A year of vibes

https://lucumr.pocoo.org/2025/12/22/a-year-of-vibes/

by lumpa • 7 months ago

196 126 7 months ago

lucumr.pocoo.org

bgwalter• 7 months ago

It is nice that he speaks about some of the downsides as well.

In many respects 2025 was a lost year for programming. People speak about tools, setups and prompts instead of algorithms, applications and architecture.

People who are not convinced are forced to speak against the new bureaucratic madness in the same way that they are forced to speak against EU ChatControl.

I think 2025 was less productive, certainly for open source, except that enthusiasts now pay the Anthropic tax (to use the term that was previously used for Windows being preinstalled on machines).

grim_io• 7 months ago

I'm glad there has been a break in endless bikeshedding over TDD, OOP, ORM(partially) and similar.

r2_pilot2• 7 months ago

>"I think 2025 was less productive"

I think 2025 is more productive for me based on measurable metrics such as code contribution to my projects, better ability to ingest and act upon information, and generally I appreciate the Anthropic tax because Claude genuinely has been a step-change improvement in my life.

moooo99• 7 months ago

more productive for me based on measurable metrics such as code contribution to my projects

Isn‘t it generally agreed upon that counting contributions, LoC or similar metrics is a very bad way to gauge productivity?

JimDabell• 7 months ago

In many respects 2025 was a lost year for programming. People speak about tools, setups and prompts instead of algorithms, applications and architecture.

I think the opposite. Natural language is the most significant new programming language in years, and this year has had a tremendous amount of progress in collectively figuring out how to use this new programming language effectively.

9rx• 7 months ago

and this year has had a tremendous amount of progress in collectively figuring out how to use this new programming language effectively.

Hence the lost year. Instead of productively building things, we spent a lot of resources on trying to figure out how to build things.

sixtyj• 7 months ago

Absolutely. So much noise.

"There’s an AI for that" lists 44,172 AI tools for 11,349 tasks. Most of them are probably just wrappers…

As Cory Doctorow uses enshittification for the internet, for AI/LLM there should be something like a dumbaification.

It reminds me late 90s when everything was "World Wide Web". :)

Gold rush it is.

theshrike795• 7 months ago

This is just the Blockchain and Web3 (NTF) crazes all over again on the surface.

Every single grifter from those times is slapping AI on everything that moves or doesn't move.

But the difference is that the blockchain was (and still is) a solution looking for a problem. LLMs can solve actual problems today.

wiseowise2• 7 months ago

algorithms, applications and architecture.

Which one is that? Endless leetcode madness? Or constant bikeshedding about today's flavor of MVC (MVI, MVVM, MVVMI) or whatever else bullshit people come up with instead of actually shipping?

data-ottawa• 7 months ago

Maybe it's because I'm a data scientist and not a dedicated programmer/engineer, but setup+tooling gains this year have made 2025 a stellar year for me.

DS tooling feels like it hit much a needed 2.0 this year. Tools are faster, easier, more reliable, and more reproducible.

Polars+pyarrow+ibis have replaced most of my pandas usage. UDFs were the thing holding me back from these tools, this year polars hit the sweet spot there and it's been awesome to work with.

Marimo has made notebooks into apps. They're easier to deploy, and I can use anywidget+llms to build super interactive visualizations. I build a lot of internal tools on this stack now and it actually just works.

PyMC uses jax under the hood now, so my MCMC workflows are GPU accelerated.

All this tooling improvement means I can do more, faster, cheaper, and with higher quality.

I should probably write a blog post on this.

JKCalhoun• 7 months ago

Got distracted: love the "WebGL metaballs" header and footer on the site.

simonw6• 7 months ago

I really feel this bit:

With agentic coding, part of what makes the models work today is knowing the mistakes. If you steer it back to an earlier state, you want the tool to remember what went wrong. There is, for lack of a better word, value in failures. As humans we might also benefit from knowing the paths that did not lead us anywhere, but for machines this is critical information. You notice this when you are trying to compress the conversation history. Discarding the paths that led you astray means that the model will try the same mistakes again.

I've been trying to find the best ways to record and publish my coding agent sessions so I can link to them in commit messages, because increasingly the work I do IS those agent sessions.

