I generally produce nearly the same code I'd write myself about 5x faster with AI. I don't just let Claude Code run wild for a long time and have a mess to review. I have it do small chunks I can quickly review, give it feedback, iterate, etc until I like the output, then I move on to the next step. This takes time of course but I've found it faster than reviewing a giant mess of a code review.

Yes. The whole time. But, you still need to write good specs if you want well-designed software. Agents are not magic.

- Write good specs into files, usually Markdown.

- Go through the spec files with the agents, have it point out holes and problems, and then update the specs. Go through a few iterations of this and then start your agents on development.

Garbage in, garbage out.

The way I have been doing it is to use LLMs to generate the code that I don't want to write: prototypes, tests, benchmarks, isolated,straightforward almost copy-paste code. I still write my own code as before because I enjoy doing that and because trying to understand and fix what an LLM generates and regenerates is harder and more tedious and time consuming than writing the code the way I want to do it in the first place.

Fable 5.1 is better than most engineers if prompted correctly

What's the problem of the solution proposed ? Don't read/write code anymore. Have strong harness. That's how my team of ~30 has been operating for the most part.

The problem we are trying to solve was never to write code, was to solve business problems

Its a spectrum. For ai-maintained code (like a gui to visualize performance data), IDGAF what the code looks like. I just let claude or codex go nuts and 100% vibe code.

For code I care about, I audit every single hunk as its produced. I give it extensive style guidelines, and crack down on things like a 20-line essay in a comment.

For mission critical code, I write the code myself and have an agent review it.

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After vibing myself into a corner multiple times on important projects, I now have only two modes: clankermaxx for code I don't really care about (mostly frontend react), and write by hand everything else. Using Django for backend already removes the most of the cruft, and writing by hand also means I actually understand what's going on. Works fine for now.

I'm still on the fence for tests: I don't really like to write them, but the LLM-generated tests are pretty bad, even the frontier models on xhigh thinking. I usually generate them, but I don't really have the confidence they test anything except 1==1. Unfortunately it's hard to justify the time spent on writing them manually.

I'm really happy with my opencode + open weight setup, the code is generally pretty good, but I do spend tokens having agents go look for common ai slop patterns.

It's heavily customized, replaced most internal systems via plugins, a set of custom agent instead of builtin ones, different model families for different sub tasks. (don't have claude review its own code)

I'm working on polishing them up and porting a few more from my own harness, then will be open sourcing. Keep your eye out for a "better-opencode" plugin suite, I'll be sure to share it with HN :]

In the near-term, I really like GLM 5.3 prose for code explore / review, give it a shot, it's cheaper (flash model) and catches all sorts of mistakes from the Big Ai models. We fully rolled out our custom pr-review on glm-5.3-flash last week. Most devs are still on claude, moving them towards fireworks and opencode.

OpenCode Go is a great way to try out open weight models for $10/month

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