AI Wrote the PRD. You're Still Accountable for It.
Seven pages out of the model in minutes. Formatted, confident, and not necessarily right.
Advaita Nigudkar has spent eight years at BILL and helped launch the company's first agentic AI platform, in a category where a wrong number means somebody's money moved. She sits down with Rina Alexin to talk about the context work that makes AI output usable, using an LLM as a judge to hold a quality bar across growing teams, and the one PM quality she thinks AI can quietly take from you.
Key Topics Discussed in This Episode
Garbage in, garbage out is now a job description
One-line prompts produce PRDs that solve the admin use case and ignore everyone else. Advaita's team built templates and skills that interrogate the PM first: which customer, which SKU, which partner type.
An LLM as your PRD judge
Feed the model your best past PRDs as the gold standard and let it flag what's missing. The PM supplies the substance. The model finesses it. Consistency survives headcount growth and churn.
The trust feature you hope nobody opens
BILL's agents move money, so the team shipped an activity log and on/off controls. Engagement dropped once customers trusted it. That was the point.
Why Listen to This Episode?
In this episode, you'll get:
The context you have to supply before AI is useful: personas, permissions, business types, historical decisions
Plus the warning Advaita gives every PM who gets comfortable with easy answers.
Related Resources
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