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Two-week seeds with evals, cost caps, and kill criteria.
Shape of a seed sprint
Seed notes for early AI wedges.
Kill criteria for seeds
Seed notes for early AI wedges.
Acceptance tests for experiments
Seed notes for early AI wedges.
Cost caps in seed mode
Seed notes for early AI wedges.
Demo vs capability
Seed notes for early AI wedges.
Design partners for seeds
Seed notes for early AI wedges.
Instrument early
Seed notes for early AI wedges.
Pivot rules that are real
Seed notes for early AI wedges.
From seed to narrative
Seed notes for early AI wedges.
One-engineer seed teams
Seed notes for early AI wedges.
Scope cuts that hurt correctly
Seed notes for early AI wedges.
Eval minimums
Seed notes for early AI wedges.
Pricing hypothesis tests
Seed notes for early AI wedges.
Security minimums
Seed notes for early AI wedges.
UX spikes
Seed notes for early AI wedges.
Data minimums
Seed notes for early AI wedges.
Week-two review ritual
Seed notes for early AI wedges.
Graduate or kill
Seed notes for early AI wedges.
Choosing an AI seed wedge
Test one user job and risky assumption before committing to a full product build.
Kill criteria for AI experiments
Set a decision date, budget, quality floor and continue-change-stop rules before the demo.
A portfolio of seeds
Seed notes for early AI wedges.
Founder checklist
Seed notes for early AI wedges.
From seed to build sprint
Use evidence about user pull, workflow fit, quality and operating cost to scope the next build.