One job, done exactly.

The harness between an AI agent and the real world. The agent declares an intent; Cazi runs it as an ephemeral container task on a real node and keeps the spec, every event, the logs and the exit code. Agents act only inside a reviewed allowlist and scope, under goals a person wrote.

• Intents, not shell: tools are YAML workload specs the agent picks from
• MCP server: the agent's hands, every action on the record
• Agents contained by allowlist, scope and circuit breakers
• Pipelines: one step's stdout feeds the next
• Failures become known patterns that warn or block the next run
• Every unit of work names who did it, and for whom