90-Day AI Launch Plan

The exact checklist I use to launch production AI products in 90 days. Track your progress through discovery, build, and launch.

Your Progress

Discovery Build Launch

Discovery Phase

Days 1-30

Define business problem and success metrics

What specific outcome will this AI product deliver?

Audit existing data assets

What data do you have? What's the quality?

Identify data gaps and acquisition plan

What additional data is needed?

Technical feasibility assessment

Can this be built with current technology?

Stakeholder alignment and sign-off

Get executive buy-in and resource commitment

Define MVP scope and timeline

What's the minimum to prove value?

Build Phase

Days 31-70

Set up development environment

Infrastructure, repos, CI/CD pipelines

Data pipeline implementation

ETL/ELT, data quality checks, monitoring

Model development and training

Build, train, and validate ML models

API/integration development

How will users/systems interact with the AI?

Testing and validation

Unit tests, integration tests, model validation

Documentation

Technical docs, user guides, runbooks

Launch Phase

Days 71-90

Staging environment deployment

Deploy to staging, run final validations

User acceptance testing

Get feedback from real users

Monitoring and alerting setup

Model drift, performance, errors

Production deployment

Go live with rollback plan ready

User training and communication

Train users, announce launch

Success metrics tracking

Measure against defined KPIs

Need Help Executing This Plan?

I've used this exact framework to launch 100+ data products. The implementation guides give you the full playbook — worksheets, templates, and week-by-week roadmaps.

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