• Actions Taken:
    • Investigated using claude for a bootstrapping UI.
    • Discovered that claude’s license restricts its use for building potentially competing systems.
    • Concluded that claude is not a viable option for the project.
    • Decided to investigate using the qwen3-code fork of the Gemini CLI as an alternative bootstrapping mechanism.
    • Created a new task in TASKS.md to track this investigation.
    • Tested qwen3-code both with Alibaba’s hosted model and with a local model kirito1/qwen3-coder.
    • Found that qwen3-code works more or less correctly in both cases, similar to how well claudecode was working, but with the promise of local operation.
    • The kirito1/qwen3-coder model is small and pretty fast, but it remains to be seen if it is accurate enough.
  • Friction/Success Points:
    • The license restriction on claude was an unexpected dead end.
    • Identified qwen3-code as a promising alternative.
    • Successfully tested both hosted and local versions of qwen3-code.
  • Lessons Learned:
    • Licensing restrictions are a critical factor to consider when selecting tools for AI development.
    • Having a backup plan is essential when initial tooling choices don’t work out.
    • Local models like kirito1/qwen3-coder offer the potential for private, fast operation, but accuracy needs further evaluation.
  • Next Steps:
    • Investigate how to build a larger version of an Ollama model (similar to how kirito1/qwen3-coder was made) to use tools and have a larger context size.
    • Add an incomplete task for this to TASKS.md.