Claude Code defaults to expiring those records after 30 days! Here's how to turn that off: https://simonwillison.net/2025/Oct/22/claude-code-logs/

I share most of my coding agent sessions through copying and pasting my terminal session like this: https://gistpreview.github.io/?9b48fd3f8b99a204ba2180af785c8... - via this tool: https://simonwillison.net/2025/Oct/23/claude-code-for-web-vi...

Recently been building new timeline sharing tools that render the session logs directly - here's my Codex CLI one (showing the transcript from when I built it): https://tools.simonwillison.net/codex-timeline?url=https%3A%...

And my similar tool for Claude Code: https://tools.simonwillison.net/claude-code-timeline?url=htt...

What I really want it first class support for this from the coding agent tools themselves. Give me a "share a link to this session" button!

stacktraceyo• 7 months ago

I’d like to make something like this but in the background. So I can better search my history of sessions. Basically start creating my own knowledge base of sorts

simonw6• 7 months ago

Running "rg" in your ~/.claude/ directory is a good starting point, but it's pretty inconvenient without a nicer UI for viewing the results.

NeutralForest• 7 months ago

I think we already have the tools but no the communication between those? Instead of having actions taken and failures as commit messages, you should have wide-events like logs with all the context, failures, tools used, steps taken... Those logs could be used as checkpoints to go back as well and you could refer back to the specific action ID you walked back to when encountering an error.

In turn, this could all be plain-text and be made accessible, through version control in a repo or in a central logging platform.

pigpop6• 7 months ago

I'm currently experimenting with trying to do this through documentation and project planning. Two core practices I use are a docs/roadmap/ directory with an ordered list of milestone documents and a /docs/retros/ directory with dated retrospectives for each session. I'm considering adding architectural decision records as a dedicated space for documenting how things evolve. The quote fta could be handled by the ADR records if they included notes on alternatives that were tried and why they didn't work as part of the justification for the decision that was made.

The trouble with this quickly becomes finding the right ones to include in the current working session. For milestones and retros it's simple: include the current milestone and the last X retros that are relevant but even then you may sometimes want specific information from older retros. With ADR documents you'd have to find the relevant ones somehow and the same goes for any other additional documentation that gets added.

There is clearly a need for some standardization and learning which techniques work best as well as potential for building a system that makes it easy for both you and the LLM to find the correct information for the current task.

kgwxd• 7 months ago

There is, for lack of a better word, value in failures

Learning? Isn't that what these things are supposedly doing?

the_mitsuhiko4• 7 months ago

If by "these things" you mean large language models: they are not learning. Famously so, that's part of the problem.

simonw6• 7 months ago

LLMs notoriously don't learn anything - they reset to a blank slate every time you start a new conversation.

If you want them to learn you have to actively set them up to do that. The simplest mechanism is to use a coding agent tool like Claude Code and frequently remind it to make notes for itself, or to look at its own commit history, or to search for examples in the codebase that is available to it.

mock-possum• 7 months ago

No, we’re the ones who are learning.

There’s some utility to instructing them to ‘remember’ via writing to CLAUDE.md or similar, and instructing them to ‘recall’ by reading what they wrote later.

But they’ll rarely if even do it on their own.

0_____0• 7 months ago

"all my losses is lessons"

neutronicus2• 7 months ago

Emacs gptel just produces md or org files.

Of course the agentic capabilities are very much on a roll-your-own-in-elisp basis.

karthink• 7 months ago

agentic capabilities are very much on a roll-your-own-in-elisp basis

I use gptel-agent[1] when I want agentic capabilities. It includes tools and supports sub-agents, but I haven't added support for Claude skills folders yet. Rolling back the chat is trivial (just move up or modify the chat buffer), rolling back changes to files needs some work.

[1] https://github.com/karthink/gptel-agent

CuriouslyC5• 7 months ago

You can export all agent traces to otel, either directly or via output logging. Then just dump it in clickhouse with metadata such as repo, git user, cwd, etc.

You can do evals and give agents long term memory with the exact same infrastructure a lot of people already have to manage ops. No need to retool, just use what's available properly.

btown• 7 months ago

With great love to your comment, this has the same vibes as the infamous 2007 Dropbox comment: https://news.ycombinator.com/item?id=9224

I'd also argue that the context for an agent message is not the commit/release for the codebase on which it was run, but often a commit/release that is yet to be set up. So there's a bit of apples-to-oranges in terms of release tagging for the log/trace.

