Phase 1: Client Discovery & Problem Decomposition · 55 min · Python · Markdown

Discovery Methodology & Stakeholder Interviews

The real problem is never the stated problem.

What you will learn

Structure a client discovery session: stakeholder interviews, workflow observation, data audit
Conduct stakeholder interviews that uncover the real problem vs. the stated problem
Perform a data audit: what data exists, where it lives, what shape it's in, compliance constraints
Document discovery findings in a structured format for downstream spec writing

Objective

What you'll learn

This lesson takes approximately 55 min. By the end, you will be able to:

Structure a client discovery session: stakeholder interviews, workflow observation, data audit
Conduct stakeholder interviews that uncover the real problem vs. the stated problem
Perform a data audit: what data exists, where it lives, what shape it's in, compliance constraints
Document discovery findings in a structured format for downstream spec writing

The Problem

The most expensive mistake in enterprise AI is building the wrong thing. Discovery is the phase where you prevent that — but most engineers treat it as a box to check. A good discovery phase takes 1-2 weeks, involves structured stakeholder interviews, and produces a problem decomposition that the entire team builds against. Skip it, and you'll spend 4-6 weeks building something the client doesn't want.

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