheaper

skydhash• 8 months ago

A plugin that does what exactly? A lot of comments here and under other posts are just declaring things with the following template: "I wanted to do X, but before it would took me N amount of hours, but now with LLM tool L, it has taken me way less time. I can't share anything about X, but LLM tool L is very useful. Just trust me, bro"

foobarbecue2• 8 months ago

My favorite is this advert I keep getting that says "Imagine being able to build an app with your name on it!" I'm like... if you're struggling with the part where you put your name on it... and that's the priority.. I don't know what to tell you.

Ah, here it is: https://www.youtube.com/watch?v=-FEWLvKztD0

mikewarot• 8 months ago

This wouldn't be the first time that the cost of software radically dropped. It happened back during the early 1960s for the first time when IBM introduced the System 360, which included backward compatibility for the 1401. Prior to this point, the maximum lifespan of software was tied to that of the computer in question. The software would be re-written for the next architecture, every time a new computer was purchased.

The advent of the PC, and the appearance of Turbo Pascal, Visual Basic, and spreadsheets that could be automated made it possible for almost anyone to write useful applications.

If it gets cheaper to write code, we'll just find more uses for it.

ls-a• 8 months ago

My tell-tale sign that AI is moving the needle is the disappearance of the concept of leetcode. If you've done an interview lately you would know AI hasn't moved any needles yet

jdswain• 8 months ago

Software Development is much more than writing code. Writing code may have become 90% easier, but a lot of the other development tasks haven't appreciably changed due to AI, although that might come. So, for now at least the answer to the question posed in the headline is no.

An exception might be building something that is well specified in advance, maybe because it's a direct copy of existing software.

vinipolicena• 8 months ago

Software engineering has got - in my opinion, often needlessly - complicated, with people rushing to very labour intensive patterns such as TDD, microservices, super complex React frontends and Kubernetes.

TDD as defined by Kent Beck (https://tidyfirst.substack.com/p/canon-tdd ) doesn't belong in that list. Beck's TDD is a way to order work you'd do anyway: slice the requirement, automate checks to confirm behavior and catch regressions, and refactor to keep the code healthy. It's not a bloated workflow, and it generalizes well to practices like property-based testing and design-by-contract.

Glyptodon• 8 months ago

I'd like to believe that this is the case, and it may well be the case that we do end up there.

But currently reproduceability, reliability, correctness, and consistency are lacking.

There's also meaningful domain variance.

nrhrjrjrjtntbt2• 8 months ago

Building yes. Maintaining no.

Cars wont be cheap because bumper prices fell 90%

But....

Obviously AI is coming for the whole car so I will operate on tbe assumption 90% is coming. We will eventually be agentic orhcestra conductors.

dubeye• 8 months ago

it has for me. I'm probably paying less than 10%, saving on seas, occasional contract fees for custom integrations, and zapier fees linking them together.

I've no idea what's going on in the enterprise space, but in the small 1-10 employee space, absolutely

djmips3• 8 months ago

It's fascinating to read these comments - I believe everyone. Some are getting huge productivity gains and others very little - so perhaps we are not in the same business. I know that I've ranged over various work - all called software development and the variety of work was quite different - some I wouldn't call challenging but still needed a lot of manual labor - perhaps this is the type of work that finds easy wins from AI automation. Still other work was much more challenging but I've never really attempted to use AI in my work because it was forbidden by policy. I've used AI at home for fun projects and it has helped me with languages I've never used before but I've never come close to 90% productivity boost. Anyway, fascinating!

ehnto• 8 months ago

I agree with your observations, in my own job I cover a great deal of the aspects of all software development practices for a few clients. Probably something you'd normally have a bunch of different roles do. Not because of AI, I have been in this role since before the AI boom, this is just how agency work is sometimes.

My observation is that there is perhaps 15% of my job that has been boosted by AI by quite a lot, and the rest it hasn't touched much at all. Most of the job just isn't coding badically. The code generation aspect is a bit flawed too because to get good results I often spend more time collating requirements and engineering the prompt that I again could have just done it quicker myself.

There is a sweet spot in there where the requirements were easy to write out, and the code was simple enough but there is a lot to write, that it's nice to not have to write it myself. But even then I am finding that AI is often not successful, and if it takes three tries to get it to do the work properly then there is no productivity gain. Often enough time is lost to the failed attempts.

Usually there isn't that much code to write, but it's fairly complex and needs to be correct, which is where I find LLMs have too many failed attempts and waste time.

(I am an 18+ year "everything" developer, my experiences are from using Claude Code)

nelox• 8 months ago

How we would design a rigorous study that measures total cost of ownership when teams integrate AI assistance, including later maintenance and defect rates, rather than just initial output speed?

arach• 8 months ago

this probably levels the playing field for a while, and then dramatically raises the bar over a longer period of time

as better engineers and better designers get more leverage with lower nuisance in the form of meetings and other people, they will be able to build better software with a level of taste and sophistication that wouldn't make sense if you had to hand type everything

0xbadcafebee• 8 months ago

I think the whole software industry has tried to obscure the fact that most companies who hire software engineers are writing exactly the same code as every other company. How many people here have written the same goddamn webapp at the last 3 companies they've been to? Anyone ever wonder why nobody just publishes blueprints to software and licenses that blueprint to a single engineer to customize? Because there's a lot less money in doing that, versus selling a lot more software add-ons/SaaS/etc.

There is no value-add to hiring software engineers to build basic apps. That's what AI will be good for: repeating what has already been written and published to the web somewhere. The commoditized software that we shouldn't have been paying to write to begin with.

But AI won't help you with all the rest of the cost. The maintenance, which is 80% of your cost anyway. The infrastructure, monitoring, logging, metrics, VCS hosting, security scanning, QA, product manager, designer, data scientist, sales/marketing, customer support. All of that is part of the cost of building and running the software. The software engineers that churn out the initial app is a smaller cost than it seems. And we're still gonna need skilled engineers to use the AI, because AI is an idiot savant.

Personally I think 50% cost reduction in human engineers is the best you can expect. That's not nothing, but that's probably like a 10% savings on total revenue expenditure.

KellyCriterion3• 8 months ago

> infrastructure, monitoring, logging, metrics, VCS hosting, security scanning, QA <<

Well, arent these the topics for what we have AI-managed infrastructure now? :-D LOL

BloondAndDoom• 8 months ago

Can someone help me out how to get started in this kind of coding setup?

I haven't written production code for the last 8 years, but has prior development experience for about 17 years (ranging from C++, full stack, .NET, PHP and bunch of other stuff).

I used AI at personal level, and know the basics. Used Claude/Github to me help fix and write some pieces of the code in languages I wasn't familiar with. But it seems like people talking and deploying large real world projects in short-"er" amount of time. An old colleague of mine whom I trust mentioned his startup is developing code 3x faster than we used to develop software.

Is there resource that explains the current best practices (presumably it's all new)? Where do I even start?

lrsaturnino• 8 months ago

The cost of building the first version of FB has dropped 90% The cost of building the next FB stays the same

More sophisticated tools mean more refined products.

If an easier and cheaper method for working carbon fiber becomes broadly available, it won't mean you get less money; it means you'll now be cramming carbon fiber in the silverware, in the shoes, in baby strollers, EVERYWHERE. The cost of a carbon fiber bike will drop 90%, but teams will be doing a LOT more.