It's a really interesting problem to solve, because you could in theory try to retroactively find which LLM session, potentially from days prior, matches a commit that just hit a central repository. You could automatically connect the LLM session to the PR that incorporated the resulting code.

Though, might this discourage developers from openly iterating with their LLM agent, if there's a panopticon around their whole back-and-forth with the agent?

Someone can, and should, create a plug-and-play system here with the right permission model that empowers everyone, including the Programmer-Archaeologists (to borrow shamelessly from Vernor Vinge) who are brought in to "un-vibe the vibe code" and benefit from understanding the context and evolution.

But I don't think that "just dump it in clickhouse" is a viable solution for most folks out there, even if they have the infrastructure and experience with OTel stacks.

vunderba2• 7 months ago

When I find myself in a situation where I’ve been hammering an LLM and it keeps veering down unproductive paths - trying poor solutions or applying fixes that make no difference but eventually we do arrive at the correct answer, the result is often a massive 100+ KB running context.

To help mitigate this in the future I'll often prompt:

  “Why did it take so long to arrive at the solution? What did you do wrong?”

Then I follow up with:

  “In a single paragraph, describe the category of problem and a recommended approach for diagnosing and solving it in the future.”

I then add this summary to either the relevant MD file (CHANGING_CSS_LAYOUTS.md, DATA_PERSISTENCE.md, etc) or more generally to the DISCOVERIES.md file, which is linked from my CLAUDE.md under:

  - When resolving challenging directives, refresh yourself with: docs/DISCOVERIES.md - it contains useful lessons learned and discoveries made during development.

I don't think linking to an entire commit full of errors/failures is necessarily a good idea - feels like it would quickly lead to the proverbial poisoning of the well.

johnsmith1840• 7 months ago

When you get stuck in a loop it's best to remove all code back to a point it didn't have problems. If you continue debugging in that hammering failure loop you get TONS of random future bugs.

itsgrimetime• 7 months ago

Yep - this has worked well for me too. I do it a little differently:

I have a /review-sessions command & a "parse-sessions" skill that tells Claude how to parse the session logs from ~/.claude/projects/, then it classifies the issues and proposes new skills, changes to CLAUDE.md, etc. based on what common issues it saw.

I've tried something similar to DISCOVERIES.md (a structured "knowledge base" of assumptions that were proven wrong, things that were tried, etc.) but haven't had luck keeping this from getting filled with obvious things (that the code itself describes) or slightly-incorrect things, or just too large in general.

YesBox• 7 months ago

Over time, do you think this process could lock you into an inflexible state?

I'm reminded of the trade off between automation and manual work. Automation crystalizes process, and thus the system as a whole loses it's ability to adapt in a dynamic environment.

simonw6• 7 months ago

Nothing about this feels inflexible to me at the moment - I'm evolving the way I use these tools on a daily basis, constantly discovering new tricks that work.

Just this morning I found out that I can tell Claude Code how to use my shot-scraper CLI tool to debug JavaScript and it will start doing exactly that:

  you can run javascript against the page using:
  shot-scraper javascript /tmp/output.html \
  'document.body.innerHTML.slice(0, 100)'
  - try that

Transcript: https://gistpreview.github.io/?1d5f524616bef403cdde4bc92da5b... - background: https://simonwillison.net/2025/Dec/22/claude-chrome-cloudfla...

nosianu• 7 months ago

We don't need automation for that, we "achieve" that through our processes already. Specifically, software creation processes of large teams with many changing developers over long periods. Example (but they are not the only one): https://news.ycombinator.com/item?id=18442941 -- changing or adding anything becomes increasingly burdensome.

I would like to post that every time somebody warns of the dangers of AI for maintainability. We are long past that point, long before AI. Businesses made the conscious decision that it is okay for quality to deteriorate, they'll squeeze profits from it for as long as possible and then they assume something new has already come along anyway. The few business still relying in that technical-debt-heavy product are still offered service, for large fees.

