Believe the Checkbook

https://robertgreiner.com/believe-the-checkbook/

by rg81 • 7 months ago

171 80 7 months ago

robertgreiner.com

hapless• 7 months ago

The ten dollar word for this is “revealed preferences”

recursive• 7 months ago

I learned that phrase from one of the bold sentences in this article.

conductr2• 7 months ago

People speak in relative terms and hear in absolutes. Engineers will never completely vanish, but it will certainly feel like it if labor demand is reduced enough.

Technically, there’s still a horse buggy whip market, an abacus market, and probably anything else you think technology consumed. It’s just a minuscule fraction of what it once was.

marcosdumay2• 7 months ago

but it will certainly feel like it if labor demand is reduced enough

All the last productivity multipliers in programming led to increased demand. Do you really think the market is saturated now? And what saturated it is one of the least impactful "revolutionary" tools we got in our profession?

Keep in mind that looking at statistics won't lead to any real answer, everything is manipulated beyond recognition right now.

conductr2• 7 months ago

Demand for software has been tied to demand for software engineering labor. That is no longer true. So demand for software may still go up while demand for labor goes another direction.

Also I do hold a belief that most tech companies are taking a cost/labor reduction strategy for a reason, and I think that’s because we’re closing a period of innovation. Keeping the lights on, or protecting their moats, requires less labor.

9rx• 7 months ago

Each of the last productivity multipliers coincided with greatly expanded markets (e.g. PC revolution, internet, mobile). Those are at the saturation point. And we've effectively built all the software those things need now. Of course there is still room for innovation in software, but it is not like in the past where we also had to build all the low-hanging fruit at the same time. That doesn't require nearly as many people — and that was already starting to become apparent before anyone knew what an LLM is.

This AI craze swooped in at the right time to help hold up the industry and is the only thing keeping it together right now. We're quickly trying to build all the low-hanging fruit for it, keeping many developers busy (although not like it used to be), but there isn't much low-hanging fruit to build. LLMs don't have the breadth of need like previous computing revolutions had. Once we've added chat interfaces to everything, which is far from being a Herculean task, all the low-hanging fruit will be gone. That's quite unlike previous revolutions where we had to build all the software from scratch, effectively, not just slap some lipstick on existing software.

If we want to begin to relive the past, we need a new hardware paradigm that needs all the software rewritten for it again. Not an impossible thought, but all the low-hanging hardware directions have also been picked at this point so the likelihood of that isn’t what it used to be either.

neilv• 7 months ago

Treat AI as force multiplication for your highest-judgment people. The ones who can design systems, navigate ambiguity, shape strategy, and smell risk before it hits. They’ll use AI to move faster, explore more options, and harden their decisions with better data.

Clever pitch. Don't alienate all the people who've hitched their wagons to AI, but push valuing highly-skilled ICs as an actionable leadership insight.

Incidentally, strategy and risk management sound like a pay grade bump may be due.

RandallBrown2• 7 months ago

The bottleneck isn’t code production, it is judgment.

It always surprises me that this isn't obvious to everyone. If AI wrote 100% of the code that I do at work, I wouldn't get any more work done because writing the code is usually the easy part.

add-sub-mul-div2• 7 months ago

I'll stare at a blank editor for an hour with three different solutions in my head that I could implement, and type nothing until a good enough one comes to mind that will save/avoid time and trouble down the road. That last solution is not best for any simple reason like algorithmic complexity or anything that can be scraped from web sites.

aaroninsf• 7 months ago

No shade on your skills, but for most problems, this is already false; the solutions have already been scraped.

All OSS has been ingested, and all the discussion in forum like this about it, and the personal blog posts and newsletters about it; and the bug tracking; and theh pull requests, and...

and training etc. is only going to get better and filtering out what is "best."

gowld• 7 months ago

I don't understand this thinking.

How many hours per week did you spend coding on your most recent project? If you could do something else during that time, and the code still got written, what would you do?

Or are you saying that you believe you can't get that code written without spending an equivalent amount of time describing your judgments?

scott_w• 7 months ago

I think OP is closer to the latter. How I typically have been using Copilot is as a faster autocomplete that I read and tweak before moving on. Too many years of struggling to describe a task to Siri left me deciding “I’ll just show it what I want” rather than tell.

kibwen• 7 months ago

"Writing code" is not the goal. The goal is to design a coherent logical system that achieves some goal. So the practice of programming is in thinking hard about what goal I want to achieve, then thinking about the sort of logical system that I could design that would allow me to verifiably achieve that goal, then actually banging out the code that implements the abstract logical system that I have in my head, then iterating to refine both the abstract system and its implementation. And as a result of being the one who produced the code, I have certainty that the code implements the system I have in mind, and that the system it represents is for for the purpose of achieving the original goals.

