Product Decisions

Articles on how to document findings after tests and make further product decisions under uncertainty. This category helps teams choose between iteration, retesting, changing the hypothesis, or abandoning an idea.

A hiring manager reviewing a confidential executive search plan for a VP replacement
Product Decisions

The Stealth Search Trap: Why Quietly Replacing a VP Usually Backfires

A stealth search sounds like the responsible move — quietly line up a replacement before anyone gets hurt, keep the team steady, avoid the drama of an open opening. Then the LinkedIn headline gets noticed, the candidate pool turns out to be three people your board already knew, and the VP you were trying to protect finds out anyway. What looked like discretion turns into the worst version of both an open search and a secret one.

Product team reviewing market signals and deciding which ideas fit their center
Product Decisions

The Center Test: A Practical Way to Decide What Your Product Team Keeps, Kills, or Retests

Every founder eventually hits the same wall: too many signals, too little certainty, and a backlog full of ideas that all sound plausible. The instinct is to ask “what should we build next?” But there’s a sharper question hiding underneath it — one that Columbia Business School strategist Rita McGrath puts to CEOs before they touch a roadmap at all: what is this company actually centered on?

A product team discussing test results on a whiteboard, using psychological safety to surface doubts and improve the product decision
Product Decisions

The Silence Before the Bad Decision

A founder runs a two-week test on a new onboarding flow. The numbers come back mixed — engagement up slightly, but a handful of users seem confused. In the debrief, one product manager wants to ship it. Another has doubts but says nothing, because the last time she pushed back, the conversation got tense and nothing changed anyway. The team ships. Three months later, they’re trying to figure out why adoption stalled — and nobody remembers that someone already saw it coming.

A product team debating an AI adoption decision with notes, laptops, and a whiteboard sketch of a test plan
Product Decisions

The AI Decision No One Should Skip: Bet, Test, or Wait?

A founder message a colleague forwarded me recently read something like: “Everyone on the leadership team wants an answer by Friday — do we buy the AI thing or not?” The question sounds simple. It isn’t. Buried inside “should we buy AI” are at least three separate decisions: how much money to risk, how fast to move, and how prepared your organization actually is to use what it buys. Treating those as one binary choice — all in or nothing — is how good teams end up either overpaying for tools they outgrow in months or watching competitors pull ahead while they wait for a “clear winner” that may never arrive.

Two product team members review customer interview notes and market signals to judge the founder credibility behind an experiment
Product Decisions

The Evidence You Forgot to Collect: Yourself

When an early product test comes back with a promising number — a waitlist that fills up, a pilot customer who says yes, a demo that gets forwarded around — most teams ask one question: is this signal real? Almost nobody asks the second, equally important question: are we the kind of team that should trust this signal enough to act on it?

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