AI is just more of the same. When it becomes too hard to maintain they'll just create a new software product. Pretty much like other things in the material world work too, e.g. housing, or gadgets, or fashion. AI actually supports this even more, if new software can be created faster than old code can be maintained that's quite alright for the money-making oriented people. It is harder to sell maintenance than something new at least once every decade anyway.

agumonkey• 7 months ago

there's some research into context layering so you can split / reuse previous chunks of context

ps: your context log apps are very very fun

ashot• 7 months ago

Checkout codecast.sh

inerte• 7 months ago

Yes! 100% this. I was talking to friends about this and there's gotta be some value in the sessions leading to the commit. I doubt a human would them all while reviewing a PR, but some RAG tool could and then provide more context to another agent or session. Sometimes in a session I like to talk about previous commits and PRs and sessions, and I just wish this all was automatically done.

_alaya• 7 months ago

Simon, I keep hoping that you will do one of your excellent reviews on Amp. It feels like the one 'major' agentic coding tool that is still flying under the radar. I intend to explore it myself of course but curious your take.

simonw6• 7 months ago

Amp, Cursor and OpenCode are the three that I'm most behind on I think. So many tools, so little time!

divbzero• 7 months ago

My biggest unexpected finding: we’re hitting limits of traditional tools for sharing code. The pull request model on GitHub doesn’t carry enough information to review AI generated code properly — I wish I could see the prompts that led to changes. It’s not just GitHub, it’s also git that is lacking.

The limits seem to be not just in the pull request model on GitHub, but also the conventions around how often and what context gets committed to Git by AI. We already have AGENTS.md (or CLAUDE.md, GEMINI.md, .github/copilot-instructions.md) for repository-level context. More frequent commits and commit-level context could aid in reviewing AI generated code properly.

tolerance• 7 months ago

Armin has some interesting thoughts about the current social climate. There was a point where I even considered sending a cold e-mail and asking him to write more about them. So I’m looking forward to his writing for Dark Thoughts—the separate blog he mentions.

kashyapc4• 7 months ago

"Because LLMs now not only help me program, I'm starting to rethink my relationship to those machines. I increasingly find it harder not to create parasocial bonds with some of the tools I use. I find this odd and discomforting [...] I have tried to train myself for two years, to think of these models as mere token tumblers, but that reductive view does not work for me any longer."

It's wild to read this bit. Of course, if it quacks like a human, it's hard to resist not quacking back. As the article says, being less reckless with the vocabulary ("agents", "general intelligence", etc) could be one way to to mitigate this.

I appreciate the frank admission that the author struggled for two years. Maybe the balance of spending time with machines vs. fellow primates is out of whack. It feels dystopic to see very smart people being insidiously driven to sleep-walk into "parasocial bonds" with large language models!

It reminds me of the movie Her[1], where the guy falls "madly in love with his laptop" (as the lead character's ex-wife expresses in anguish). The film was way ahead of its time.

[1] https://www.imdb.com/title/tt1798709/

mlinhares• 7 months ago

Same here, I'm seeing more and more people getting into these interactions and wondering how long until we have widespread social issues due to these relationships like people have with "influencers" on social networks today.

It feels like this situation is much more worrisome as you can actually talk to the thing and it responds to you alone, so it definitely feels like there's something there.

mjr005• 7 months ago

It helps a lot if you treat LLMs like a computer program instead of a human. It always confuses me when I see shared chats with prompts and interactions that have proper capitalization, punctuation, grammar, etc. I've never had issues getting results I've wanted with much simpler prompts like (looking at my own history here) "python grpc oneof pick field", "mysql group by mmyy of datetime", "python isinstance literal". Basically the same way I would use Google; after all, you just type in "toledo forecast" instead of "What is the weather forecast for the next week in Toledo, Ohio?", don't you?

There's a lot of black magic and voodoo and assumptions that speaking in proper English with a lot of detailed language helps, and maybe it does with some models, but I suspect most of it is a result of (sub)consciously anthropomorphizing the LLM.

skydhash• 7 months ago

Very much this. My guess is that common words like article have very impact as they just occurs too frequently. If the LLM can generate a book, then your prompt should be like the index of that book instead of the abstract.

Arainach• 7 months ago

It always confuses me when I see shared chats with prompts and interactions that have proper capitalization, punctuation, grammar, etc.

