For me, a team of junior developers that refuse to learn from their mistakes is the fuel of nightmares. I'm stuck in a loop where every day I need to explain to a new hire why they made the exact same beginner's mistake as the last person on the last day. Eventually, I'd rather spend half an hour of my own time than to explain the problem once more...

Why anyone thinks having 3 different PRs for each jira ticket might boost productivity, is beyond me.

Related anime: I May Be a Guild Receptionist, But I'll Solo Any Boss to Clock Out on Time

The current challenge is not to create a patch, but to verify it.

Testing a fix in a big application is a very complex task. First of all, you have to reproduce the issue, to verify steps (or create them, because many issues don't contain clear description). Then you should switch to the fixed version and make sure that the issue doesn't exists. Finally, you should apply little exploratory testing to make sure that the fix doesn't corrupted neighbour logic (deep application knowledge required to perform it).

To perform these steps you have to deploy staging with the original/fixed versions or run everything locally and do pre-setup (create users, entities, etc. to achieve the corrupted state).

This is very challenging area for the current agents. Now they just can't do these steps - their mental models just not ready for a such level of integration into the app and infra. And creation of 3/5/10/100 unverified pull requests just slow down software development process.

I’ve been using Cursor and Code regularly for a few months now and the idea of letting three of them run free on the codebase seems insane. The reason for the chat interface is that the agent goes off the rails on a regular basis. At least 25% of the time I have to hit the stop button and go back to a checkpoint because the automatic lawnmower has started driving through the flowerbed again. And paradoxically, the more capable the model gets, the more likely it seems to get random ideas of how to fix things that aren’t broken.

Over the last two days, I've built out support for autonomy in Aider (a lot like Claude Code) that hybridizes with the rest of the app:

https://github.com/Aider-AI/aider/pull/3781

Edit: In case anyone wants to try it, I uploaded it to PyPI as `navigator-mode`, until (and if!) the PR is accepted. By I, I mean that it uploaded itself. You can see the session where it did that here: https://asciinema.org/a/9JtT7DKIRrtpylhUts0lr3EfY

Edit 2: And as a Show HN, too: https://news.ycombinator.com/item?id=43674180

and, because Aider's already an amazing platform without the autonomy, it's very easy to use the rest of Aider's options, like using `/ask` first, using `/code` or `/architect` for specific tasks [1], but if you start in `/navigator` mode (which I built, here), you can just... ask for a particular task to be done and... wait and it'll often 'just get done'.

It's... decidedly expensive to run an LLM this way right now (Gemini 2.5 Pro is your best bet), but if it's $N today, I don't doubt that it'll be $0.N by next year.

I don't mean to speak in meaningless hype, but I think that a lot of folks who are speaking to LLMs' 'inability' to do things are also spending relatively cautiously on them, when tomorrow's capabilities are often here, just pricey.

I'm definitely still intervening as it goes (as in the Devin demos, say), but I'm also having LLMs relatively autonomously build out large swathes of functionality, the kind that I would put off or avoid without them. I wouldn't call it a programmer-replacement any time soon (it feels far from that), but I'm solo finishing architectures now that I know how to build, but where delegating them to a team of senior devs would've resulted in chaos.

[1]: also for anyone who hasn't tried it and doesn't like TUI, do note that Aider has a web mode and a 'watch mode', where you can use your normal editor and if you leave a comment like '# make this darker ai!', Aider will step in and apply the change. This is even fancier with navigator/autonomy.

The trend with LLMs so far has been: if you have an issue with the AI, wait 6 months for a more advanced model. Cobbling together workarounds for their deficiencies is basically a waste of effort.