Is it all just vapourware?

I was fairly skeptical of agentic coding before I used it for a real product. Although I still have to be heavily involved in planning the code that LLMs write for me, they can write code much faster than I can, and they know more about edge cases than I do, so they can handle edge cases/subtle bugs that I would have missed. I have been paid to write code at every level of the stack from assembly to frontend javascript, but I'm not equally good at all those areas. In some areas I can still outperform LLMs, but for areas I'm weak they do a much better job than I would have.

I still think of what I'm doing as software engineering, and I'm glad that I had many years of professional and hobby development before using agents since I think that's given me the ability to make good architectural decisions (and helps me resteer the LLMs when they want to do something suboptimal), but my involvement in actually writing code is quickly going to zero. That said, they aren't perfect and they still introduce bugs, but I believe the quality of my current product is higher than what I would have created pre-agentic coding.

Things I've found helpful in keeping quality high:

- Visual regression tests (detect UI bugs before you commit them)

- Fuzz testing of interfaces and app behavior

- Automatically add regression tests for any bug that I/the LLM fixes

- Logging/alerting that tracks an errors/invariant violations triggered in the app

- Performance metrics that are surfaced in a dashboard.

All of these are very easy to add since the LLM can create this infrastructure for you. The fuzz testing in particular is something very few products I've previously worked on have since most people don't know how to implement it. I ran the fuzzers for a few minutes and they quickly caught multiple subtle bugs that I was not aware of.

This is a real product that helps a real, non-VC funded service business, and although I could have made something similar myself it would have taken me a lot longer, be harder to use, and probably be less reliable.

Edit: while it's true that you can quickly blow through the $20/month plan, the $200/month plan allows you to get a lot done and is basically sufficient for my needs. It's also very cheap when you consider what it would cost to pay someone to do similar work.

I don't know how you can claim it's all vapour ware.

Two years ago, I couldn't just roughly describe my backlog and then have the code fixed. I had to type it out myself, run it, look at logs, fix toolchain issues, and so on. It was tedious. Or I could get a junior to do it.

Now can get these things done quite fast, without concentrating nearly as hard.

Clearly, it isn't vapour.

It delivers something. That something we have yet to figure out the best way to use, but there's definitely something there that works.

I get the feeling a lot of people are frustrated because the little gains are lost in organisational chaos, rather than the tools not working.

I did but it was followed by "holy shit now I gotta review this +3000 -500 LOC PR full of subtly wrong abstractions, needless diversions and incorrect assumptions".

People keep repeating your sentiment here but I simply can't follow, are we even on the same planet? Or did everyone switch to just not caring about maintainability and code quality anymore? Or are your work tasks simply so mindnumbingly, stupidly simple that even an AI can oneshot them properly?

I mean this honestly btw, not dismissively like some sister comments. The gap between the productivity increases people report on HN and what I experience myself is insane. In fact, if I factor in the procrastination I find myself doing on dotting the i's on a supposedly "one-shotted" AI implementation of a nontrivial feature, I think the AI actively slows me down.

The only way I've found that I can actually use AI productively and sustainably is in very small tight loops and, well, at that point it's not that much faster than just typing in the code (with the occasional "Cursor Tab" complete).

Am I doing something wrong?

I'll worry when that stops happening. Probably means I'm getting in my own way or not thinking big enough.

> I'm so sick of having AI chase a bug and having to lead it by the hand like a toddler to try and help me solve bugs.

This hasn't been my experience at all. I can give it a vague description of the problem and have it find it pretty easily without any more input from me.

I do think there's a pretty big variation in tools and setups and what output people are getting. I'm now just using OpenAI Codex in VS Code and it churns through problems like they're nothing.

Sometimes I have to get it to not over-engineer a solution; not because it's necessarily wrong but because I don't need that much correctness.