I felt that, too. It turns out I was getting 'too comfortable' while using CC. The best way is to treat CC like a junior engineer and overexplain things before letting it do anything. With time, you start to trust CC, but you shouldn't do that because it is still the same LLM when you started.

Another thing is that before, you were in a greenfield project, so Claude didn't need any context to do new things. Now, your codebase is larger, so you need to point out to Claude where it should find more information. You need to spoon-feed the relevant files with "@" where you want it to look up things and make changes.

If you feel Claude is lazy, force it to use more thinking budget "think" < "think hard" < "think harder" < "ultrathink.". Sometimes I like to throw "ultrathink" and do something else while it codes. [1]

[1]: https://www.anthropic.com/engineering/claude-code-best-pract...

> If anyone has pointers, I’m all ears!!

Give programming a try, you might like it.

I ran into this too.

In my case it was exactly the kind of situation where I would also run into trouble on my own - trying to change too many things at once.

It was doing superbly for smaller, more contained tasks.

I may have to revert and approach each task on its own.

I find I need to know better than Claude what is going on, and guide it every step. It will figure out the right code if I show it where it should go, that kind of thing.

I think people may be underestimating / underreporting how much they have to be in the loop, guiding it.

It’s not really autonomous or responsible. But it can still be very useful!

Sometimes I take a repomix dump of a slice where there's issues and then get chat gpt to analyze it and come up with a step by step guide to fix it for Claude to follow. That has worked.

It's the plateau; once your codebase hits a certain size/complexity, CC struggles to make exponential progress. To make good progress, you have to dive in and guide it very finely.

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