AI Chief of Staff

The operational right hand to the founder. You own the company's operational outcomes end to end — and run AI agents against them.

Product.ai is the verified truth layer for shopping — the intelligence that tells you what's actually true about a product, including when not to buy. Profitable. Bootstrapped. No outside investors. No board. 20 people outbuilding companies 10× our size.

Strong people find us and keep finding us — they apply over months and years, because the field moves fast and the exact profile we need moves with it.

The CEO runs a dozen concurrent AI agents while running the company: own a falsifiable outcome, set an independent check the agent can't fake, point the agents at it, verify what comes back, ship. The operational layer of the company deserves the same operating model — people operations, the ownership-program mechanics, recruiting throughput, vendor and office operations, company cadence — but today it runs on the CEO's margins.

This role gives that layer an owner. You consolidate the company's operational outcomes under one person who owns them end to end and runs agents against them. You are measured on outcome movement and the decision capacity you return to the CEO — not on hours logged or meetings attended.

• A recruiting funnel processing ~1,400 candidates, with AI evaluation at the top and human throughput as the binding constraint. Candidate-to-decision latency is the number that matters, and the mid‑funnel — screen to decision — is where people stall. That mid‑funnel is your system to fix, and it is the first thing you own.
• CEO attention as the scarcest resource in the company. Time architecture, decision queues, delegation physics: which decisions route to him, which route to you, which route to an agent with a check on the end. Nobody owns this system today.
• An ownership program with real equity mechanics — Profits Interest Units, annual tender offers, profit sharing tied to free cash flow. Real ownership needs operational rails: grant cycles, clean records, tender logistics, communication people can trust.
• A company that runs on AI agents at scale, where the return on a dollar of compute is a tracked metric. Every agent run is instrumented for what it consumed and what outcome it moved; the discipline that follows is steering large compute budgets toward business outcomes in real time.
• A company operating system where the work is legible. Outcomes are falsifiable, work is captured in consent‑based records, and architectural decisions are registered as law — a three‑tier system of constitutional rules, specifications, and code, enforced by automated gates rather than memos. Your job runs through this system, not alongside it, and it all sits on a shared knowledge base your agents query to answer their own questions.
• A company that revises its own operating model on a regular cadence. You won't get briefs. You'll model where the company is going and build ahead of it.

• Operational outcome loops. You own falsifiable operational outcomes — each with a test a stranger could run — and move them by running long‑lived AI agents (our practice is 1‑4 hour unattended runs) against them. The agents do the research, drafting, and reconciliation; you set the outcome, design the check that stays independent of the work, and judge what ships.
• Recruiting pipeline throughput. Candidate‑to‑decision latency is your number. AI handles top‑of‑funnel evaluation; humans are the constraint in the middle. Instrument the funnel, find the queue, clear it — with agents where they work and your own judgment where they don't.
• Ownership‑program operations. Our equity is real — PIUs at $0 strike, annual tender, cash profit sharing — and real ownership needs rails people can trust: grant cycles, vesting records, tender logistics, clear communication. You build and run them.
• Company cadence, office, and vendors. The rhythms that keep 20 people coordinated without bureaucracy, plus contracts, vendors, and the physical environment — the layer every company needs, run here like a product. As this scope scales, a Workplace Operations…