Next GTM Experiment
Give your coding agent a GTM brain.
Your agent can build anything. It just doesn't know what to build next to grow. UseCaseify GTM finds your riskiest go-to-market assumption, turns it into one executable experiment, and hands your agent the implementation — pass/fail criteria locked before you start.
Free during beta · 3 experiments a month · No credit card
From “what now?” to a running experiment.
01
Install the skill
One command adds /gtm-next-experiment and /gtm-decision to Claude Code in your repo. Codex and Cursor get a paste-in bootstrap.
02
Your agent gathers the context
It inspects your actual codebase — stack, analytics, signup flow — and asks you three questions. No forms, no crawling your site from outside.
03
One assumption, one experiment
The brain ranks your riskiest GTM assumptions and designs a single executable experiment — with continue / iterate / kill rules you lock before starting.
04
Your agent builds it
TASKS.md is a full implementation spec: scope, data, feature flag, rollback, tests, acceptance criteria. Your agent executes it in your codebase.
05
Results in, decision out
When the calendar reminder fires, run /gtm-decision. Your agent collects the numbers; you get an honest Continue / Iterate / Kill recommendation.
“Stop guessing your GTM. Test the next assumption.”
Start the first one →Everything lands in your repo, under version control.
No dashboard to babysit. Each experiment is a directory your team can read, review, and diff — and your kill criteria live in git history, where nobody can quietly rewrite them.
BRIEF.mdThe experiment explained for humans — assumption, evidence, design, risks.TASKS.mdThe implementation spec your coding agent executes, with hard scope limits.criteria.lock.jsonYour decision rules, committed to git before results exist. No moving goalposts.reminder.icsThe results day, straight onto your calendar.
Built to be honest.
GTM tools love telling you what you want to hear. This one is designed not to.
No invented numbers. Every claim is labeled: stated by you, observed in your repo, or AI inference. We never dress a guess up as market data.
Locked criteria. Continue / iterate / kill rules are hashed and frozen when you start. The database physically refuses to change them afterward.
Qualitative confidence. Decisions come with low / medium / high confidence — never fake precision. Weak data caps confidence automatically.
One experiment at a time. Not fifty marketing ideas. The single riskiest assumption, tested properly, then the next one.
You decide. The verdict is a recommendation. Override it — your reason is recorded alongside the AI's, honestly.
Every experiment can go on the public record.
Free connected experiments are preregistered on the public registry: criteria locked and timestamped before results existed, honest outcomes after — including the kills. That's the deal that builds a commons of real GTM evidence.
Browse public experiments →