You could say the cost per line of code has dropped 90%, but the number of lines of code written will 100x.

jmward01• 8 months ago

I am a believer in the new agentic coding tools (I wasn't 6 months ago) but the delays and time it takes to build something haven't really changed even though everyone I know is using them. What I see is what has always been there:

Product doesn't understand the product because if it was easy to understand then someone else would have solved the problem already and we wouldn't have jobs. This means you need to iterate and discuss and figure out just like always. The iterations can be bolder, bigger, etc and maybe a bit faster but ultimately software scales np so a 10x improvement in -individual- capability doesn't scale to 10x improvement in -organizational- capability.

Let me put it another way. If your problem was so simple you could write a 200 word prompt to fully articulate it then you probably don't have much of a moat and aren't providing enough value to be competitive.

DrewADesign5• 8 months ago

As I said in a previous post:

I think the 90/90 rule comes into play. We all know Tom Cargill quote (even if we’ve never seen it attributed):

The first 90 percent of the code accounts for the first 90 percent of the development time. The remaining 10 percent of the code accounts for the other 90 percent of the development time.

It feels like a gigantic win when it carves through that first 90%… like, “wow, I’m almost done and I just started!” And it ‘is’ a genuine win! But for me it’s dramatically less useful after that. The things that trip up experienced developers really trip up LLMs and sometimes trying to break the task down into teeny weeny pieces and cajole it into doing the thing is worse than not having it.

So great with the backhoe tasks but mediocre-to-counterproductive with the shovel tasks. I have a feeling a lot of the impressiveness depends on which kind of tasks take up most of your dev time.

If your job is pumping out low-effort websites that are essentially marketing tools for small businesses, it must feel like magic. I think the more magical it feels for your use case, the less likely your use case will be earning you a living 2 years from now.

janalsncm• 8 months ago

Yeah, I think the more your job demands correctness in novel scenarios the less impressed you are with these shiny demos. I encourage anyone to pause the demo once the thing is generated and stare at what it did. Is it genuinely correct and impressive? Are you impressed because it made a thing generally shaped like what you expected, or because it would be genuinely impressive (or even adequate) if a person did it?

saikia812• 8 months ago

you are right, but the inverse doesn't have to be. There is a factor that could make the work so cheap, that people don't care about the quality anymore.

ewoodrich• 8 months ago

Fully agreed, aligns perfectly with my experience hitting the 95% done wall on a solo contract project recently. I still do the majority of work using agentic tools but the multiplier effect feeling evaporated at a certain point as the accumulated tech debt, complexity and scope creep enabled by how “easy” features felt with Claude Code/Codex early on finally caught up to me.

I (probably) still would have used CC heavily with benefit of hindsight but with a view that every seemingly “trivial” feature CC adds in the greenfield stage to be radioactive tech debt as the pile grows over time. Until reaching the point where CC starts being unable to comprehend its own work and I have to plan out tedious large scale refactors to get the codebase into a state approaching long term maintainability.

DrewADesign5• 8 months ago

It’s always tempting to start writing code before you really know what you’re going to build because it’s so satisfying and exciting to see an idea take shape. I know I’ve had more than one or two projects where I started writing before I understood the shape of the problem I was solving and ended up a few hours into the project with a useless pile of stupid. It seems like LLMs can lead you much further down that road because it just seems so magically productive.

adammarples• 8 months ago

One thing I've noticed is that Claude is so good at doing things that I've asked for, that later on I realise that I shouldn't have even been doing them because they're stupid or unnecessary but Claude was just cheerleading me on and emoji spamming tick marks so that I didn't realise there was very little purpose to the feature.

DrewADesign5• 8 months ago

Yeah once you start working at the feature level, you’re into product design, and that’s an entirely different realm of working that, IMO, shouldn’t even involve code. Even higher-level software design —e.g. broad stroke architecture like figuring out your data model and how it will be accessed— is better off being done before any significant amount of code gets written. Claude, et al will happily walk you straight off a cliff if you ask it to, and not having that stuff sketched out ahead of time is a most efficient way of accidentally doing that.

kalx• 8 months ago

Let’s say you’re right. Do we still want to, though? I mean. At some point we will no longer have the skill to babysit the AI agent.

turtletontine• 8 months ago

When the LLM code bases are too complex for the humans on deck to understand and debug… that sounds like the turning point when companies go back to real developers IMO. Any serious mission critical code needs knowledgeable humans on deck who can leap into again when s** hits the fan, put out fires and patch critical bugs.

onraglanroad2• 8 months ago

Not if you can have the AI rewrite your entire stack in 5 minutes and you just deploy that. CR/CD ftw! (continuous rewrite/continuous deployment)

est• 8 months ago

The cost of building droppped by 90% but the cost of maitaining is increased by 9000%

Havoc4• 8 months ago

Next quarters problem

gaigalas• 8 months ago

I think the author underestimate the forces that introduce coordination overhead.

"Good AI developers" are a mystery being (not really, but for corporate they are). Right now, companies are trying to measure them to understand what makes them tick.

Once that is measured, I can assure you that the next step is trying to control their output, which will inevitably kill their productivity.

This then allows developers who really master this technology to be hugely effective at solving business problems.

See what I mean?

"If only we could make them work to solve our problems..."

You can! But that implies additional coordination overhead, which means they'll not be as productive as they were.

Your job is going to change

My job changes all the time. Developers are ready for this. They were born of change, molded by it. You know what hasn't caught up with the changes?

reactordev• 8 months ago

The cost of writing software dropped but the complexity ballooned so we’re on the side of needing ai assistants to write it all for us.

m0llusk• 8 months ago

It will be interesting how this goes moving forward. Agents learn from massive scraping. With the newest tools and frameworks there is nothing but documentation and initial examples to scrape. And now that agent output is flooding everything it can be expected there will be a lot of feedback with automated learning early in development cycles.

Lots of applications have a simple structure of collecting and operating data with fairly well documented business logic tying everything together. Coding outside of that is going to be more tricky.

And if agentic coding is so great then why are there so still so many awful spreadsheets that can't compete with Excel? Something isn't adding up quite as well as some seem to expect.

hexo• 8 months ago

No, it did not. Thanks for asking.

maddmann2• 8 months ago

I strongly agree. It may be even more than 90%. For example yesterday I was able to use lovable (and Claude code web) on my phone to build out an almost 1:1 replacement (for my purposes) for an expensive subscription based app for working out: https://strengthquest.lovable.app/

This is simply unimaginable level of productivity— in one day on my phone, I can essentially build and replace expensive software. Unreal days we are living in.

tehjoker4• 8 months ago

This is the kind of piece that becomes popular around the top of the hype cycle when people are trying to keep it going but can sense that perhaps Wiley E coyote has run off the cliff and is suspended in the air. Obviously, by any possible objective indicator, the cost of software development has barely budged and "AGI" is nowhere in the offing while luminary scientists appear to be drawn to whatever the next big thing is, having seen the limits of their (admittedly impressive) creation.

I'm sure that AI tools will be here to stay and will become more integrated and better. I wonder what the final result will be, -20% productivity as in the METR study? +20%? Anything like 90% is the kind of sensationalism reserved for r/WallStreetBets

jbruton• 8 months ago

Betteridge's law of headlines applies here. https://en.wikipedia.org/wiki/Betteridge's_law_of_headlines

culi• 8 months ago

The only cost that's dropped by 90% is writing unoriginal blog posts

phendrenad2• 8 months ago

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool. This would take me, or many developers I know and respect, days to write by hand.

