Category: Early-Stage Validation
Assumption Mapping: David Bland's 2×2 for Deciding What to Test First
Assumption mapping is the workshop discipline that tells a product team which assumption to test first. David Bland and Alex Osterwalder's 2×2 — importance × evidence — surfaces the 'leap of faith' assumptions that belong at the top of the discovery queue. In 2026, when building is nearly free, assumption mapping is the single highest-leverage hour a product team spends each quarter.
Early-Stage Product Validation: Seven Thinking Tools for 'Should This Idea Even Ship?'
Seven thinking tools for the stage before product-market fit — the stage where the honest answer to 'should this idea ship at all?' is usually no, or not yet, or not in this form. Problem-solution fit, riskiest assumption tests, assumption mapping, the Mom Test, MVP vs MLP vs MVA, Proof of Usefulness, and PMF measurement itself. Each framework answers a different question; sometimes the answer is 'stop validating and ship', sometimes it's 'stop building and listen'. This directory is for product leaders deciding which lens to pick up.
MVP vs MLP vs MVA: Minimum Viable, Lovable, or Awesome?
MVP, MLP, or MVA? Frank Robinson's Minimum Viable Product was designed to learn, not ship. Brian de Haaff's Minimum Lovable Product added an emotional bar. Minimum Viable Awesome (or Minimum Awesome Product) argues that in 2026 'minimum' is the wrong target entirely. When building is nearly free, the only defensible goal is magnificent in at least one dimension — your crown jewel.
Problem-Solution Fit: The Stage Before PMF (And Why It Matters More Now)
Problem-solution fit is the stage before product-market fit — the one where you prove the problem is worth solving before you spend a penny on building a solution. In the AI era, when building is nearly free, problem-solution fit is the only discipline that stops teams from shipping ten wrong products in the time it used to take to ship one.
Product-Market Fit: How to Measure It Honestly (Ellis, Vohra, Rachleff)
Product-market fit is the only milestone that matters for an early-stage product. AI has collapsed the cost of building, so measuring PMF — using Sean Ellis's 40% test, the Rahul Vohra Superhuman engine, and retention cohorts — now matters more, not less. Here's how to measure it honestly, diagnose fake PMF from a board seat, and allocate a minimum viable team to hunt it down.
Proof of Usefulness: A Weighted Scorecard for Early-Stage Ideas
Proof of Usefulness is a weighted scorecard from HackerNoon (April 2026) that rates early-stage products on real-world utility, traction, reach, technical stability, timing, and completeness. It's not a canonical framework yet — but the weight distribution is a genuinely useful lens for boards and founders asking whether an early-stage bet is real or theatre. Here's how to borrow what works without swallowing it whole.
Riskiest Assumption Test (RAT): Testing What Could Kill Your Product First
A Riskiest Assumption Test (RAT) is the smallest possible experiment that can prove or kill the assumption most likely to sink your early-stage product. Rik Higham coined the term in 2016 as a corrective to the abuse of MVP. In 2026, when building is nearly free, the RAT is arguably the only unit of early-stage work worth funding.
The Mom Test: Customer Interviews That Don't Lie to You
Rob Fitzpatrick's The Mom Test (2013) is the canonical playbook for customer interviews that produce signal rather than polite lies. Talk about their life, not your idea. Ask about specific past behaviour, not hypothetical future intent. Extract commitment, not compliments. In 2026, when building is nearly free, Mom Test discipline is the single biggest separator of teams that find real products from teams that don't.