The two-pass agentic engine runs an AI agent through your hypothesis twice, in strict order — first on the problem alone, then on your solution against real competitors — so the agent's judgment of the problem is captured before your product can influence it.
Why isolate the passes
Show an agent your solution immediately and its reasoning anchors to whatever you've presented — the same way a person's opinion shifts once they know what answer you're hoping for. Isolating the problem-only pass first captures the agent's unprompted criteria and deal-breakers, giving a clean baseline to measure your actual solution against.
Pass 1 — Discovery
The agent receives your problem and target only. The solution is hidden. Output: the agent's decision model — the criteria, weights, deal-breakers, and trust signals it applies to this problem and segment.
Pass 2 — Validation
The same agent now also sees your solution and a real competitor set. Output: inclusion decision, rank, recommendation, objection list, and a full reasoning trace.
What comes out the other end
- Agent-Readiness grade (A–F)
- Decision-Model map — the criteria and deal-breakers agents actually apply
- Inclusion and ranking results against real competitors
- Actionable recommendations to change how agents see your product
Ask an agent about your product directly and it'll be diplomatic. Ask it about the problem first, and you find out what it actually thinks.