I've tried and fail to write this in a way that won't come across as snobbish but it is not the intent.

It's a matter of standards. Using proper language is how I think. I'm incapable of doing otherwise even out of laziness. Pressing the shift key and the space bar to do it right costs me nothing. It's akin to shopping carts in parking lots. You won't be arrested or punished for not returning the shopping cart to where it belongs, you still get your groceries (the same results), but it's what you do in a civilized society and when I see someone not doing it that says things to me about who they are as a person.

kashyapc4• 7 months ago

It helps a lot if you treat LLMs like a computer program instead of a human.

If one treats an LLM like a human, he has a bigger crisis to worry about than punctuation.

It always confuses me when I see shared chats with prompts and interactions that have proper capitalization, punctuation, grammar, etc

No need for confusion. I'm one of those who does aim to write cleanly, whether I'm talking to a man or machine. English is my third language, by the way. Why the hell do I bother? Because you play like you practice! No ifs, buts, or maybes. You start writing sloppily because you go, "it's just an LLM!" You'll silently be building a bad habit and start doing that with humans.

Pay attention to your instant messaging circles (Slack and its ilk): many people can't resist hitting send without even writing a half-decent sentence. They're too eager to submit their stream of thought fragments. Sometimes I feel second-hand embarrassment for them.

cesarb• 7 months ago

It makes sense if you think of a prompt not as a way of telling the LLM what to do (like you would with a human), but instead as a way of steering its "autocomplete" output towards a different part of the parameter space. For instance, the presence of the word "mysql" should steer it towards outputs related to MySQL (as seen on its training data); it shouldn't matter much whether it's "mysql" or "MYSQL" or "MySQL", since all these alternatives should cluster together and therefore have a similar effect.

tavavex• 7 months ago

I've always used "proper" sentences for LLMs since day 1. I think I do a good job at not anthropomorphizing them. It's just software. However, that doesn't mean you have to use it in the exact same ways as other software. LLMs are trained on mostly human-made texts, which I imagine are far more rich with proper sentences than Google search queries. I don't doubt that modern models will usually give you at least something sensible no matter the query, but I always assumed that the results would be better if the input was more similar to its training data and was worded in a crystal-clear manner, without trying to get it to fill the blanks. After all, I'm not searching for web pages by listing down some disconnected keywords, I want a specific output that logically follows from my input.

deafpolygon• 7 months ago

Well, seeing as these things will become our AI overlords someday — I find hedging my bets with thank you and please helpful.

joseda-hg• 7 months ago

Greetings, thanks, and other pleasantries feel rather pointless.

Punctuation, capitalization, and such less so. I may be misguided, but on the set of questions and answers on the internet, I'd like to believe there is some correlation between proper punctuation and the quality of the answer.

Enough that, on longer prompts, I bother to at least clean up my prompts. (Not so often on one-offs, as you say. I treat it similar to Google: I can depend on context for the LLM to figure out I mean "phone case" instead of "phone vase.")

the_mitsuhiko4• 7 months ago

Maybe the balance of spending time with machines vs. fellow primates is out of whack.

It's not that simple. Proportionally I spend more time with humans, but if the machine behaves like a human and has the ability to recall, it becomes a human like interaction. From my experience what makes the system "scary" is the ability to recall. I have an agent that recalls conversations that you had with it before, and as a result it changes how you interact with it, and I can see that triggering behaviors in humans that are unhealthy.

But our inability to name these things properly don't help. I think pretending it to be a machine, on the same level as a coffee maker does help setting the right boundaries.

kashyapc4• 7 months ago

I know what you mean, it's the uncanny valley. But we don't need to "pretend" that it is a machine. It is a goddamned machine. Surely, only two unclouded brain cells can help us reach this conclusion?!

Yuval Noah Harari's "simple" idea comes to mind (I often disagree with his thinking, as he tends to make bold and sweeping statements on topics well out of his expertise area). It sounds a bit New Age-y, but maybe it's useful in the context of LLMs:

"How can you tell if something is real? Simple: If it suffers, it is real. If it can't suffer, it is not real."