I should have stopped reading here. People who think that the time it takes to write some code is the only metric that matters are only marginally better than people who rank employees by lines of code.

chasing• 8 months ago

Alternate take: The cost of building software will remain the same but software will need to be 10x as feature-rich to remain competitive.

If you can build it in a weekend so can I. So you're going to have to figure out bigger things to build.

seanmcdirmid• 8 months ago

We might actually get all the software we actually need. We won’t have to listen to antiquated DMV/IRS/health systems not being updated because the projects designed to replace them failed.

laughing_man• 8 months ago

I'll believe that when I see it.

d--b• 8 months ago

Jevons Paradox says that when something becomes cheaper to produce, we don't just do the same amount for less money. Take electric lighting for example; while sales of candles and gas lamps fell, overall far more artificial light was generated.

Can’t wait to debug all that stuff.

foobarbecue2• 8 months ago

How is it that some people feel comfortable just making up numerical statistics out of thin air?

joeyguerra• 8 months ago

Yes.

nurettin• 8 months ago

For me, the cost of motivating myself dropped significantly. I now feel like working on little things that have been pending tasks for ages. A db synch script here , an unearthed project from 12 years ago there , migrating project package versions , finding and fixing incomplete/missing data , refactoring legacy code to be suitable for unit testing , installing a bunch of cron jobs all in a day's work.

seinecle• 8 months ago

To nick pick, it is more about 800% gain in productivity. Cost actually increased.

I refer here to my experience as a solo developer.

With AI assistance I don't spend less hours coding, but more.

There is the thrill of shipping relevant features that were sleeping in my drawers for ages, quicker. Each hour of coding delivers just 8 x more features and bug solving.

Also, whereas I spent a few dozen dollars per month on server costs, I now also spend an equivalent amount on subscriptions and API calls to LLM services for this AI assisted coding. Worth every penny.

So while productivity increased manifold, absolute cost actually increased as well for me.

gloosx• 8 months ago

From the creators of the 10x engineer:

0.1x engineering cost

112233• 8 months ago

From the article:

"I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool"

Did you catch what the author didn't mention? Are the tests any good? Are they even tests? I'm playing with Opus now (best entertainment for a coder), it is excellent at writing fake code and fabricating results. It wrote me a test that validates an extremely complex utility, and the test passed!

What was the test? Call utility with invalid parameters and check that there is an error.

DeathArrow• 8 months ago

Software engineering has got - in my opinion, often needlessly - complicated, with people rushing to very labour intensive patterns such as TDD, microservices, super complex React frontends and Kubernetes.

Let's say it is complicated. But what is the better alternative when dealing with large software? To what point we can simplify it and not lose anything important?

_pdp_• 8 months ago

The majority of vibe coded software I have seen (and produced) are similar to spreadsheets - it does the job for 5 minutes - easily forgettable.

It is throwaway software at best.

What AI did was to move the goalpost even further. Now you need to write exceptional software.

asilis• 8 months ago

I'd rather inherit a repo written with an agent and a good engineer in the loop than one written by a questionable quality contractor who left three years ago, with no tests, and a spaghetti mess of classes and methods.

Oh, false dilemma :/

harishpanwar9• 8 months ago

This is a fascinating perspective — and honestly, it feels like one of those shifts we’ll only fully recognize in hindsight. The idea that software development could transition from months of coordination and engineering overhead to rapid iteration with small, high-leverage teams is both exciting and a little uncomfortable.

The 90% cost reduction isn’t just about efficiency — it’s about access. If the barrier to shipping software drops this dramatically, we’re likely standing at the edge of a new wave of innovation driven not just by engineers, but by domain specialists who previously couldn’t justify the investment.

The most interesting takeaway here is that technical mastery may become less of the moat, while contextual and domain intelligence becomes the real differentiator. That flips the traditional power structure in tech.

2026 might really be the year where “build fast, throw away, rebuild smarter” becomes normal instead of reckless.

Curious to see how fast organizations adapt — and who gets left behind simply because they assumed disruption would arrive slower.

dvh• 8 months ago

emdashes
isn’t just

How do you do fellow human

Anamon5• 7 months ago

Fair indicators, although I'd say the fresh user account and the lack of any concrete meanings in the statements are even more telling.

Saying this partly in self-defense – as a human who likes using en dashes and ellipses in my manual writing…

Besides, I wonder why people do this. What's the motivation? Is there some way of financially profiting from writing comments on HN that I'm unaware of?

blobbers2• 8 months ago

I am shocked by the number of people who are dismissive of AI, or have stuck to the whole copy and paste into a chatbot approach to development.

I'm finding this stuff, when given proper guidance, can reproduce experiments I've run incredibly fast. Weeks of typing done in minutes of talking to Claude Code.

In the working world, a lot of the time what matters is getting results, not writing 'perfect' code the way software engineers would like to.

concerns: - security bugs - business logic errors that seem correct but are wrong

as long as you have domain experts, I suspect these will gradually go away. hopefully LLMs can be trained not to do insecure things in code.

liampulles4• 8 months ago

In the working world, a lot of the time what matters is getting results, not writing 'perfect' code the way software engineers would like to.

But you do recognize that one's ability to speedily implement features is dependent on the present quality of a codebase, right? Being a serious practitioner here means balancing active feature development with active tending to the codebase to keep it in a reasonable state, since its quality will tend ever downward otherwise.

In your experiments, do you find agents readily find this balance? I ask genuinely, I have only minimal experience with Cursor.

theshrike7913• 8 months ago

To be blunt and a bit nihilistic: I get paid to ship features.

Client wants a feature EoW, they get it EoW, they're not paying for a week of extra work for the "quality codebase" feature.

But the good thing is that we've had objective and automated tooling for quality checks for code. We used to use them for humans, but now we apply the same tools for AI.

Good unit testing practices, exhaustive linters, .editorconfig etc. force humans AND LLMs to produce code within specific parameters.

If your project doesn't have automated tests and linters, now is the time to add them. Maybe use an LLM to help you with it :)

thingortwo2• 8 months ago

I'm not dismissive of AI but I still do the whole "copy and paste" into chatbot approach simply because I use it as a boilerplate or research tool where the intent or workflows are already established and is targeted so it doesn't really matter how it writes since I can "parse" it's output quickly kind like an advance version of vscode saved snippet templates. I never use it do software design for me since this actually requires you understanding the problem but I can still use it to research existing stuff which is pretty cool.

arduinomancer3• 8 months ago

Not everyone is building web apps/web services

The more niche the thing you’re working on the worse results I’ve found these tools to give

SiempreViernes• 8 months ago

AI Agents however in my mind massively reduce the labour cost of developing software.

So the claim of massive cost reduction is just something the author made up (or hallucinated to use the lingo of the field)?

Seems like Betteridges law applies here.

o9992• 8 months ago

Some indirect results to this might be:

- More engineers moving from employment to indie development.

- Less abandoned open source software.

- Indie developers, small teams, and open source software developers will be more able to catch up and better compete with tech giants.

I believe the AI agentic coders will threat tech giants more than it - collectively - threats software engineers.

drcxd• 8 months ago

I believe the AI agentic coders will threat tech giants more than it - collectively - threats software engineers.

