Feb 5 • General discussion
10X AGENTIC PRODUCTIVITY WORKFLOW 🦞
I analysed how the creator of OpenClaw uses AI coding agents. Here are top takeaways:
1. Runs 3-8 agents at the same time — each in its own terminal window. Lets them work for hours without checking on them.
2. Gives agents testing tools — so they can check their own work instead of waiting for him to verify everything.
3. Short prompts — 1-2 sentences max. The AI reads your code anyway, no need for long explanations.
4. Screenshots over descriptions — "fix the padding" + a screenshot beats writing a paragraph explaining what's wrong.
5. Command-line tools over plugins — AI already knows how to use git, database commands, etc. No need to add extra tools.
6. "Write tests right after the feature" — the agent just built it, it knows what might break. Don't start a new chat to ask for tests later.
7. Think about scope first — before starting, estimate how big the change is. If it's taking too long, stop and ask for a status update.
8. Commits straight to main — only uses branches when unsure about big architectural decisions.
1
0 comments
10X AGENTIC PRODUCTIVITY WORKFLOW 🦞
powered by
skool.com/ai-learn-3541
Build & ship reliable AI agents + get paid: LangGraph, RAG, MCP, tools, memory, evals. Templates, build-alongs, and feedback.
Suggested communities
Powered by