Useful rules @tedx_ai - I also find these 3 debugging techniques useful when I want to debug stubborn bugs:

1. Use deeper reasoning LLMs like 3.7 Sonnet + thinking or augment your LLM with Sequential thinking if supports MCP

Enabling extended thinking or smart model selection breaks the repetitive solution attempts most assistants get trapped in.

2. Ensure the AI Focuses on 1 failure at a time, target specific test cases or test suites until solved - 
Disable any automated actions like immediately addressing linting issues

Test Isolation prevents the assistant from jumping between errors without solving any.

3. Create specialised knowledge docs to share alongside the issue (build them with LLMs and store for reuse)

Including latest best practices and domain-specific context dramatically improves solution quality.

Think I'll go away and write a more comprehensive thread as i find defining workflows like this in this new dev paradigm helpful.