Currently, I don't think so. Coding agents' performance generally depends on the quality of the model behind them. Running a powerful model is assets-dependent. Not everyone has the hardware and power to support Sonnet 4.5 or Gemini 3 even if they are open-source. So, before the top notch models can be deployed on personal computing devices, I would not say coding agents will threat any organization.

o9992• 8 months ago

You don't have to self host, $100/engineer/mo is enough for many usecases.

otikik• 8 months ago

The cost of writing code has gone down - I don't think by 90%. Maybe by 30%, with a big asterisk that says something like "as long as someone has put some similar code somewhere or is a very mechanical refactor".

The thing is, writing code is just the first step on building software. You are reviewing what your AI generates, right? You will still be held responsible when it doesn't work. And you will have to maintain and support that code. That is, in my mind, also "building software".

This reminds me of the (amazing) Vim experts that zip around a codebase with their arcane keystrokes. I'm a main Vim user and I can't mimic a fraction of their power. It's mesmerizing to watch them edit files, it's as if their thoughs get translated into words on the screen.

I also know that editing is just the first step. If you skip the rest, you are being misled by an industry with vested interests.

j45• 8 months ago

Software becoming easier to build will mean it's possible to build far deeper into solving problems with software.

Cost is a funny misnomer. The best code that's written is the code that doesn't need to be written, and doesn't have to be supported.

Being able to build different approaches to solving a problem quickly may turn out to be a lot more helpful than saving 90%.

benrutter• 8 months ago

We should find out pretty quick, I'd probably suggest by now already, 10x is an absolutely massive productivity increase. That would essentially mean, all the software development my team did by November could have instead been finished by the end of January.

zkmon• 8 months ago

Building the software is only a small part of the overall cost. For any significant production deployment, the cost goes into change management and support.

Only a miniscule part of the work is green-field development. Everything else is managing a mess.

throwawayffffas• 8 months ago

That has not been my experience, vibe coded code is typically unworkable garbage. I use it as motivation.

I ask it to do something, if it works, I keep it without looking at it. If it doesn't I look, recoil in horror, delete and rewrite myself.

It takes more time but seems to work for me.

lanthissa• 8 months ago

i think theres a huge section of tasks which required you pay high salaries for which are gone.

just thinking from the finance world, in 2010 no knew how to program on the desk and no one knew sql, and even if they did the institutional knowledge to use the dev systems was not worth their time. So you had multiple layers of meetings and managers to communicate programs. As a result, anything small just didn't get done, and everything took time.

by 2020 most junior guys knew enough python to pick up some of the small stuff

in 2025 ai tools are good enough that they're picking up things that legit would have taken weeks to do in 2010 because of the processes around them not the difficulty and doing it in hours. A task that would take an hour to do used to take multiple meetings to properly outline to someone without finance knowledge and now they can do themselves in less time than it took to describe to a fresh cs grad.

Those tasks that junior traders/strats are able to do now that would have taken weeks or months to get into prod going through an it department i'm seeing cost drop 90% everyday right now. Which is good, it lets tech focus on tech and not learning the minutia of options trading in some random country

JanTurnherr• 8 months ago

a little anecdote: i used gemini cli for a large implementation of a feature for a cpp api. gemini did a huge amount of work i otherwise had to write by myself. problem? in all this great work was somewhere a memory bug hidden. there was no error you just feed to the cli and call it a day. after 4 days debugging i found the bug. needless to say, gemini did not even once came close to where the bug was in the guessing game... will this change in the future? we will see...

axismundi• 8 months ago

Maybe that 90% transferred into lots of low quality code caused by reckless vibe coding? That slop now sits there as kind of technical debt?

tangotaylor• 8 months ago

Engineers need to really lean in to the change in my opinion.

I tried leaning in. I really tried. I'm not a web developer or game developer (more robotics, embedded systems). I tried vibe coding web apps and games. They were pretty boring. I got frustrated that I couldn't change little things. I remember getting frustrated that my game character kept getting stuck on imaginary walls and kept asking Cursor to fix it and it just made more and more of a mess. I remember making a simple front-end + backend with a database app to analyze thousands of pull request comments and it got massively slow and I didn't know why. Cursor wasn't very helpful in fixing it. I felt dumber after the whole process.

The next time I made a web app I just taught myself Flask and some basic JS and I found myself moving way more quickly. Not in the initial development, but later on when I had to tweak things.

The AI helped me a ton with looking things up: documentation, error messages, etc. It's essentially a supercharged Google search and Stack Overflow replacement, but I did not find it useful letting it take the wheel.

r_lee3• 8 months ago

These posts like the one OP made is why I'm losing my mind.

Like, is there truly an agentic way to go 10x or is there some catch? At this point while I'm not thrilled about the idea of just "vibe coding" all the time, I'm fine with facing reality.

But I keep having the same experience as you, or rather leaning more on that supercharged Google/SO replacement

or just a "can you quickly make this boring func here that does xyz" "also add this" or for bash scripts etc.

And that's only when I've done most of the plumbing myself.

adam_patarino3• 8 months ago

I keep using this excel analogy. When excel came out everyone said accountants were dead. Now we have more accountants than ever.

The analogy carries to what you’re saying here. Accountants or folks who know excel deeply can get a lot more from it than folks who are novice to it.

AI coding can be really helpful for an engineer. Keep at it!

adriand6• 8 months ago

Like, is there truly an agentic way to go 10x or is there some catch?

Yes. I think it’s practice. I know this sounds ridiculous, but I feel like I have reached a kind of mind meld state with my AI tooling, specifically Claude Code. I am not really consciously aware of having learned anything related to these processes, but I have been all in on this since ChatGPT, and I honestly think my brain has been rewired in a way that I don’t truly perceive except in terms of the rate of software production.

There was a period of several months a while ago where I felt exhausted all the time. I was getting a lot done, but there was something about the experience that was incredibly draining. Now I am past that and I have gone to this new plateau of ridiculous productivity, and a kind of addictive joy in the work. A marvellous pleasure at the orchestration of complex tasks and seeing the results play out. It’s pure magic.

Yes, I know this sounds ridiculous and over-the-top. But I haven’t had this much fun writing software since my 20s.

lionkor• 8 months ago

I have a feeling that people who are genuinely impressed by long term vibe coding on a single project are only impressed because they don't know any better.

Take writing a book, or blog post; writing a good blog post, or a chapter of a book, takes lots of skill and practice. The results are very satisfying and usually add value to both the writer's life as well as the reader's. When someone who has done that uses AI and sees the slop it generates, he's not impressed, probably even frustrated.

However, someone who can barely write a couple coherent sentences, would be baffled at how well AIs can put together sentences, paragraphs, and have a somewhat coherent train of thought through the entire text. People who struggled in school with writing an introduction and a conclusion will be amazed at AIs writing. They would maybe even assume that "those paragraphs actually add no meaning and are purely fluff" is a totally normal part of writing and not an AI artifact.

bonzini2• 8 months ago

I did find some benefit in lowering the cost of exploratory work, but that's it—certainly worth 20€/month, but not the price of any of the "ultimate" plans.

For example today I had to write a simple state machine (for a parser that I was rewriting so I had all the testcases already). I asked Claude Code to write the state machine for me and stopped it before it tried compiling and testing.

Some of the code (of course including all the boilerplate) worked, some made no sense. It saved a few minutes and overall the code it produced was a decent first approximation, but waiting for it to "reason" through the fixes would have made no sense, at least to me. The time savings mostly came from avoiding the initial "type the boilerplate and make it compile" part.

