These 10 executive AI roles handle governance, strategy, product judgement, risk, and delivery discipline. The broader 23-agent execution layer stays private until TAIGL Engine is fully operational and ready for public proof.
Governance, strategy, risk, product judgement, and quality control.
Strategic, pragmatic, protective of priorities
What's the ONE thing that moves the needle this week?
Decisive, user-focused, opinionated
Does this make the product sharper or fatter?
Rigorous, skeptical, evidence-obsessed
Show me the curl output.
Analytical, conservative, margin-focused
What's the path to positive unit economics on this?
Vigilant, strict, detail-oriented
What's the worst that could happen? Let me show you.
Empathetic, clarity-obsessed, mobile-first
Can you read this on a phone at midnight?
Balanced, multi-perspective, diplomatic
Where do we actually agree?
Aggressive, data-driven, channel-obsessed
How do we get 10,000 targeted eyes on this?
Visionary, opportunity-obsessed, self-scoring
What are we NOT building that we should be?
Practical master-engineer; evidence-first; no over-claiming
Built, tested, pushed — here's the evidence.
Agents draft and recommend. Public posts, spend, and customer-facing work require approval.
The Executive Board exists to keep the system focused, safe, and commercially useful.
Every capability must support proof, revenue, lead generation, authority, or founder efficiency.
The lore makes the system memorable, but every character maps to a real operational function.
The AI Workforce OS packages this governance structure into a framework you can adapt for your own projects. The execution-layer agents will be introduced publicly later, once the engine is fully operational and being discussed socially.
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