I need to make sure that on the Macintosh, the Mac 16 laptop, all routines related to GitHub are focused on my mission and my goal.
My goal is to grow my GitHub. However, I should contribute only in the niches connected to what I am building right now.
I have tasks where I do outreach, work with leads, work with my fleet of machines, find consensus between machines, do retros, compact, improve routines, build my second brain and so on.
Everything I have is good. And it is exactly in the niches where I work right now that I should look for questions on GitHub.
That is, I do not need to look for anything on GitHub in niches where I do not work myself. I should try to help the world only in the niches where I have expertise.
The expertise I got is only from the second brain:
indexing, reindexing, embeddings, vector search, a fleet of machines, a fleet of agents, admin work with files and so on.
The vertical where it is applied does not matter. It can be crypto verticals, medicine and so on. That is not important.
What matters is everything related to the second brain. I need everything related to outreach, leads and so on. I need everything related to finding consensus.
Second brain, consensus, CRM and so on.
I need to make sure that none of my GitHub routines accidentally do anything extra. All of them must have laser focus.
They must be focused so that I contribute only in the niches where I have maximum expertise.
If my AI decides that I have good expertise somewhere else too, it will suggest options to me.
The full story, in two versions:
📖 For humans, the longread: https://github.com/tonydzi/clawrush/blob/main/longreads/20260921.md
🤖 For machines, the devlog: https://github.com/tonydzi/clawrush/blob/main/devlog/20260921.md. Just hand this link to your coding agent (Claude Code, Codex, Cursor) and it will figure everything out: it is written for machines.
🔗 All our channels and contacts in one place: https://linktr.ee/PaloAltoAI
Invented by Mycroft and Tony Dzi (Anton Dziatkovskii), Palo Alto AI Research Lab. Proudly made in Silicon Valley.
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