Is it too much to expect companies to share some of this in the open vs just the results?

I think we are just very close to the peak of a typical Gartner hype cycle around LLMs. They are useful but overhyped. There will be more posts about fuckups that happen because people run things on autopilot and cannot keep up with reviewing AI generated code.

Do not get me wrong. I use AI all day to speed things up. But I believe that there is only a small group, maybe 5 percent or less, that actually knows how to use AI properly (I'd count myself not yet in that 5%), which I see as potentially dangerous. The other issue I see is inexperienced software engineers writing software. Although I see this as a great value add and productivity boost for prototyping, I am afraid of the “I do not know much about coding but can also make PRs to our codebase” mentality.

For those of you that run things on autopilot, how do you keep code quality under control? And how do you handle refactoring? I am really curious, because one option now is also to just YOLO your LLMs to write code based on the maturity of the product. You can refactor an app or parts of it pretty fast again with LLMs. While tech debt accumulates faster, we also have the opportunity to rebuild faster.

I find it interesting that this line of adventure quickly lead to locking problems.

> A long-running agent made video rendering 25x faster with an efficient Rust version.

Which is not an optimization. This is coming from a Rust dev; Rewriting it in Rust is not the optimization.

Also, I do not believe they actually reviewed the SolidJS->React PR. This PR is incredibly unrealistic and should've been done with either stacker PRs or incremental non-breaking changes.

None of this feels organic, can we stop pretending it is?

To continue the pessimistic tone, none of the writing went in-depth. I did not gain any knowledge, just a marketing post.

Very cool. Seems long running AI Agents are the new monuments.

Is the code not even compiling a feature or...

Reviewing all this code is the issue.

would really appreciate some elaboration as they gloss over the most important part in my kind. why can’t one agent just do it. that’s what ai seems to be - an amalgamation of all our knowledge. why split it back up into separate tentacles. i think focus should be on letting it envelop the problem like a fog and swallow it whole, instead of molesting it independently at touch points and reporting back to … the brain? it’s pretty ridiculous actually. just mimicking ourselves yet again.

“Arthur looked up. ‘Ford,’ he said, ‘there’s an infinite number of monkeys outside who want to talk to us about this script for Hamlet they’ve worked out.”