[ogig]

I decided to really learn what is going on, started with: https://karpathy.ai/zero-to-hero.html That give a useful background into understanding what the tool can do, what context is, and how models are post trained. Context management is an important concept. Then I gave a shot to several tools, including copilot and gemini, but followed the general advice to use Claude Code. It's way better that the rest at the moment. And then I dive deep into Claude Code documentation and different youtube videos, there is plenty of good content out there. There are some ways to customize and increase the determinism of the process by using the tools properly.

Overall my process is, define a broad spec, including architecture. Heavy usage of standard libraries and frameworks is very helpful, also typed languages. Create skills according to your needs, and use MCP to give CC a feedback mechanism, playwright is a must for web development.

After the environment and initial seed is in place in the form of a clear spec, it's process of iteration via conversation. My session tend to go "Lets implement X, plan it", CC offers a few route, I pick what makes most sense, or on occasions I need to explain the route I want to take. After the feature is implemented we go into a cleanup phase, we check if anything might be going out of hand, recheck security stuff, and create testing. Repeat. Pick small battles, instead of huge features. I'm doing quite a lot of hand handling at the moment, saying a lots of "no", but the process is on another level with what I was doing before, and the speed I can get features out is insane.

[tossandthrow]

Thanks! Very valuable insights.

I have been through Karpathy's work - however, I don't find that it helps with large scale development.

Your tactics work successfully for me at smalle scale (at around 10klocs, etc) and starts to break down - especially when refactorings are involved.

Refactoring happens when I see that the LLM is stumbling over it's own decisions _and_ when I get a new idea. So the ability to refactor is a hard requirement.

Alternatively refactoring could be achieved by starting over? But I do have a hard time accepting that idea for projects > 100klocs.

[nprateem]

It is until it's not. That's the problem. The AI gets tripped up at some point, starts frigging tests instead of actually fixing bugs, starts looping then after several hours says it's not possible. If you're lucky.

Then on average your velocity is little better than if you just did it all by hand.

[ogig]

The AI gets tripped phenomenon is something I've experienced, and I think it's again related to context usage. Using more agents and skills will reduce the pollution on the main context, and delay the moment where things go weird. /clear after each small mission. As said above, CC needs heavy guidance, but even with these issues, I'm way faster.