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ProductValidation

Test what could sink it.Before you write the code.

LiteSurface ranks every assumption by importance × uncertainty × cost of being wrong, then plans experiments with success and kill criteria set in advance. Outcomes update the assumption and trigger a fresh evaluation, while the earlier one stays on record.

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risk score for each assumption
I × U × C
agreed before an experiment starts
Kill criteria
from unknown to falsified
5 statuses
evaluation history
Append-only

How it works

Spend the first weekon the biggest unknown.

  1. 01

    Collect assumptions

    Assumptions come from the genome, from evaluator critiques, and from your team, gathered in one list.

  2. 02

    Rank by risk

    Each one is scored for importance, uncertainty, and cost of being wrong. The product of the three sets the order.

  3. 03

    Plan the experiment

    Generate a plan with method, success criteria, kill criteria, and timeline, then adjust it to your constraints.

  4. 04

    Record the outcome

    Log what happened. The assumption moves to supported, weakened, or falsified, and the concept is evaluated again.

Learning loop

Outcomes update the score.History stays honest.

A completed experiment becomes evidence. It changes the assumption’s status and feeds a new evaluation, which is appended beside the old one. You can always see what the system believed before the test and what changed after it.

  • Assumption statuses: unknown, testing, supported, weakened, falsified
  • A board for planned, running, complete, and abandoned experiments
  • Reminders when an experiment passes its end date
  • Learnings carry into briefs and build handoffs

Capabilities

Cheap tests,clear verdicts.

  • Risk-ranked assumptions

    Genome, AI, and manual assumptions share one ranked list, so the riskiest belief is always at the top.

  • Generated experiment plans

    Plans suggest the cheapest credible test, such as a concierge pilot, a fake-door page, interviews, or a technical spike.

  • Kill criteria up front

    Decide what failure looks like before the data arrives, so a weak result cannot be explained away.

  • Experiment board

    Track every experiment across planned, running, complete, and abandoned.

  • Reminders

    Get a nudge when an experiment runs past its timeline or an outcome is still missing.

  • Re-evaluation on outcome

    Recording a structured outcome triggers a fresh evaluation of the concept that cites the result.

What you getEvidence you made yourself.

Validation turns opinions into results you own, attached to the concept they tested.

  • A ranked list of what must be true
  • Experiment plans with success and kill criteria
  • Structured outcomes linked to assumptions
  • Statuses that reflect what you learned
  • Re-evaluations that cite experiment results
  • A validation brief ready to share

Learn cheaply nowwhat would cost you later.

Walk through the sample project’s validation plan, then plan your first experiment and watch an outcome flow back into the score.

Start freeSee a sample evaluation