Entries for January 21, 2026

  1. Portrait of Onur Solmaz
    @onusoz · /2026/01/21· View on
    AI agents are the greatest instrument for imposing organization rules and culture. AGENTS.md, agent skills are still underrated in this aspect. Few understand this Everybody in an org will use agents to do work. An AI agent is the single chokepoint to teach and propagate new rules to an org, onboard new members, preserve good culture Whereas propagating a new rule to humans normally took weeks to months and countless repetitions, it is now INSTANT = the moment you deploy the instruction to the agent. You use legal-ish language, capital letters, a generous amount of DO NOTs and MUSTs Humans are hard to change. But AI agents are not. And that is the only lever we need for better organizations
  4. Portrait of Onur Solmaz
    @onusoz · /2026/01/21· View on
    gave our internal @openclaw instance zeno a hubspot cli, because hubspot's own cli is limited to developer stuff It's called hubspot++. should we open source it?
  5. Portrait of Onur Solmaz
    @onusoz · /2026/01/21· View on
    just added session persistence to our kubernetes managed devboxes using zmx by Eric Bower (neurosnap/zmx on github). like tmux but with native scrollback! I don't want to give agents access to my personal computer, so I host them on hetzner. one click spawn, and start working
  6. Portrait of Onur Solmaz
    @onusoz · /2026/01/21· View on
    @nicopreme I do something equivalent on codex with just a skill Ralphing works 90% of the time with reviews, and if it gives a stupid review, you just revert
    @onusoz·
    Automated AI reviews on github by creating an ai-review skill and a script to paste trigger prompts and wait for their response. It is instructed to loop and not stop until all AI review feedback is resolved. This AI review workflow developed gradually based on the current capabilities, and I've realized recently that it became quite mechanical. So decided to automate it in full ralph spirit (it's ok because it's addressing feedbacks and fixing minor bugs) In the current state, we paste the contents of REVIEW_PROMPT.md into a comment, which automatically tags claude (opus 4.5) and codex (whatever model openai is serving) It then waits until both have responded. In the ai-review skill, it is instructed to take the feedback from SLopus with a grain of salt and ignore feedback that doesn't make sense It works! See in the images below. If the review is stupid, you will of course see it on the PR and what the model has done, and can revert it