Abstract Learning Playbooks

AI MVP

Validate an idea by creating app, initial traffic and commercial feedback.

Direct answer

Use this playbook to validate an idea with a navigable app, offer page, first creatives and feedback or lead capture.

PrismaMarketing
AI MVP LoopHipotese validada

MVP validation

hipotese em teste

Prisma

Supabase

Marketing

1

Briefing

problema e publico

2

Build

preview navegavel

3

Publicar

URL de teste

AI MVP LoopHipotese validada

MVP validation

Prisma gera app, publica oferta e mede sinais de demanda

hipotese em teste

Prisma

app funcional

Supabase

dados reais

Marketing

sinais

Preview do MVP

app publicado recebe sinais de uso real

CRM imobiliario

preview /imob-crm

live

Tabela leads

Supabase conectado

64

Iteracao v3

ajuste no onboarding

+21%
1

Briefing

problema e publico

2

Build

preview navegavel

3

Publicar

URL de teste

4

Medir

cadastros e uso

project: mvp-crm

publish: preview publico

learn: ajustar roadmap

Usuarios

64

Interesse

21%

Iteracoes

3

The animated mockup shows the MVP starting in Prisma Studio, gaining an auditable offer and receiving demand signals in the CRM.

Playbook outcome

An MVP with the right template, planned scope, generated app, connected data and first reviewable publication.

Execution route

1

Choose template

2

Plan scope

3

Generate app

4

Connect data

5

Publish and audit

Application checklist

  • Describe the problem, audience and main MVP action
  • Create a navigable app with AI in Prisma Studio
  • Audit the offer page and prepare content for search
  • Publish creatives and measure real interest in CRM

Metrics to track

  • Time until the first navigable prototype
  • Clicks and responses on the offer page
  • Qualified leads or feedback received
  • Main objections before investing in development

Does this playbook replace customer research?

No. It creates an MVP and a validation route so you can talk to real users earlier.

Do I need to publish the final app?

Not necessarily. The initial goal is to measure interest and learn before turning the MVP into a full product.