When completing the refactoring there were a few other steps like where using AI was useful. But overall the LLM did maybe 10% of the work and saved optimistically 20-30 minutes over a morning.

Assuming I have similar savings once a week, which is again very optimistic... That's a 2% reduction or less.

itgoon2• 8 months ago

Like another reply says: practice.

How many hours have you spent writing code? Thousands? Tens of thousands? Were you able to achieve good results in the first hundred hours?

Now, compare it to how much time you've spent working with agents. Did you dedicate considerable time to figuring out how to use them? Do you stop using the agent and do things manually when it isn't going right, or do you spend time figuring out how to get the agent to do it?

groby_b• 8 months ago

You can go faster once you understand the domain reasonably well that you could have written it yourself. This allows you to write better designs, and steer LLMs in the right direction.

"Vibe coding" though is moving an ever growing pile of nonunderstanding and complexity in front of you, until you get stuck. (But it does work until you've amassed a big enough pile, so it's good for smaller tasks - and then suddenly extremely frustrating once you reach that threshold)

Can you go 10x? Depends. I haven't tried any really large project yet, but I can compress fairly large things that would've taken a week or two pre-LLM into a single lazy Sunday.

For larger projects, it's definitely useful for some tasks. ("Ingest the last 10k commits, tell me which ones are most likely to have broken this particular feature") - the trick is finding tasks where the win from the right answer is large, and the loss from the wrong one is small. It's more like running algorithmic trading on a decent edge than it is like coding :)

It definitely struggles to do successfully do fully agentic work on very large code bases. But... I've also not tried too much in that space yet, so take that with a grain of salt.

JeremyNT• 8 months ago

Like, is there truly an agentic way to go 10x or is there some catch? At this point while I'm not thrilled about the idea of just "vibe coding" all the time, I'm fine with facing reality.

Below is based on my experience using (currently) mostly GPT-5 with open source code assistants.

For a new project with straightforward functionality? I think you (and "you" being "basically anybody who can code at all") can probably manage to go 10x the pace of a junior engineer of yesteryear.

Things get a lot trickier when you have complex business logic to express and backwards compatibility to maintain in an existing codebase. Writing out these kinds of requirements in natural language is its own skillset (which can be developed), and this process takes time in and of itself.

The more confusing the requirements, the more error prone the process becomes though. The model can do things "correctly" but oops maybe you forgot something in your description, and now the whole thing will be wrong. And the fact that you didn't write the code means that you missed out on your opportunity to fix / think about stuff in the first pass of implementation (i.e. you need to seriously review stuff, which also slow you down).

Sometimes iterating over English instructions will take longer than just writing/expressing things in code from the start. But sometimes it will be a lot faster too.

Basically the easy stuff is way easier but the more complex stuff is still going to require a lot of hand holding and a lot of manual review.

coffeefirst• 8 months ago

That's my finding as well. The smaller the chunk, the better, and it saves me 5m here and an hour there. These really add up.

This is cool. It's extra cool on annoying things like "fix my types" or "find the syntax error" or "give me the flags for ffmpeg to do exactly this."

If I ever meet someone who drank the koolaid and wants to show me their process, I'm happy to see it. But I've tried enough to believe my own eyes, and when I see open source contributors I respect demo their methods, they spend enough time and energy either waiting on the machine and trying to keep it on the rails that, yes this is harder, but it does not appear to be faster.

KallDrexx4• 8 months ago

EVERY DX survey that comes out (surveying over 20k developers) says the exact same thing.

Staff engineers get the most time savings out of AI tools, and their weekly time savings is 4.4 hours for heavy AI users. That's a little more than 10% productivity, so not anywhere close to 10x.

What's more telling about the survey results is they are also consistent in their findings between heavy and light users of AI. Staff engineers who are heavy users of AI save 4.4 hours a week while staff engineers who are light users of AI save 3.3 hours a week. To put another way, the DX survey is pretty clear that the time savings between heavy and light AI users is minimal.

Yes surveys are all flawed in different ways but an N of 20k is nothing to sneeze at. Any study with data points shows that code generation is not a significant time savings and zero studies show significant time savings. All the productivity gains DX reports come from debugging and investigation/code base spelunking help.

digitalsushi• 8 months ago

does anyone remember that episode of star trek tng where the kid is given a little laser engraver that carves a dolphin from a block of wood? and the kid is like "i didn't make this" and the teacher (who abducted him, ew) is like "yeah but it's what you wanted to make, the tool just guided you"

so in 2026 we're going to get in trouble doing code "the old way", the pleasurable way, the way an artist connects with the work. we're not to chefs any longer, we're a plumber now that pours food from a faucet.

we're annoyed because our output can suddenly be measured by the time unit. the jig is up. our secret clubhouse has a lightbulb the landlord controls.

some of us were already doing good work, saving money, making the right decisions. we'll be fine.

some of us don't know how to do those things - or won't do those things - and our options are funneled down. we're trashing at this, like dogs being led to the pound.

there's before, there's during, and there's after; the during is a thing we so seldom experience, and we're in it, and 2024 felt like nothing, 2025 feels like the struggle, and 2026 will be the reconciliation.

change sucks. but it's how we continue. we continue differently or we dont exist.

jjice• 8 months ago

or just a "can you quickly make this boring func here that does xyz" "also add this" or for bash scripts etc.

I still write most of the interesting code myself, but when it comes to boring, tedious work (that's usually fairly repetitive, but can't be well abstracted any more), that's when I've found gen AI to be a huge win.

It's not 10x, because a lot of the time, I'm still writing code normally. For very specific, boring things (that also are usually my least favorite parts of code to write), it's fantastic and it really is a 10x. If you amortize that 10x over all the time, it's more like a 1.5x to 3x in my experience, but it saves my sanity.

Things like implementing very boring CRUD endpoints that have enough custom logic that I can't use a good abstraction and writing the associated tests.

I would dread doing work like that because it was just so mind numbing. Now, I've written a bunch of Cursor rules (that was actually pretty fun) so I can now drop in a Linear ticket description and have it get somewhere around 95% done all at once.

Now, if I'm writing something that is interesting, I probably want to work on it myself purely because it's fun, but also because the LLM may suck at it (although they're getting pretty damn good).

vbezhenar• 8 months ago

I tried claude code to write very simple app for me. Basically Golang mock server which will dump request to console. I'd write this kind of app in an hour. I spent around 1.5 hours with claude code and in the end I had code which I liked, almost the same code I'd write myself. It's not vibe coding, I carefully instructed it to write code in a way I prefer, one small step after another.

So for me, it's pretty obvious that with better training, I'd be able to achieve speed ups with the same result in the end. Not 10x, but 2x is possible. The very first attempt to use AI ended up with almost the same time I'd write the same code, and I have a lot to improve.

That said, I have huge problem with this approach. It's not fun to work like that. I started to program 25 years ago, because it was fun for me. It still fun for me today. I love writing all these loops and ifs. I can accept minimal automation like static autocomplete, but that's about it.

csomar• 8 months ago

I have been building a game (preview here: https://qpingpong.codeinput.com) as a practice to "vibe-coding". There is only one rule: I am not allowed to write a single line of code. But can prompt as much as I want.