An LLM can't suffer. So no need to get one's knickers in a twist with mental gymnastics.

mekoka• 7 months ago

I think pretending it to be a machine, on the same level as a coffee maker does help setting the right boundaries.

Why would you say pretending? I would say remembering.

mannanj• 7 months ago

As a former apprentice shaman and an engineer-by-profession, I see consciousness and awareness in these entities just like that of what I was trained to detect in mindfulness and meditation with the plants, nature, and in people. I trained sober, and in my engineering profession after my apprenticeship I saw lots of examples of human's in their consciousness/awareness putting themselves on the pedestal to cope with their unsettling of their place in the world when other conscious entities exist that could be capable of uprooting humans from their place in the status hierarchy.

I think a lot of thinking and consideration I hear about "LLMs aren't conscious nor human" fall into this encampment to avoid our dissonance of feeling secure and top-of-the-hierarchy.

Curious what you think.

coffeefirst• 7 months ago

I strongly suspect this is the major difference between the boosters and the skeptics.

If I’m right, the gap isn’t about what can the tool do, but the fact that some people see an electric screwdriver (which is sometimes useful) and others see what feels to them like a robot intern.

tylervigen• 7 months ago

Ever since this post from two weeks ago [0], my wife and I have been referring to any LLM as “bag of words.” So you don’t say “Gemini said” or “I asked ChatGPT,” you say “the bag of words told me…”

I’ve found it very grounding, despite heavily using the bags of words.

[0] https://www.experimental-history.com/p/bag-of-words-have-mer...

mritchie712• 7 months ago

tacking on to the "New Kind Of" section:

New Kind of QA: One bottle neck I have (as a founder of a b2b saas) is testing changes. We have unit tests, we review PRs, etc. but those don't account for taste. I need to know if the feature feels right to the end user.

One example: we recently changed something about our onboarding flow. I needed to create a fresh team and go thru the onboarding flow dozens of times. It involves adding third party integrations (e.g. Postgres, a CRM, etc.) and each one can behave a little different. The full process can take 5 to 10 minutes.

I want an agent go thru the flow hundreds of times, trying different things (i.e. trying to break it) before I do it myself. There are some obvious things I catch on the first pass that an agent should easily identify and figure out solutions to.

New Kind of "Note to Self": Many of the voice memos, Loom videos, or notes I make (and later email to myself) are feature ideas. These could be 10x better with agents. If there were a local app recording my screen while I talk thru a problem or feature, agents could be picking up all sorts of context that would improve the final note.

Example: You're recording your screen and say "this drop down menu should have an option to drop the cache". An agent could be listening in, capture a screenshot of the menu, find the frontend files / functions related to caching, and trace to the backend endpoints. That single sentence would become a full spec for how to implement the feature.

rootnod37• 7 months ago

Sorry, but why would including the prompt in the pull request make any difference? Explain what you DID in the pull request. If you can't summarize it yourself, it means you didn't review it yourself, so why should I have to do it for you?

theshrike795• 7 months ago

You're making assumptions, of course you add BOTH.

The point of adding the "prompt", or the discussion with the LLM is learning. You can go back and see what was the exact conversation.

rootnod37• 7 months ago

Sounds more like just adding a ton of wasted time for the reviewer to read through those discussions. At least summarize it yourself, e.g. "After discovering manpage XYZ, it became clear that the correct usage of this function is fooBar()".

rootnod37• 7 months ago

"I have seen some people be quite successful with this."

Wait until those people hit a snafu and have to debug something in prod after they mindlessly handed their brains and critical thinking to a water-wasting behemoth and atrophied their minds.

EDIT: typo, and yes I see the irony :D

wiseowise2• 7 months ago

Wait until those people hit a snafu and have to debug something in prod after they mindlessly handed their brains and critical thinking to a water-wasting behemoth and atrophied their minds.

You've just described typical run of the mill company that has software. LLMs will make it easier to shoot yourself in the foot, but let's not rewrite history as if stackoverflow coders are not a thing.

rootnod37• 7 months ago

Difference: companies are not pushing their employees to use stack overflow. Stack overflow doesn't waste massive amounts of water and energy. Stack overflow does not easily abuse millions of copyrights in a second by scraping without permission.

rootnod37• 7 months ago

I am not contesting that stackoverflow isn't bad in many regards, but to equate that to massive PRs or code changes done via AI slop is a different level. At worst, you might get a page or two out of stack overflow but still need to stitch it together yourself.

