A year of vibes
16 comments
·December 22, 2025simonw
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!
NeutralForest
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.
kgwxd
> There is, for lack of a better word, value in failures
Learning? Isn't that what these things are supposedly doing?
the_mitsuhiko
If by "these things" you mean large language models: they are not learning. Famously so, that's part of the problem.
stacktraceyo
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
simonw
Running "rg" in your ~/.claude/ directory is a good starting point, but it's pretty inconvenient without a nicer UI for viewing the results.
the_mitsuhiko
Amp represents threads in the UI and an agent can search and reference its own history. That's for instance also how the handoff feature leverages that functionality. It's an interesting system and I quite like it, but because it's not integrated into either github or git, it is sufficiently awkward that I don't leverage it enough.
tolerance
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.
divbzero
> 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.
JKCalhoun
Got distracted: love the "WebGL metaballs" header and footer on the site.
bgwalter
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).
r2_pilot
>>"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.
JimDabell
> 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.
grim_io
I'm glad there has been a break in endless bikeshedding over TDD, OOP, ORM(partially) and similar.
sixtyj
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.
"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 sense that very smart people are 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/