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Read mini classes on this topic together, starting with the latest lessons for context.
lessons
Tag guide
These posts cover the boundaries readers should set when AI agents and always-on assistants become work actors.
When AI skills collide, reduce overlaps at the source by clarifying event boundaries, removing duplicate triggers, and narrowing write ownership. Arbitration should be the last fallback for unavoidable overlap.
Mina turns a messy refund case into observable stop rules: verify gaps and conflicts, approve exact external actions, and preserve enough state for another person to resume.
No-code agents can automate an entire workflow, but they should not inherit blanket authority. Classify each action by consequence, then place an informed human handoff before the risk becomes real.
Choose an AI entry point by the job and its consequences, not by API or MCP momentum: public reading, bounded lookup, or an approved and recoverable action.