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Product thinking (JTBD · PMF · OKR · discovery)

Think in value, not features: user jobs, product/market fit, goals and experiments.

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$ Objective: Newcomers quickly grasp the knowledge base's value. KR1: activatio…

Essence

Product thinking is the habit of thinking in user value and problems, not features and wishes. The shift: not "what to build" but "what user job we solve and whether it's worth solving". An antidote to the feature factory.

JTBD

A user "hires" a product for a job. Look at the task, not the feature ("people don't want a drill, they want a hole" — really a shelf). Pair with the Value Proposition Canvas.

Problem/Solution fit → PMF

First confirm the problem is real and the solution removes it; then PMF — the market needs it (people return, pay, refer; Sean Ellis test ≥40% "very disappointed if it went away").

Dual-track

Discovery ("what & why" — hypotheses, interviews, experiments) parallel to Delivery ("how"). Loop: hypothesis → experiment → metric → conclusion.

OKR

An ambitious Objective + 3–5 measurable Key Results. Focus on outcome, not output.

Example OKR

Objective: Newcomers quickly grasp the knowledge base's value.
KR1: activation 40% → 60%. KR2: time-to-value 5 min → 90s. KR3: D7 retention 18% → 30%.
These are outcomes, not "ship onboarding + 3 tutorials". Score 0.0–1.0 per KR; ~0.7 is a healthy ambitious result.

When to use

JTBD/VPC on discovery; PMF before scaling; dual-track always; OKR for quarterly focus.

Pitfalls

Solution before problem; OKR as a task list; scaling without PMF; box-ticking discovery; the feature factory.

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