ai

Learn AI Workflows by Stealing .claude Files

Cassia Scheffer

— 2 min read

When Harper Reed first published “My LLM codegen workflow atm”, I was hooked.

I had been working with LLMs for a few months, and Harper’s post made it all click. “THIS! This is the workflow that has been taking shape for me!” I dove in headfirst, and now, for the past few months, I’ve been AI-first in all my work. I hardly type code anymore. I read, refine, critique, and guide. I only get hands-on-keyboard when I have a very specific preference for how things should work.

Learning Takes Time

It took me a lot of time to learn this workflow. I was lucky enough to have willow.camp as a side project so I could get into the nitty-gritty. But not everyone has that opportunity.

If I had to learn this all today, here’s the approach I would take:

  1. Steal my .claude files, which I stole from Harper, who borrowed from Jesse.
  2. Install Claude Code
  3. Pick up a ticket and start with Claude Code. This is TRAINING WHEELS OFF! Try it out. If you need an editor on the side, hook claude up to Cursor by typing /ide.
  4. Type /brainstorm into Claude Code.
  5. Work through the brainstorming steps to generate a spec.md.
  6. Then kick off /plan, which will generate a todo.md.
  7. Finally, kick off /do-todo, which will iterate through todos.

Repeat.

The more you do this, the more it will become second nature. Eventually, you might not even need the commands anymore because you’ll know when to plan and when to act.

Break Things

I learn by breaking things!

  • Modify your commands to suit your needs. Come up with your own commands and see how they work for you.
  • Try the same thing twice to learn more about keeping the LLM on track and focused.
  • Try the same task without doing the planning and see what happens.
  • Try a massively complex task with and without planning.
  • Try a tiny, simple task with and without planning.

Breaking things is all about finding the boundaries. The best way to know what an AI agent is good at is to find out what it is BAD at!

Keep it cool. If the LLM wanders off into the woods to build a tree fort when you asked it to do something else, that’s okay. We all get off track. Here are a few things I do to learn:

Ask the LLM what went wrong:

  • “I noticed we struggled to solve this. Analyze our conversation and give me pointers on how to find a solution sooner.” This is a good prompt because sometimes, some incorrect context or weird code misdirects the LLM.
  • “We have struggled to find a solution. Explain to me why you thought this was the right path forward?” This is an excellent prompt for getting the LLM to reveal its thinking. I have learned from this prompt that it is very important to correct the LLM early and often. If you don’t, you both might misunderstand something. Once the LLM is off track, I ask for a session summary, clear the chat and start over.

Takeways

Try stuff! Try lots of stuff and try it often. Timebox your work so you don’t get stuck in a hole. Check yourself to see if the task you’re doing is valuable. Are you learning something? Are you making progress?

Learning is about making mistakes. Remember to make mistakes safely and adapt to them quickly. AI workflows can accelerate your work, but you have to shift your approach first and know how the tools work.

Read more