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Evaluate product bets and shape pitches using Shape Up's appetite model and Bezos's Type 1/Type 2 decision framework. Use when asked to assess a product bet, evaluate initiative risk, decide resource allocation, or shape a pitch for a new feature or project.
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SOC 職業分類に基づく
Analyze competitive landscape with feature matrices, positioning maps, and strategic gap analysis. Use when asked to analyze competitors, map the competitive landscape, find differentiation, or evaluate alternatives to a product.
Design hypothesis-driven experiments and A/B tests with proper methodology. Use when asked to design an A/B test, validate a hypothesis, plan an experiment, or set up a test for a product change. Covers hypothesis writing, sample size, and common mistakes.
Prioritize features and backlog items using RICE scoring and Linear's enablers vs blockers lens. Use when asked to rank features, prioritize a backlog, decide what to build next, or evaluate feature requests against each other.
Analyze customer motivations using Jobs-to-be-Done and Forces of Progress. Use when asked about jobs-to-be-done, why customers switch products, what job a product is hired for, or when analyzing the forces that drive or resist product adoption.
Plan product launches with the right tier and coordinated checklists. Use when asked to plan a launch, coordinate a release, prepare for go-to-market, or figure out how to announce a new feature or product. Covers silent, soft, and big-bang launch tiers.
Define product metrics with a North Star, input/output tree, and counter-metrics. Use when asked to define metrics, set up measurement, choose KPIs, pick a north star metric, or build a metrics framework. Prevents vanity metrics and gaming.
| name | bet-sizing |
| description | Evaluate product bets and shape pitches using Shape Up's appetite model and Bezos's Type 1/Type 2 decision framework. Use when asked to assess a product bet, evaluate initiative risk, decide resource allocation, or shape a pitch for a new feature or project. |
Size product bets by separating reversible from irreversible decisions and shaping work to fit an appetite. Most product bets are Type 2 decisions — reversible, low-cost to try, high-cost to deliberate. Move fast on those. Save deliberation for Type 1 decisions that are hard to undo.
Type 1 (Irreversible): One-way doors. Hard to undo once committed.
Type 2 (Reversible): Two-way doors. Easy to undo or iterate.
Rule: Use lightweight process for Type 2. Use deliberate process for Type 1. Most product teams over-process Type 2 decisions and under-process Type 1 decisions.
When proposing a bet, structure it as a Shape Up pitch:
A specific story showing real pain. Not an abstract need — a concrete situation with a real user.
"When a PM finishes a customer interview, they spend 45 minutes transcribing notes into a PRD. By the time they're done, the emotional context is gone and the PRD reads like a requirements list."
How much time is this worth? Not how long it will take — how much you're willing to invest.
If you can't fit the solution in the appetite, reshape or kill it.
Breadboard-level, not pixel-perfect. Show the key interactions and flows without getting into visual design. Fat-marker sketches, flow diagrams, or written walkthroughs.
Known risks and unknowns that could blow up the timeline. For each: what's the risk and how will you mitigate it?
What's explicitly excluded. This is as important as what's included — it prevents scope creep during execution.
For larger bets, estimate expected value:
EV = (Upside x P(success)) - (Downside x P(failure)) + Learning Value
Built on Shape Up (Basecamp) and Jeff Bezos's Type 1/Type 2 decision framework. Skills from productskills.
