
A Zenn essay describes a workflow where you write rough specs into CompanyBrain, hand the goal to OpenAI's resident agent dots, and just review and merge the pull requests it raises.
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The essay frames the change as a shift from prompting an AI to handing it a standing goal. Earlier AI worked as a single exchange; dots keeps running in the background and holds its own cloud environment, and specialist dots for roles like accounting, invoicing and customer support are starting to appear for companies.
The author ties this to a CompanyBrain concept from an earlier essay: write decisions, policies and common assumptions as Markdown in one place and link them to GitHub Issue and PR history so AI and people read the same context. For a resident agent, the biggest obstacle is said to be the cost of re-explaining context each time, and CompanyBrain is presented as the fix.
On automation, the author describes a loop where the agent opens a pull request, CI passes, and GA4 metrics — error rates, drop-offs, conversions after deployment — act as one safety valve for auto-merge, deployment and rollback. The stated limits are to automate only as far as tests protect, keep permissions narrow, avoid too much parallelism, and keep rollback available.
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