Code is cheap. Clarity isn't. Thesis versions your product context, surfaces blind spots, locks every bet with an exit condition, and scores it against what shipped.
Thesis versions your product context like code. Every AI bet is derived from the current snapshot — and stays explainable against the one that existed when you made the call.
models change monthly · your decision record shouldn't reset with them
Teams build for the loudest voice, not the clearest evidence.
Tactical calls pile up until the roadmap no longer ladders to the strategy — and nobody notices.
Nothing you shipped last quarter changes how you decide this quarter.
The evidence already exists. It's just scattered across eight tools and nobody's job to connect.
"A team that cannot answer 'under what circumstances would we conclude this was the wrong bet?' has not made a decision. They've made a hope."
Passive feedback is product analytics — adoption, task completion, retention.
Passive feedback is outcome analytics — delivery rate, escalation rate, cost-per-outcome.
Interviews, tickets, surveys, sales calls — identical in both eras. One loop serves both.
Thesis plugs into the tools you already use and turns your team's product decisions into a system of record. You keep your process. You get three things back that get sharper every quarter.
Every decision is locked with a measurable objective and an honest kill-condition — and calibrated against your team's real track record. Overconfident calls get flagged before you sink a quarter into them.
Teams using exit conditions save 8–12 engineering weeks a quarter on bets that should have been killed earlier.
Thesis reads across your CRM, support, analytics, and calls to find the evidence your roadmap is missing. Convergence across four independent lenses tells you what's real signal versus what's just the loudest voice.
Detection is tuned to your org's history — not a generic rulebook — so the findings get more accurate the longer you use it.
Every ticket carries its evidence. Every quarter, you can answer: what did we bet, what did we assume, what happened, and what did we learn? Strategy stops being a slide and starts being a ledger.
your data stays in your workspace · aggregate benchmarks are opt-in
| Thesis | Conf | Brier | Status |
|---|---|---|---|
| SSO for mid-market | 80% | 0.04 | HIT |
| Mobile companion app | 70% | 0.49 | MISS |
| Usage-based pricing tier | 60% | 0.16 | HIT |
Linear tracks the work. Mixpanel tracks the usage. Thesis tracks the decisions.