Most AI tools optimize for agreement. Tenth Man optimizes for dissent.
Three agents - Strategist, Skeptic, Synthesizer - run structured adversarial analysis on your decision.
The Skeptic attacks assumptions. The Synthesizer makes a call.
Confidence is capped by what's unresolved, not by how good the answer sounds.
No chat. No "it depends." A real decision brief.

I built Tenth Man because I kept watching smart founders make bad decisions due to a lack of opposition. Every advisor in the room agreed. Every AI tool they consulted found a way to validate the plan. And there was no structural mechanism to force anyone to assume the crowd was wrong. The Tenth Man doctrine comes from military intelligence: if nine people agree, the tenth must disagree. The assumption is that consensus, by itself, is a blind spot. So I built a three-agent, three-model system where dissent is mandatory. A Strategist makes the case for action. A Skeptic attacks assumptions, incentives, and weak logic. A Synthesizer makes a call and owns the risk. Confidence is capped mechanically by what's unresolved - the system fails loudly if it tries to sound more certain than the evidence justifies. It's not a chatbot. You don't ask it questions. You submit a decision, and it tells you what you're missing. The decisions I had in mind: hiring a senior exec, raising or delaying a round, walking away from a deal, firing a co-founder. The ones where "it depends" is not an answer and the downside is real.
Really smart approach to decision-making. The three-agent structure (Strategist, Skeptic, Synthesizer) with mandatory dissent is brilliant — most AI tools just validate what you already think. The confidence capping mechanism is particularly interesting: anchoring certainty to unresolved issues rather than how convincing the output sounds. Would love to see this applied to product roadmap prioritization too.

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I built Tenth Man because I kept watching smart founders make bad decisions due to a lack of opposition. Every advisor in the room agreed. Every AI tool they consulted found a way to validate the plan. And there was no structural mechanism to force anyone to assume the crowd was wrong. The Tenth Man doctrine comes from military intelligence: if nine people agree, the tenth must disagree. The assumption is that consensus, by itself, is a blind spot. So I built a three-agent, three-model system where dissent is mandatory. A Strategist makes the case for action. A Skeptic attacks assumptions, incentives, and weak logic. A Synthesizer makes a call and owns the risk. Confidence is capped mechanically by what's unresolved - the system fails loudly if it tries to sound more certain than the evidence justifies. It's not a chatbot. You don't ask it questions. You submit a decision, and it tells you what you're missing. The decisions I had in mind: hiring a senior exec, raising or delaying a round, walking away from a deal, firing a co-founder. The ones where "it depends" is not an answer and the downside is real.
Really smart approach to decision-making. The three-agent structure (Strategist, Skeptic, Synthesizer) with mandatory dissent is brilliant — most AI tools just validate what you already think. The confidence capping mechanism is particularly interesting: anchoring certainty to unresolved issues rather than how convincing the output sounds. Would love to see this applied to product roadmap prioritization too.

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