So far I am hitting a "hard-block" on getting the AI to make changes once you have a large code base. One "unblocker" was to restructure all the elements as their own components. This makes it easier for the LLM (and you?) to reason about each component (React) in isolation.

Still, even as this "small/simple game" stage, it is not only hard for the LLM to get any change done but very easy for it to break things. The only way I can see my around it, is to structure very through tests (including E2E tests) so that any change by the LLM has to be thoroughly tested for regression.

I've been working on this for a month or so. I could have coded it faster by hand except for the design part.

Lich• 8 months ago

Feeling the same. I’m guessing the folks getting good results are literally writing extremely detailed pseudocode by hand?! Like:

Write a class Person who has members (int) age, (string) first name, (string) last name…

But if you can write that detailed…don’t you know the code you want to write and how you should write it? Writing plain pseudo code feels more verbose.

GoatInGrey• 8 months ago

It's been my experience that reaching for an LLM is a significant context switch that breaks flow state. Comparable to a monkey entering your office and banging cymbals together for a minute, returning to programming after writing up instructions for an LLM requires a refocusing process to reestablish the immersion you just forfeited. This can be a worthwhile trade with particularly tedious or annoying tasks, but not always.

I suspect that this explains the current bifurcation of LLM usage. Where individuals either use LLMs for everything or use them minimally. With the in-between space shrinking by the day.

estimator7292• 8 months ago

It seems to very heavily depend on your exact project and how well it's represented in the training set.

For instance, AI is great at react native bullshit that I can't be bothered with. It absolutely cannot handle embedded development. Particularly if you're not using Arduino framework on an Atmel 328. I'm presently doing bare metal AVR on a new chip and none of the AI agents have a single clue what they're doing. Even when fed with the datasheet and an entire codebase of manually written code for this thing, AI just produces hot wet garbage.

If you're on the 1% happy path AI is great. If you diverge even slightly from the top 10 most common languages and frameworks it's basically useless.

The weird thing is if you go in reverse it works great. I can feed bits of AVR assembly in and the AI can parse it perfectly. Not sure how that works, I suspect it's a fundamentally different type of transformation that these models are really good at

dent92• 7 months ago

Agentic AI is a pretty huge scam. Every organization worth it's salt has so many IAM protections in place that an AI developer is useless because you can't give it SSO and OIDC credentials to access the company resources. And no IT team will ever let it. So all these folks trying to convince us that AI will ever deploy anything useful are lying their butts off; IT won't even let their own developers deploy anything why would an AI be treated any differently?

hattmall2• 7 months ago

Like, is there truly an agentic way to go 10x

Yes, absolutely.

or is there some catch?

Yes, absolutely.

The catch is that to go 10x you have to either do a lot of work of the variety that AI excels at, mainly boilerplate and logical but tedious modifications. There's a lot of code I can write, but I will probably need to check the syntax and implementations for 10 or more functions / methods, but I know what they are and how I want the code to flow. AI never really nails it, but it gets close enough that I can fix it with considerable time savings. The major requirement here is that I, for the most part, already knew almost exactly what I wanted to do. This is the really fancy auto-complete that is actually a pretty reasonable assistant.

The other way is that you have to start from a position of 0.1x (or less) and go to !~1x.

There are a tremendous amount of people employed in tech roles, but outside of actual tech companies that have very very low throughput.

I've recently worked in a very large non-tech firm but one that is part of a major duopoly and is for the most part a household name worldwide. They employ 1000s of software developers whose primary function is to have a vague idea of who they should email about any question or change. The ratio of emails to lines of code is probably 25:1.

The idea that you could simply ask an AI to modify code, and it might do it correctly, in only a day is completely mind blowing to people whose primary development experience is from within one of these organizations.

godelski2• 7 months ago

  > for bash scripts etc

Everyone keeps telling me that it's good for bash scripts but I've never had real success.

Here's an example from today. I wanted to write a small script to grab my Google scholar citations and I'm terrible with web so I ask the best way to parse the curl output. First off, it suggests I use a python package (seriously? For one line of code? No thanks!) but then it gets the wrong grep. So I pull up the page source, copy paste some to it, and try to parse it myself. I already have a better grep command and for the second time it's telling me to use pearl regex (why does it love -P as much as it loves delve?). Then I'm pasting in my new command showing it my output asking for the awk and sed parts while googling the awk I always forget. It messes up the sed parts while googling, so I fix it, which means editing the awk part slightly but I already had the SO post open that I needed anyways. So I saved maybe one minutes total?

Then I give it a skeleton of a script file adding the variables I wanted and fully expected it to be a simple cleanup. No. It's definitely below average, I mean I've never seen an LLM produce bash functions without being explicitly told (not that the same isn't also true for the average person). But hey, it saved me the while loop for the args so that was nice. So it cost as much time as it gave back.

Don't get me wrong, I find LLMs useful but they're nowhere near game changing like everyone says they are. I'm maybe 10% more productive? But I'm not convinced that's even true. And sure, I might have been able to do less handholding with agents and having it build test cases but for a script that took 15 minutes to write? Feels like serious overkill. And this is my average experience with them.

Is everyone just saying it's so good at bash because no one is taking the time to learn bash? It's a really simple language that every Linux user should know the basics of...

sheepscreek• 8 months ago

The thing is, using an agent or AI to code for you is a learned skill. It doesn’t come naturally to most people. For you to be successful at it, you’ve got to adopt a mentor / lead mindset - directing vs doing. In other words, you have to be an expert at explaining yourself - communicating clearly to get great results.

Someone who hasn’t got any experience coding, or leading in any capacity, anywhere in life (or mentoring) will have a hard time with agentic development.

I’ll elaborate a bit more - the ideal mindset requires fighting that itch to “do it yourself” and sticking to the prompts for any changes. This habit will force you to get better at communicating effectively to others (including agents).

alemanek• 8 months ago

I don’t vibe code yet but it has sped me up a lot when working with large frameworks that have a lot of magic behind the scenes (Spring Boot). I am doing a very large refactor, major version spring boot upgrade, at the moment.

When given focused questions for parts of the code it it will give me 2-4 different approaches extending/implementing different bean overrides. I go through a cycle of back and forth having it give me sample implementations. I often ask what is considered the more modern or desirable approach. Things like give me a pros and cons list of the different approaches. The one I like the best I then go look up the specific docs to fact check a bit.

For this type of work it easily is a 2-3x. Spring specifically is really tough to search for due to its long history and large changes between major versions. More times than not it lands me on the most modern approach for my Spring Boot version and while the code it produces is not bad it isn’t great either. So, I rewrite it.

Also it does a pretty good job of writing integration tests. I have it give me the boilerplate for the test and then I can modify it for all my different scenarios. Then I run those against the unmodified and refactored code as validation suite that the refactor didn’t introduce issues.

When I am working in GoLang I don’t get this level of speed up but I also don’t need to look up as much. The number of ways to do things is far lower and there is no real magic behind the scenes. This might be one reason experiences may differ so radically.

jonfw3• 8 months ago

If you have not started working on a new codebase while adopting AI, it may be harder to realize the gains.

I switched jobs somewhat recently. At my previous job, where I was on the codebase for years, I knew where the changes should be and what they should look like. So I tried to jump directly to implementation with the AI because I didn't need much help planning and the AI got confused and did an awful job.

In a new codebase, where I had no idea how things are structured, I started the process by using AI to understand where the relevant code is, the call hierarchies and side effects, etc.

