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A year of vibes

lucumr.pocoo.org

11–20 of 128 posts

Re: A year of vibes

#11
post #2

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…

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.

Re: A year of vibes

#12
post #4

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…

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

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

Re: A year of vibes

#13
post #12

Earlier quoted context omitted.

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

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

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.

Re: A year of vibes

#14
post #4

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…

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

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

Re: A year of vibes

#15
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.

Re: A year of vibes

#16
post #14
post #4

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…

> There is, for lack of a better word, value in failures Learning? Isn't that what these things are supposedly doing?

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

Re: A year of vibes

#17
"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/

Re: A year of vibes

#18
post #12

Earlier quoted context omitted.

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

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

... this inspired me to try using a "rg --pre" script to help reformat my JSONL sessions for a better experience. This prototype seems to work reasonably well: https://gist.github.com/simonw/b34ab140438d8ffd9a8b0fd1f8b5a...

Use it like this:

  cd ~/.claude/projects
  rg --pre cc_pre.py 'search term here'

Re: A year of vibes

#19
post #4

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…

"all my losses is lessons"

Re: A year of vibes

#20
post #4

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…

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…

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.

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