Ask HN: How is AI-assisted coding going for you professionally?

I work for a university. We've got a dedicated ChatGPT instance but haven't been approved to use a harness yet. Some devs did a pilot project and approval/licenses are supposedly coming soon.

It has made my job an awful slog, and my personal projects move faster.

At work, the devs up the chain now do everything with AI – not just coding – then task me with cleaning it up. It is painful and time consuming, the code base is a mess. In one case I had to merge a feature from one team into the main code base, but the feature was AI coded so it did not obey the API design of the main project. It also included a ton of stuff you don’t need in the first pass - a ton of error checking and hand-rolled parsing, etc, that I had to spend over a week unrolling so that I could trim it down and redesign it to work in the main codebase. It was a slog, and it also made me look bad because it took me forever compared to the team who originally churned it out almost instantly. AI tools are not good at this kind of design deconflicting task, so while it’s easy to get the initial concept out the gate almost instantly, you can’t just magically fit it into the bigger codebase without facing the technical debt you’ve generated.

In my personal projects, I get to experience a bit of the fun I think others are having. You can very quickly build out new features, explore new ideas, etc. You have to be thoughtful about the design because the codebase can get messy and hard to build on. Often I design the APIs and then have Claude critique them and implement them.

I think the future is bleak for people in my spot professionally – not junior, but also not leading the team. I think the middle will be hollowed out and replaced with principals who set direction, coordinate, and execute. A privileged few will be hired and developed to become leaders eventually (or strike gold with their own projects), but everyone in between is in trouble.

> At work, the devs up the chain now do everything with AI – not just coding – then task me with cleaning it up.

This has to be the most thankless job for the near future. It's hard and you get about as much credit as the worker who cleans up the job site after the contractors are done, even though you're actually fixing structural defects.

And god forbid you introduce a regression bug cleaning up some horrible redundant spaghetti code.

I am getting disproportionately good results with the models by following a process: spec -> plan -> critique -> improve plan -> implement plan.

On two greenfield web apps using straightforward stuff (Preact, Go, PostgreSQL) Claude Code has been very helpful. Especially with Claude Code and Opus >= 4.5, adding an incremental feature mostly just works. One of these is sort of a weird IDE, and Opus even does OK with obscureish things like CodeMirror grammars. I literally just write a little paragraph describing what I want, have it write the code and tests, give it a quick review, and 80% of the time it’s like, great, no notes.

To be clear, this is not vibecoding. I have a strong sense of the architecture I want, and explicitly keep Claude on the desired path much like I would a junior programmer. I also insist on sensible unit and E2E test coverage with every incremental commit.

I will say that after several months of this the signalling between UI components is getting a bit spaghettilike, but that would’ve happened anyway, and I bet Claude will be good at restructuring it when I get around to that.

I also work in a giant Rails monolith with 15 years of accumulated cruft. In that area, I don’t write a whole lot, but CC Opus 4.6 is fantastic for reading the code. Like, ask “what are all the ways you can authenticate an API endpoint?” and it churns away for 5 minutes and writes a nice summary of all four that it found, what uses them, where they’re implemented, etc.