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Shift23

Build the future · Strategy · 2–3 weeks

Discovery Sprints

Validate problem, solution, pricing, demand and messaging with fast experiments.

A Discovery Sprint is a 2 to 3 week cycle to validate a bet before writing code. Shift23 tests the riskiest hypotheses about problem, solution, pricing, demand and messaging with interviews and fast experiments, and at the end you have evidence to decide whether to go, adjust or stop.

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Who it's for

For teams with a new bet who want to know if it's worth it before writing code.

It makes sense when

  • There is a new bet and the temptation to start by building.
  • The team disagrees on the problem, the audience or the price.
  • There isn't enough evidence to ask for budget or investment for the bet.

What you get

  • Key hypotheses tested

    The riskiest assumptions behind the bet, tested with fast experiments.

  • User interviews and tests

    Conversations and tests with the target audience, with the learnings organized.

  • A go, adjust or stop decision

    A clear recommendation, backed by the evidence collected.

How it works

Duration: 2–3 weeks

  1. 01

    Hypotheses

    We list the assumptions behind the bet and pick the riskiest.

  2. 02

    Experiments

    We run interviews, prototypes, and demand and pricing tests.

  3. 03

    Decision

    We consolidate the evidence and recommend going, adjusting or stopping.

Proof

Founder's track record

Frete.com: 73% of experiments validated and 3x freight postings per customer.

Frequently asked questions

What does a Discovery Sprint test?

The riskiest hypotheses behind the bet: whether the problem exists, whether the solution solves it, what people would pay, whether there is demand and which message works.

What if the answer is to stop?

Stopping early is a result too. You save the cost of building something the market didn't ask for and free the team for the next bet.

Related services

  • Zero to MVP

    Minimal scope, built with tests and documented decisions, and analytics from day one.

  • AI products & agents

    LLM features, RAG and agents, evaluated for quality and cost before scaling.

  • Innovation program

    A thesis, a portfolio of bets, PoCs with kill criteria and startup partnerships.

Talk directly with Evandro.

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