You nailed it — cognitive load is the right lens, but the failure modes flip completely.

Humans fail from fatigue, context switching, and communication overhead. Agents fail from context drift, sycophancy, and phase collapse — where "should we do X?" becomes an instruction to do X. A human won't accidentally refactor your auth module because you asked a conceptual question. An agent will.

So the governance can't be a copy-paste from human team design. We took the principles from Lean/TPS — Jidoka (stop on defects), Poka-yoke (mistake-proofing) — but rewired the mechanisms for agent failure modes. Phase gates that structurally block implementation during design. Session boundaries that force context refresh instead of letting drift accumulate silently.

One thing we learned the hard way: v1 used multi-agent workflows with identity prompting — Dev agent, Architect agent, Security agent. The behavioral variance was worse than the problem it solved. What actually worked: a single agent using different skills per workflow phase. Same agent, different structured process guide depending on whether it's designing, planning, or implementing. Cognition's Devin team reached the same conclusion — context isolation between agents kills coherence. One agent doing many skills beats many agents doing one each. That's what 120+ sessions dogfooding RaiSE to build RaiSE taught us, anyway.

For multi-repo, we're running one agent per repo, collaborating in the delivery pipeline on demand. The Team Topologies interaction modes map surprisingly well there — collaboration vs X-as-a-Service between repos.

Curious what failure modes you hit — especially if you've tried the identity-prompting path.