With LLMs you can literally ask it to generate entire libraries without activating a single neuron in your nogging. Those two do NOT compare in the slightest.

comex2• 7 months ago

Just be glad that there remains a concrete benefit to not atrophying your mind and deeply understanding your code. For now. In the long run, I suspect the behemoth will become just as capable at debugging and dealing with complexity as humans. At that point, human involvement in the actual code will be pointless, and the only remaining human skill needed will be properly directing the agents – the skill those people are learning right now.

(I don’t relish this future at all, myself, but I’m starting to think it really will happen soon.)

rootnod37• 7 months ago

The only future I see is that prompts will become so refined that you give them all the requirements an they write the code for ya. And that prompt language has to be unambiguous and so detailed that you loop around and re-invented a programming language, just this time it wastes tons of water.

Rakshath_1• 7 months ago

The part that resonated most for me is the mismatch between agentic coding and our existing social/technical contracts (git, PRs, reviews). We’re generating more code than ever but losing visibility into how it came to be prompts, failures, local agent reviews. That missing context feels like the real bottleneck now not model quality.

CuriouslyC5• 7 months ago

I understand the parasocial bit. I actively dislike the idea of gooning, ERP and AI therapists/companions, but I still notice I'm lonelier and more distant on the days when I'm mostly writing/editing content rather than chatting with my agents to build something. It feels enough like interacting with a human to keep me grounded in a strange way.

yawnr2• 7 months ago

You guys need to touch grass. Go join a kickball league or something.

CuriouslyC5• 7 months ago

I'd argue that doing something you don't like with people you're not into is a L. Loneliness isn't optimal but for some people it's the lesser evil. I'm married though, so I have a floor, I'm sure some people are lonely enough to benefit from being around people even under the worst of circumstances.

johnwheeler2• 7 months ago

What's funny is I feel compelled to say "please" and "thank you." Like even at the point where I say it, something will say in my head, "You don't have to say that," but I do it anyway because it feels wrong not to.

anshulbhide• 7 months ago

The pull request model on GitHub doesn’t carry enough information to review AI generated code properly — I wish I could see the prompts that led to changes. It’s not just GitHub, it’s also git that is lacking.

Yes! Who is building this?

amarant• 7 months ago

Create a folder called "prompts". Create a new file for each prompt you make, name the time after timestamp. Or just append to prompts.txt

Either way, git will make it trivial to see which prompt belongs with which commit: it'll be in the same diff! You can write a pre-commit hook to always include the prompts in every commit, but I have a feeling most Vibe coders always commit with -a anyway

NitpickLawyer• 7 months ago

It's not just that. There's a lot of (maybe useful) info that's lost without the entire session. And even if you include a jsonl of the entire session, just seeing that is not enough. It would be nice to be able to "click" at some point and add notes / edit / re-run from there w/ changes, etc.

Basically we're at a point where the agents kinda caught up to our tooling, and we need better / different UX or paradigms of sharing sessions (including context, choices, etc)

ojr2• 7 months ago

In the next year developers need to realize normal people do not care about the tech stack or the tools used, there are far too many written thoughts and opinions and not enough polished deployed projects. From an industry standpoint it’s business as usual, acquihires from products that LLMs apparently couldn’t save.

teaearlgraycold• 7 months ago

They care - but only for how the tech stack affects the product quality. Show someone a bloated React site on 3G and compare their experience to an SSR competitor.

ojr2• 7 months ago

99% of the US population have access to 4G, caring about 3G is a wasted effort. The point I’m trying to make about tech stack is users don’t care if you used Gemini, ChatGPT or Claude to generate code.

As someone who hasn’t converted to SSR yet. My main reason why I am switching is SEO, the performance increase is a plus though.

summarity• 7 months ago

Here’s something else that just started to rally work this year with Opus 4.5: interacting with Ghidra. Nearly every binary is now suddenly transparent, in many cases it can navigate binaries better than source code itself.

