RIGHT ENGINES
Requirements sound complete until delivery fails
A practical guide to diagnosing requirements sound complete until delivery fails and deciding whether an AI engine is justified.
The problem
Ambiguous outcomes and unstated constraints create rework, disputes, and systems that solve the wrong problem.
Symptoms
Look for recurring delay, correction, escalation, or paid attention around this workflow. Confirm the pattern with original request, stakeholders, constraints, examples, failure conditions, and decision authority. rather than relying on anecdotes.
Why it happens
Teams jump from request to specification without testing assumptions and acceptance criteria.
What it costs
Measure the burden created by requirements sound complete until delivery fails: responsible-person hours, elapsed delay, rework, error exposure, outside spend, and decisions deferred. Use a representative baseline; do not invent ROI.
What people usually try
Adding more features or producing a longer document without resolving ambiguity.
Where AI helps
For this problem, AI may help by turning original request, stakeholders, constraints, examples, failure conditions, and decision authority. into clarification questions, assumption register, scoped requirements, acceptance criteria, and change boundaries. It should preserve evidence and expose exceptions for review.
Where AI does not help
Do not automate stakeholder agreement or invent missing authority.
What an engine could do
Clarification questions, assumption register, scoped requirements, acceptance criteria, and change boundaries.
Inputs required
Original request, stakeholders, constraints, examples, failure conditions, and decision authority.
Success measures
Fewer late changes, testable acceptance, stakeholder agreement, and reduced rework.
Risks
The specific failure boundary is clear: Do not automate stakeholder agreement or invent missing authority. Also test provenance, access, false confidence, and the effect of unreliable inputs.
Small / medium / large solution
Start with the smallest validated route. Use an Outcome Kit only where its stated inputs and tests fit requirements sound complete until delivery fails; adapt a proven engine where workflow context differs; commission private work only when the evidence, integration, governance, or rights justify it.
Estimate this problem’s burden · Decide whether it is worth building for · Review reusable Outcome Kits
Published 2026-08-31 · Updated 2026-08-31 · Version 1.0