I have found by using the AI to conduct the initial investigation, it was then very easy to get the AI to generate an effective spec, and then it was relatively easy to get the AI to generate the code to that spec. That flow works much better than trying to one shot implementation

hackernewds• 8 months ago

You are discounting his experience with your own, while your example is not remotely relevant to his flask game example.

dominotw• 8 months ago

gp clearly said they use ai to lookup/explain stuff. they could do the same with local codebase.

not sure what you are trying to say.

xtracto• 8 months ago

How are you guys using LLMs? I've done a couple of applications for my own use, including a "Mexican Train Dominoes" online multiplayer using LLMs and it doesn't stop amazing me, Gemini 3 is crazy good at finding bugs at work, And every week there are very interesting advances in Arxiv articles.

I'm 45 years old, have been programming since I was 9, and this is the most amazing time to be building stuff.

xnx2• 8 months ago

Don't be put off forever by one bad experience with Cursor. Gemini 3 would likely yield much better results now.

jjav2• 7 months ago

IME vibe coding works spectacularly for simple one-off scripts that do a fairly simple thing. I can describe the work in ~10 minutes and save 2-4 hours of scripting.

Just last weekend I wanted a script to process a csv file and produce some reports and graphs out of that. I think it would've taken me the 2-4 hours to write it myself. Instead, I had cursor write it while waiting for boarding at the airport, probably no more than 10 minutes.

For codebases anything more complex than that, it starts to fall apart pretty quickly.

In that scenario it works ok only if I do all the work of designing the system and the functions and only let it type in the code for individual strictly-defined functions. So it does save some work which is nice, but it's not a huge win.

adam_patarino3• 7 months ago

Yeah, that matches my experience: LLMs are amazing “script interns” and shaky “systems engineers.” One trick that helps on bigger stuff: force it into a tight loop of (1) write a failing test for a single behavior, (2) implement smallest change, (3) run tests, (4) refactor. When you make the unit of work “one green test,” the model’s tendency to wander gets way less destructive.

andupotorac• 7 months ago

When they say skill issue, they mean it. Have you spent at least 4-5 hours on specs (mermaid, markdown)?

6r17• 8 months ago

We are in that era where most people don't know about software quality enough to have an influence that annihilates the hole market. This makes me think of the lemon market thing ; eg : if people are unable to know what product qualitative or bad - then everything collapses.

swiftcoder• 8 months ago

Previously, you'd have a small team of people working on setting up CI/CD... Nearly all of this can be done in a few hours with an agentic coding CLI

I've had a couple of contracts now, where I get to fix everything for teams who vibe-coded their infrastructure. I'm not saying it isn't a speed-up for teams who already have a wealth of infra experience - but it's not a substitute for the years of infra experience such a team already has.

ForHackernews• 8 months ago

Article mentions Jevons Paradox, but where is it? Where are all the thousands of new apps?

adam_patarino3• 8 months ago

I feel like people who write articles like this have never worked at big companies.

My wife works at Shutterstock, first as a SWE, now as a product manager. Most of their tasks involve small changes in 5 different systems. Sometimes in places like Salesforce. A simple ask can be profoundly complicated.

AI has certainly made grokking, and code changes easier. But the real cost of building has not been reduced 90%. Not even close.

enbugger• 8 months ago

The author "teaches workshops on AI development for engineering teams". This is nothing but a selling post for companies. I don't know what to discuss here honestly, this is more primitive bait than an average video preview picture on YouTube.

arduinomancer3• 8 months ago

These articles act like creating new demo apps or isolated tools is what software development is all about

kachapopopow• 8 months ago

honestly, my usage of AI is constantly evolving and sometimes I have days where I just don't use it at all, but it also allows me to do things I could never make myself do like realigning icons for 400+ models and also allows me to understand just enough of a subject to leave it behind and continue on my own.

AI has also probably saved me 100 hours of repetitive work at this point and completely elimitated the need to rely on other people working on time consuming configuration tasks and back-and-forward which used to stall work for me since I am the kind of person who will work for 20 hours until something is finished without losing that much in productivity.

jgeada• 8 months ago

Articles like this seem to keep highlighting a fundamental disconnect between what software teams really do vs what the people "managing" software teams a couple of layers above think those teams actually do.

The people up in the clouds think they have a full understanding of what the software is supposed to be, that they "own" the entire intent and specification in a few ambiguously worded requirements and some loose constraints and, being generous, a very incomplete understanding of the system dependencies. They see software teams as an expensive cost center, not as true the source of all their wealth and power.

The art of turning that into an actual software product is what good software teams do; I haven't yet seen anything that can automate that process away or even help all that much.

Volundr• 8 months ago

FTA

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool. This would take me, or many developers I know and respect, days to write by hand.

I have no problem believing that Claude generated 300 passing tests. I have a very hard time believing those tests were all well thought out, consise, actually testing the desired behavior while communicating to the next person or agent how the system under test is supposed to work. I'd give very good odds at least some of those tests are subtly testing themselves (ex mocking a function, calling said function, then asserting the mock was called). Many of them are probably also testing implementation details that were never intended to be part of the contract.

I'm not anti-AI, I use it regularly, but all of these articles about how crazy productive it is skip over the crazy amount of supervision it needs. Yes, it can spit out code fast, but unless your prepared to spend a significant chunk of that 'saved" time CAREFULLY (more carefully than with a human) reviewing code, you've accepted a big drop in quality.

kllrnohj• 8 months ago

Anecdotes etc etc but the AI tests I've been sent to review have been absolute shit. Stuff like that just calling a function doesn't crash the program. No assertions other than "end of test method reached"

Yes sometimes those tests are necessary, but it seemed to just do it everywhere because it made the code coverage percentage go up. Even though it was useless.

I have also had great experiences with AI cranking out straightforward boilerplate or asking C++ template metaprogramming questions. It's not all negative. But net-net it feels like it takes more work in total to use AI as you have to learn to recognize when it just won't handle the task, which can happen a lot. And you need to keep up with what it did enough to be able to take over. And reading code is harder than writing it.

piperswe• 8 months ago

I’ve seen agents produce plenty of those tests, but recently I’ve seen them generate some actually decent unit tests that I wouldn’t have thought of myself. It’s a bit of a crapshoot

rkozik1989• 8 months ago

The benefit of having a team of QA engineers create tests is their differing perspectives, so with LLMs being trained to act like affirmation engines you have to wonder how that impacts the test cases it creates. Its the problem of LLMs being miserable at critiques manifesting itself in a different way.

However, in saying that, I am by no means an AI hater, but rather I just want models to be better than they currently are. I am tired of the tech demos and benchmark stats that don't really mean much aside from impressing someone who's not in a critical thinking mindset.

jf226• 8 months ago

you've accepted a big drop in quality.

Right, but you do it in a 10th of the time.

WesleyJohnson3• 8 months ago

So you're openly saying you're fine with quantity over quality.... in software engineering? That's fine for a MVP, maybe, but nothing beyond on that IMHO unless they're throw away scripts.

"Houston, we have a problem."

"Yeah, but we did it in a 10th of the time"

bagacrap5• 8 months ago

I mean, just say you view unit testing as nothing more than a checkbox.

klysm• 8 months ago

Very similar experience here. I have not once managed to get an LLM to generate good tests, even for very simple code. It generally writes tautologies that will pass with high confidence.

stocksinsmocks4• 8 months ago

Which is the better value:

Hundreds of tests that were written basically for free in a few minutes even though a lot of them are kind of dumb?

