Hey HN! Quick update on Mysti based on your feedback:
1- Mysti now supports GitHub Copilot CLI as a fourth provider.
So you can now do Claude Code + Copilot (running GPT-5) in Brainstorm mode, or any combination of the 4 providers. Mix and match based on what catches different issues.
2- Mysti is now MIT Licensed. Switched from BSL 1.1 to MIT.
3- Better Auth UX When a CLI isn't authenticated, you now get a friendly error with one-click "Open Terminal & Authenticate" instead of cryptic CLI errors.
I was working on a project where I tried Claude code to optimize processing of taichi Kernel and it kept using structure that didn’t work with taichi lang limitations so it kept going on a loop, did the same with codex and faced the same issue then tried to have both agents discuss it and it worked! It saved me several hours
Thanks! You would need to instruct the agents to follow best practices and explain it while developing. Sometimes they get messy but if you use the right instructions/persona/skills then you will get very good results
A final review from experienced developers is always recommended
I find it useful to let one agent come up with a plan after a review and another agent implementing the plan. For example, Gemini reviewing the code, codex writing a plan and then Claude code implementing it
What about the reverse, after Claude code implements it, let Gemini/Codex do a code review for bugs and architecture revisions? I found it is important to prompt to only make absolutely minimal changes to the working code, or unwanted code clobbering will happen.
Haven’t done Evals yet but measured on few real world situations where projects got stuck and the brainstorm mode solved it. Definitely running evals is something worth doing and contributions are welcomed
I think what really degrades the output is the context length vs context window limits, check out NoLima
This is why context optimization is going to be critical and thank you so much for sharing this paper as this also validates what we are trying to do. So if we managed to keep the baseline below 40% through context optimization then coordination might actually work very well and helps at scaling agentic systems.
I agree on measuring and it is planned especially once we integrate the context optimization. I think the value of context optimization will go beyond just avoiding compacting and reducing cost to providing more reliable agents.
