AI should only run as fast as we can catch up

I think your intuition matches mine. When I try to apply Claude Code to a large code base, it spends a long time looking through the code and then it suggests something incorrect or unhelpful. It's rarely worth the trouble.

When I give AI a smaller or more focused project, it's magical. I've been using Claude Code to write code for ESP32 projects and it's really impressive. OTOH, it failed to tell me about a standard device driver I could be using instead of a community device driver I found. I think any human who works on ESP-IDF projects would have pointed that out.

AI's failings are always a little weird.

In large projects you need to actually point it to the interesting files, because it has no way of knowing what it doesn’t know. Tell it to read this and that, creating summary documents, then clear the context and point it at those summaries. A few of those passes and you‘ll get useful results. A gap in its knowledge of relevant code will lead to broken functionality. Cursor and others have been trying to solve this with semantic search (embeddings) but IMO this just can’t work because relevance of a code piece for a task is not determinable by any of its traits.

But in the end, do you feel that it has saved you time?

I find hand-holding Claude a permanent source of frustration, except in the rare case that it helps me discover an error in the code.

Have you tried having AI build up documentation on the code first and then correct it where it’s understanding is wrong, then running code changes with the docs in the context, you can even separate it out for each module if you are daring. Ai still takes alot of hand holding to be productive with, which means our jobs are safe for now until they start learning about SWe principles somehow.

I‘ve had a similar feeling before Opus 4.5. Now it suddenly clicks with me, and it has passed the shittiness threshold, into the „often useful“ area. I suspect that’s because Apple is partnering with Anthropic and they will have improved Swift support.

Eg it‘s great for refactoring now, it’s often updating the README along with renames without me asking. It’s also really good at rebasing quickly, but only by cherry-picking inside a worktree. Churning out small components I don’t want to add a new dependency for, those are usually good on first try.

For implementing whole features, the space of possible solutions is way too big to always hit something that I‘ll be satisfied with. Once I have an idea on how to implement something in broad strokes, I can give a very error ridden first draft to it as a stream of thoughts, let it read all required files, and make an implementation plan. Usually that’s not too far off, and doesn’t take that long. Once that’s done, Opus 4.5 is pretty good at implementing that plan. Still I read every line, if this will go to production.

I start new projects "AI-first" – start with docs, and refining them on the go, with multiple CLAUDE.md in different folders (to give a right context where it's needed). This alone increases the chances of it getting tasks right tenfold. Plus I almost always verify myself all the code produced.

Ironically, this would be the best workflow with humans too.