So reducing the part where I go from abstract system to concrete implementation only saves me time spent typing, while at the same time decoupling me from understanding whether the code actually implements the system I have in mind. To recover that coupling, I need to read the code and understand what it does, which is often slower than just typing it myself.

And to even express the system to the code generator in the first place still requires me to mentally bridge the gap between the goal and the system that will achieve that goal, so it doesn't save me any time there.

The exceptions are things where I literally don't care whether the outputs are actually correct, or they're things that I can rely on external tools to verify (e.g. generating conformance tests), or they're tiny boilerplate autocomplete snippets that aren't trying to do anything subtle or interesting.

RandallBrown2• 7 months ago

In my experience (and especially at my current job) bottlenecks are more often organizational than technical. I spend a lot of time waiting for others to make decisions before I can actually proceed with any work.

My judgement is built in to the time it takes me to code. I think I would be spending the same amount of time doing that while reviewing the AI code to make sure it isn't doing something silly (even if it does technically work.)

A friend of mine recently switched jobs from Amazon to a small AI startup where he uses AI heavily to write code. He says it's improved his productivity 5x, but I don't really think that's the AI. I think it's (mostly) the lack of bureaucracy in his small 2 or 3 person company.

I'm very dubious about claims that AI can improve productivity so much because that just hasn't been my experience. Maybe I'm just bad at using it.

jgeada• 7 months ago

All you did was changing the programming language from (say) Python to English. One is designed to be a programming language, with few ambiguities etc. The other is, well, English.

Speed of typing code is not all that different than the speed of typing English, even accounting for the volume expansion of English -> <favorite programming language>. And then, of course, there is the new extra cost of then reading and understanding whatever code the AI wrote.

layer8• 7 months ago

Or are you saying that you believe you can't get that code written without spending an equivalent amount of time describing your judgments?

It’s sort of the opposite: You don’t get to the proper judgement without playing through the possibilities in your mind, part of which is accomplished by spending time coding.

linhns• 7 months ago

Well you should be surprised by the number of people who do not know this. Klarna is probably the most popular example where the CEO was all about creating more code, then fired everyone before regretting

trollbridge• 7 months ago

Klarna, now there's a company that seems to have no idea what direction it's going in. In the past month, they've announced they're going to be at the forefront of Agentic AI for merchants so... agents can figure out what merchants are selling? They're somehow offering stablecoins to institutional investors to use USDC to extend loans to Klarna? And then they're starting some kind of credit-card rewards program with access to airline lounges?

skybrian• 7 months ago

I'm retired now, but I spent many hours writing and debugging code during my career. I believed that implementing features was what I was being paid to do. I was proud of fixing difficult bugs.

A shift to not writing code (which is apparently sometimes possible now) and managing AI agents instead is a pretty major industry change.

gopher_space• 7 months ago

Anything you do with AI is improved if you're able to traverse the stack. There's no situation where knowing how to code won't put you above peers who don't.

It's like how every job requires math if you make it far enough.

keyle• 7 months ago

As someone not close to retirement yet, it's a very sad shift.

xnx• 7 months ago

Lots of people have good judgement but don't know the arcane spells to cast to get a computer to do what they want.

phantasmish• 7 months ago

At my company doubling the writing-code part of software projects might speed them up 5%. I think even that’s optimistic.

Imperfectly fixing obvious problems in our processes could gain us 20%, easy.

Which one are we focusing on? AI. Duh.

Quothling• 7 months ago

I think it depends on the sort of work you do. We had some hubspot integration which hadn't been touched for three years break. Probably because someone at hubspot sunset their v1 api a few weeks too early... Our internal AI tool that I've build my own agents on updated our data transfer service to use the v3 api. It also added typing, but kept the rather insane way of delivering the data since... well... since it's worked fine for 3 years. It's still not a great piece of software that runs for us. It's better now than it was yesterday though and it'll now go back to just delivering business value in it's extremely imperfect form.

All I had to do was a two line prompt, and accept the pull request. It probably took 10 minutes out of my day, which was mostly the people I was helping explaining what they thought was wrong. I think it might've taken me all day if I had to go through all the code and the documentation and fixed it. It might have taken me a couple of days because I probably would've made it less insane.

For other tasks, like when I'm working on embedded software using AI would slow me down significantly. Except when the specifications are in German.

bibimsz• 7 months ago

I thought you were going to point how this phrase (and others) make it painfully obvious this article was written by AI.

saghm3• 7 months ago

Sometimes people who don't work in software seem surprised that I don't type faster than I do given my line of work, and I explain to them that typing speed is never the bottleneck in the work that I do. I don't pretend to know for sure if this holds true for every possible software job but it's not a concept I've seen surprise many software engineers. This almost seems like the next level of that; they certainly do more than just write code I want faster, but except for problems where I have trouble figuring out how to express what I want in code, they're not necessarily the solution to any problem I have.