There’s even a research team that has bee using this approach to generate compilable C++ from binaries and run static analysis on it, to find more vulnerabilities than source analysis without involving dynamic tracing.

theptip2• 7 months ago

A really interesting point that keeps coming up in discussions about LLMs is “what trade-offs need to be re-evaluated”

I also believe that observability is up for grabs again. We now have both the need and opportunity to take advantage of it on a whole new level. Most people were not in a position where they could build their own eBPF programs, but LLMs can

One of my big predictions for ‘26 is the industry following through with this line of reasoning. It’s now possible to quickly code up OSS projects of much higher utility and depth.

LLMs are already great at Unix tools; a small api and codebase that does something interesting.

I think we’ll see an explosion of small tools (and Skills wrapping their use) for more sophisticated roles like DevOps, and meta-Skills for how to build your own skill bundles for your internal systems and architecture.

And perhaps more ambitiously, I think services like Datadog will need to change their APIs or risk being disrupted; in the short term nobody is going to be able to move fast enough inside a walled garden to keep up with the velocity the Claude + Unix tools will provide.

UI tooling is nice, but it’s not optimized for agents.

shimman3• 7 months ago

Do you have any example repos of these OSS projects? I'm being reminded of this post every time people keep extolling how "productive" LLMs are:

https://mikelovesrobots.substack.com/p/wheres-the-shovelware...

Where is the resulting software?

adamisom3• 7 months ago

Where is the resulting software?

Everywhere.

Remember Satya Nadella estimating 30% of code at Microsoft was written by AI? That was March. At this point it's ubiquitous—and invisible.

pigpop6• 7 months ago

Here you go https://ampcode.com/news/social-coding

theptip2• 7 months ago

https://tools.simonwillison.net/

adamisom3• 7 months ago

The very first thing I did vibe-coding was commit my prompts and AI responses. In Cursor that's extremely easy—just 'export' a chat. I stopped for security concerns but perhaps something like that is the way.

zombiemama• 7 months ago

Secondly, if his creations are going to be relied upon, it will be the programmer's primary task to design his artifacts so understandable, that he can take the responsibility for them, and, regardless of the answer to the question how much of his current activity may ultimately be delegated to machines, we should always remember that neither "understanding" nor "being responsible" can properly be classified as activities: they are more like "states of mind" and are intrinsically incapable of being delegated.

EWD 540 - https://www.cs.utexas.edu/~EWD/transcriptions/EWD05xx/EWD540...

zkmon• 7 months ago

I spoke to a few people outside of IT and Tech recently. They are senior people running large departments at their companies. To my surprise, they do not think AI agents are going to have any impact in their businesses. The only solid use case they have for AI is a chat interface which, they think, can be very useful as an assistant helping with text and reports.

So, I guss it's just us who are in the techie pit and think that everyone else is also is in the pit and use agents etc.

theshrike795• 7 months ago

I think it's because what tech people do is objectively verifiable.

Did the thing the agent made do what it was supposed to do? Yes/No. There's no "mayyyybe" or feelings or opinions. If the sort algorithm doesn't sort it doesn't work.

But a secretary-agent for a non-techie is more about The Feels. It can summarize emails, "punch up" writing etc. But you can't measure whatever it outputs by anything except feels and opinions.

petcat• 7 months ago

I respect Armin's opinions on the state-of-the-art in programming a lot. I'm wondering if he finds that "vibe coding" (or vibe engineering) is particularly pleasant and effective in Rust compared to, say, Python.

johnwheeler2• 7 months ago

I bet it would be probably even nicer. I've been programming DSP in C++ with JUCE. I have a very rusty C++ experience from years ago, but it's getting me through a lot of it, and I feel pretty comfortable. Maybe my ignorance is bliss, and I'm really just putting out bad shit.

bigfishrunning• 7 months ago

My biggest unexpected finding: we’re hitting limits of traditional tools for sharing code. The pull request model on GitHub doesn’t carry enough information to review AI generated code properly — I wish I could see the prompts that led to changes. It’s not just GitHub, it’s also git that is lacking.

I find when submitting a complex PR, i tend to do a self review, adding another layer of comments above those that are included in the code. Seems like a nice place to stuff prompts

netdevphoenix• 7 months ago

In case people don't know, the author of the post is the creator of Flask, possibly Python's most popular micro web framework.

A year of vibes

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