Or hundreds of tests that were written for a five figure sum that took weeks or months, and only some of them are kind of dumb?

If you’re just thinking of code as the end in and of itself, then of course, the handcrafted artisanal product is better. If you think of code like an owner, an incidental expense towards solving a problem that has value, then cheap and disposable wins every time. We can throw our hands up about “quality“ and all that, but that baby was thrown out with the bathwater a very, very long time ago. The modern Web is slower than the older web. Desktop applications are just web browsers. Enterprise software barely works. Windows 11 happened. I don’t think anybody even bothers to scrutinize their dependency chains except for, I don’t know, like maybe missile guidance or something. And I just want to say Claude is not responsible for any of this. You humans are.

welshwelsh2• 8 months ago

Neither. Tests should be written by developers only when it saves them time. The cost of writing them should be negative.

Instead of writing hundreds of useless tests so that the code coverage report shows high numbers, it is better to write a couple dozen tests based on business needs and code complexity.

a_rana• 8 months ago

Hard disagree! Review is still an important part but more and more, I find myself agreeing with the LLM generated changes ~90% of the time.

insane_dreamer2• 7 months ago

Experience from 2 days ago:

I had CC write a bunch of tests to make sure some refactoring didn't break anything, and then I ran the app and it crashed out of the gate. Why? Because despite the verbosity of the tests it turns out that it had mocked the most import parts to test, so the _actual_ connections weren't being tested, and while CC was happy to claim victory with all tests green, the app was broken.

kreijstal• 7 months ago

so you do integration tests, if possible, however CC will claim victory even if test is red, or CC just deletes the failing tests

netdevphoenix• 8 months ago

Maybe not 90% but everyone can see the signs in the horizon.

The tale goes like this: one day visual arts got commoditised to the point any given visual artwork could be obtained for virtually free digitally. This has been the case for centuries. The aural arts (see records of spoken poetry, podcasts, music) have been commoditised for a long time. Full commodisation might never been happen (ie you can still work in the field) but it is undeniable that it has had a massive impact in their respective fields. Getting a Picasso-like painting might not be quite possible but we are getting quite there, same with music.

The same is coming for devs.

Devving is still far away but it doesn't really take that much to produce a significant impact in the field. The percentage of devs who can be able to get late 10s salaries will be gradually diminishing over time. This is what early stage commodisation looks like.

yakattak• 8 months ago

The agentic coding tools have got extremely good at converting business logic specifications into pretty well written APIs and services.

I haven’t experienced this at all. They can do okay with greenfield services (as the author mentioned). However it’s often not “extremely good”. It’s usually “passable” at best. It doesn’t save me any time either. I have to read and audit every line and change it anyway.

urxvtcd• 8 months ago

If AI is such a competitive advantage, why are AI companies even trying to sell it? Wouldn't it bring more money to use a bleeding edge internal model and just vibe a couple of facebooks at the fraction of the cost and profit like crazy?

bagacrap5• 8 months ago

It seems the people who think they can just tell computers to write code for them, also are the people who are inclined to tell other people to build apps for them.

We are hurdling towards a brave new world where only 10% of humans have to work, and the other 90% form the bureaucracy on top.

arduinomancer3• 8 months ago

Every time I see an article like this I ask the same question: show me the money?

If it’s so good why hasn’t it made you rich?

manishsharan• 8 months ago

Yes the cost of building software dropped by 90%.

However, the cost of software maintenance went up by 1000% . Lets hope you don't need to ever add a new business rule or user interface to your vibe coded software.

Ologn• 8 months ago

I am on the free tier of Gemini 3. With some intervention on my part, I got it to build, in Emacs Lisp, a primitive-recursive function for determining if a number is prime (by mu-recursive I mean a function built from the building blocks of a constant, successor and projection function, as well as a primitive recursive function and compositional function/macro). I was impressed, as previous models (including Anthropic and OpenAI) could not do this.

For the past few days I asked it to built a mu-recursive Ackermann function in Emacs Lisp (built on the primitive-recursive functions/operators, plus an extra operator - minimization). I said that the prime detector function it already built should be able to use the same functions/operators, and to rewrite code if necessary.

So far it has been unable to do this. If I thought it could but was stumbling over Emacs Lisp I might ask it to try in Scheme or Common Lisp or some other language. It's possible I'll get it to work in the time I have allotted from my daily free tier, but I have had no success so far. I am also starting with inputs to the Ackermann function of 0,0 - 0,1 - 1,0 - 1,1 to not overburden the system but it can't even handle 0, 0. Also it tries to redefine the Emacs Lisp keyword "and", which Emacs hiccups on.

A year ago LLMs were stumbling over Leetcode and Project Euler functions I was asking it to make. They seem to have gotten a little better, and I'm impressed Gemini 3 can handle, with help, primitive recursive functions in Emacs Lisp. Doesn't seem to be able to handle mu-recursive functions with minimization yet though. The trivial, toy implementations of these things. Also as I said, it tried to redefine "and" as well, which Emacs Lisp fell over on.

So it's a helpful helper and tool, but definitely not ready to hand things over to. As the saying goes, the first 90% of the code takes 90% of the time, and the last 10% of the code takes the other 90% of the time. Or the other saying - it's harder to find bugs than write code, so if you're coding at peak mental capacity, finding bugs becomes impossible. It does have its uses though, and has been getting better.

bagacrap5• 8 months ago

If the cost of building software had dropped 90%, the author wouldn't need to write a blog post. Just undercut the competition by 80% (they can keep 10% for themself).

newsoftheday4• 8 months ago

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool. This would take me, or many developers I know and respect, days to write by hand.

What was the value add of those tests, when I tried this, AI would often re-write the code to make match its poorly written test.

misja111• 8 months ago

I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool.

And what do you have then? 300 tests that test the behavior that's exposed by the implementations of the api. Are they useful? Probably some are, probably some are not. The ones that are not will just be clutter and maintenance overhead. Plus, there will be lots of use-cases for which you need to look a little deeper than just the api implementation, which are now not covered. And those kind of tests, tests that test real business use cases, are by far the most useful ones if you want to catch regressions.

So if your goal is to display some nice test coverage metrics on SonarQube or whatever, making your CTO happy, yes AI will help you enormously. But if your goal is to speed up development of useful test cases, less so. You will still gain from AI, but nowhere near 90%.

john61• 8 months ago

LLMs are calculating probable text/code. A lot of it in very short time. Probable text/code is not the same as correct/proper text/code. It is a huge mass of probable and maybe correct/proper text/code. That is very dangerous as it looks correct but maybe it is not. It is likely that the cost of software will increase because of the unmanageable mess that this creates.

insane_dreamer2• 7 months ago

This is a bit like saying RoR or Django dropped the cost of building web apps by 90% because you could write a blog app with 5 lines of code (IIRC early Rails claim).

So yes, the cost of certain tasks may drop by 90% (though I think that's a high number still), certainly the cost of developing software overall has not dropped by 90%.

I might be able to whip up a script in 30 seconds instead of 30 minutes, but I still have to think of whether I need the script, what exactly it should do, what am I trying to build and how and why, how does it fit with all the requirements, etc. That part isn't being reduced by 90%.

FarMcKon• 7 months ago

No.

Has the cost of building software dropped 90%?

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