If they could write exactly what I wanted but faster, I'd probably stop writing code any other way at all because that would just be a free win with no downside even though the win might be small! They don't write exactly what I want though, so the tradeoff is whether the amount of time they save me writing it is lost from the extra time debugging the code they wrote rather than my own. It's not clear to me that the code produced by an LLM right now is going to be close enough to correct enough of the time that this will be a net increase in efficiency for me. Most of the arguments I've seen for why I might want to consider investing more of my own time into learning these tools seem to be based on extrapolation of trends to up to this point, but it's still not clear to me that it's likely that they'll become good enough to reach a positive ROI for me any time soon. Maybe if the effort to actually start using them more heavily was lower I'd be willing to try it, but from what I can tell, it would take a decent amount of work for me to get the point where I'm even producing anything close to what I'm currently producing, and I don't really see the point of doing that if it's still an open question if it will ever close the remaining gap.

RealityVoid• 7 months ago

I explain to them that typing speed is never the bottleneck in the work that I do.

Never is a very strong word. I'm not a terribly fast typist but I intentionally trained to be faster because at times I wanted to whip out some stuff and the thought of typing it all out just annoyed me since it took too long. I think typing speed matters and saying it doesn't is a lie. At the very least if you have a faster baseline then typing stuff is more relaxing instead of just a chore.

jollyllama• 7 months ago

"Believe the checkbook? Why do that when I can get pump-faked into strip-mining my engineering org?"- VPs everywhere

zamadatix3• 7 months ago

Something about the way the article sets up the conversation nags at me a bit - even though it concludes with statements and reasoning I generally agree quite well with. It sets out what it wants to argue clearly at the start:

Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished... The Bun acquisition blows a hole in that story.”

But what the article actually discusses and demonstrates by the end of the article is how the aspects of engineering beyond writing the code is where the value in human engineers is at this point. To me that doesn't seem like an example of a revealed preference in this case. If you take it back to the first part of the original quote above it's just a different wording for AI being the code writer and engineering being different.

I think what the article really means to drive against is the claim/conclusion "because AI can generate lots of code we don't need any type of engineer" but that's just not what the quote they chose to set out against is saying. Without changing that claim the acquisition of Bun is not really a counterexample, Bun had just already changed the way they do engineering so the AI wrote the code and the engineers did the other things.

croes• 7 months ago

But the engineers can do it because they have written lots of code before. Where will these engineers get their experience in the future.

And what about vibe coding? The whole point and selling point of many AI companies is that you don’t need experience as a programmer.

So they sell something that isn’t true, it’s not FSD for coding but driving assistance.

zamadatix3• 7 months ago

These are all things I'd rather have seen the article set out to talk about as well, instead it opens up to disprove a statement saying AI can write the coding portion of the engineering problem by means of showing it being used that way with Bun to mean Anthropic must not actually think that.

imron• 7 months ago

Where will these engineers get their experience in the future

The house of the feeble minded: https://www.abelard.org/asimov.php

fwip2• 7 months ago

I mean, it smells an AI slop article, so it's hard to expect much coherence.

fwip2• 7 months ago

I guess y'all disagree?

The Bun acquisition blows a hole in that story.
That contradiction is not a PR mistake. It is a signal.
The bottleneck isn’t code production, it is judgment.
They didn’t buy a pile of code. They bought a track record of correct calls in a complex, fast-moving domain.
Leaders don’t express their true beliefs in blog posts or conference quotes. They express them in hiring plans, acquisition targets, and compensation bands.

Not to mention the gratuitous italics-within-bold usage.

zamadatix3• 7 months ago

I was thinking the same but it's like they only used AI to handle the editing or something because even throwing it into ChatGPT "how could this article be improved: ${article}" gives:

Tighten the causal claim: “AI writes code → therefore judgment is scarce”

As one of the first suggestions, so it's not something inherent to whether the article used AI in some way. Regardless, I care less about how the article got written and more about what conclusions really make sense.

drcode• 7 months ago

The bun acquisition is driven by current AI capabilities.

This argument requires us to believe that AI will just asymptote and not get materially better.

Five years from now, I don't think anyone will make these kinds of acquisitions anymore.

0x3f2• 7 months ago

This argument requires us to believe that AI will just asymptote and not get materially better.

That's not what asymptote means. Presumably what you mean is the curve levelling off, which it already is.

SoftTalker• 7 months ago

This seems overly pedantic. The intended meaning is clear.

bigstrat2003• 7 months ago

This argument requires us to believe that AI will just asymptote and not get materially better.

