Dr. Aki Wijesundara
Manu Jayawardana
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

Dr. Aki Wijesundara

AI Founder | Educator | Google AI Accelerator Alum

Manu Jayawardana

Manu Jayawardana

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

Previous Students from

Google
Meta
OpenAI
NVIDIA
Amazon Web Services
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