

Free Lesson
Writing a PRD for a Non-Deterministic Feature
30 min
Oct 6, 2026 9:00 AM
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What you'll learn
A PRD template built for non-deterministic behavior
A spec format that assumes variable output instead of fighting it.
How to define "success" for a feature that varies output
Metrics and acceptance criteria engineering can actually test against.
What to specify for engineering that a normal PRD leaves out
Failure modes, fallbacks, and eval criteria that belong in the doc.
Why this topic matters
A standard PRD template assumes a feature behaves the same way every time. AI features don't, and PRDs written the old way leave engineering guessing about what "working" even means. This session rebuilds the PRD for that reality.
You'll learn from

Dr. Aki Wijesundara
AI Founder | Educator | Google AI Accelerator Alum

Manu Jayawardana
AI Advisor | Co-Founder & CEO at Krybe | Co-Founder of Snapdrum
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