It hasn't gotten materially better in the last three years. Why would it do so in the next three or five years?

bitwize• 7 months ago

Deep learning and transformers have given step functions in AI's capabilities. It may not happen, but it's reasonable to expect another step-function development soon.

nitwit005• 7 months ago

An Anthropic engineer was getting some attention for saying six months: https://www.reddit.com/r/ClaudeAI/comments/1p771rb/anthropic...

I assume this is at least partially a response to that. They wouldn't buy a company now if it would actually happen that fast.

faxmeyourcode3• 7 months ago

While I agree with the premise of the article, even if it was a bit shallow, this claim made at the beginning is also still true:

Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished.”

Software engineering pre-LLMs will never, ever come back. Lots of folks are not understanding that. What we're doing at the end of 2025 looks so much different than what we were doing at the end of 2024. Engineering as we knew it a year or two ago will never return.

maccard2• 7 months ago

Does it?

I use AI as a smart auto complete - I’ve tried multiple tools on multiple models and I still _regularlt_ have it dump absolute nonsense into my editor - in thr best case it’s gone on a tangent, but in the most common case it’s assumed something (often times directly contradicting what I’ve asked it to do), gone with it, and lost the plot along the way. Of course when I correct it it says “you’re right, X doesn’t exist so we need to do X”…

Has it made me faster? Yes. Had it changed engineering - not even close. There’s absolutely no world where I would trust what I’ve seen out of these tools to run in the real world even with supervision.

geitir• 7 months ago

When you have that hair raising “am I crazy why are people touting ai” feeling, it’s good to look at their profile. Oftentimes they’re caught up in some ai play. Also it’s good to remember yc has heavy investment in gen ai so this site is heavily biased

faxmeyourcode3• 7 months ago

Unfortunately this is a skill issue. And it's a totally different skill than reading and writing code, building solid systems, and general software engineering at large. That is annoying, but where we're currently at.

Assume you're writing code manually, and you personally make a mistake. It's often worthwhile to create a mechanism that prevents that class of mistake from cropping up again. Adding better LSP or refactoring support to your editor, better syntax highlighting, better type checking, etc.

That same exact game of whack a mole now has to be done for you and whatever agent you're building with. Some questions to ask: What caused the hallucination? Did you have the agent lay out its plan before it writes any code? Ask you questions and iterate on a spec before implementation? Have you given it all of the necessary tools, test harnesses, and context it needs to complete a request that you've made to it? How do you automate this so that it's impossible for these pieces to be missing for the next request? Are you using the right model for the task at hand?

fooqux• 7 months ago

How do I know they didn't buy them just to make sure their competitors couldn't?

kubb• 7 months ago

Can anyone tell me the leading theory explaining the acquisition?

I can’t see how buying a runtime for the sake of Claude Code makes sense.

barfoure• 7 months ago

I disagree with this article and what it attempts to do: frame the acquisition using a conjecture. The only thing to “believe” are the authors reasons - which are flimsy, because they are the very thing we need to be critical of.

I don’t know why the acquisition happened, or what the plans are. But it did happen, and for this we don’t have to suspend disbelief. I don’t doubt Anthropic has plans that they would rather not divulge. This isn’t a big stretch of imagination, either.

We will see how things play out, but people are definitely being displaced by AI software doing work, and people are productive with them. I know I am. The user count of Claude Code, Gemini and ChatGPT don’t lie, so let’s not kid ourselves.

zmj• 7 months ago

Do people reading this post not understand that this is the output of a prompt like 'analyze <event> with <perspective> arriving at <conclusion>'? Tighten up your epistemology if you're arguing with an author who isn't there.

mk12• 7 months ago

This has been happening a lot recently, where an article immediately sets off all my AI alarm bells but most people seem to be happily engaging with it. I’m worried we’re headed for a dystopian future where all communication is outsourced to the slop machine. I hope instead there is a societal shift to better recognize it and stigmatize it.

integralid3• 7 months ago

instead there is a societal shift to better recognize it

Unlikely. AI keeps improving, and we are already at the point where real people are accused of being AI.

duskdozer• 7 months ago

I've noticed some of this in recent months. I've also noticed people editing out some of the popular tells, like replacing em-dashes with commas, or at least I think so, because of odd formatting/errors in places where it sounds like the LLM would have used a dash.

But at this point I'm not confident that I'm not failing to identify a lot of LLM-generated text and not making false positives.

placebo• 7 months ago

The very fact that people are arguing with a non-existent author signals that whatever generated the content did a good enough job to fool them today. Tomorrow it will do a good enough job to fool you. I think the more important question is what this means in terms of what is really important and what we should invest in to remain anchored in what matters.

verbify• 7 months ago

The article is full of snow clones that I see in AI writing. Or as the AI would put it "that's style *without* authorship".

The point is still valid, although I've seen it made many times over.

Believe the Checkbook

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