Hacker News Reader

Comment by stefangordon | Hacker News Reader

Our agents automatically review our PR's - the authors agents automatically see the feedback and make fixes, and automatically merge when everything is green.

A well authored CI review process is significantly better than any human could do. We have the AI review not only the changes but clone and investigate all related repositories that integrate with the code to evaluate interactions, check all open and historical issues that may be related, review production/development logs for the feature, etc.

It will then also go update issues/tasks to reflect the changes after the merge.

Similarly you can have automated agents watching post-deployment to mitigate risk in the "a new feature just went out" time-frame. Just having someone check the related logs in the hours after deployment can catch a lot of issues that otherwise would turn into a fire-drill.

View on HN

Should this not all happen before the PR is created?

My question as well. Why is this happening in ci/ci? Why aren't contributors performing the automated review and correction step locally?

The only answer I can imagine is that it supports reviewing patches from people who aren't using AI or review by humans but parent doesn't mention this.

What if your working on work that isn't easily worktreeable due to available resources but you want to work on multiple things? Seems pretty normal to leverage CI as a cloud compute resource instead of clogging up the machine i use to interact with my agents and communicate with others.

Yes, it should. Reduces a lot of noise.

Must be a token burner setup. Nice if you really got it to work. Now also add business agents that come up with new features based on actual research. Your automated humanless company is almost there.

Sounds like an AI-OS slop machine…been there, done that!

They're making money, which is more than most ICs living in cost centers can say.

The human code monkey sometimes thinks too highly of the task of coding. That's never once been the job to be done.

Every engineer is going to become a master of understanding and measuring need, opportunity cost, organizational support and headwinds, political will, etc. These are the true features of the job. The coding part will fall away entirely.

Deliver value. Code used to be the expensive part, but now it's becoming cheap, fungible, and ephemeral.

This all assumes LLMs can maintain a steady state of code while extending it.

JFC, get off the Kool-Aid dude ;)

...of course you're likely just trolling, hard to say with the drivel coming out of Silicon Valley the last few years. In that case: my apologies and keep up the good work :D

This is where we landed too. It works remarkably well. AI guidance is really the crucial thing here. I know a lot of people don't like this, think it's really bad, think it just results in slop... but it doesn't or at least never results in dead end slop. If you find what you get out of AI is weak in some area, then get it to focus on making sure that it does a better job, give it more guardrails / guidance etc till you are happy with the result.

Reply on news.ycombinator.com