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Diverge Before You Deliver: AI Outcomes for PMs and Design

Hosted by Jason Prunty

Wed, Sep 23, 2026

4:00 PM UTC (30 minutes)

Virtual (Zoom)

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AI Instruction Sets for Product Managers and Designers
Jason Prunty
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What you'll learn

Tell a prompt library from an instruction set

One is retrieval; you have to remember. The other is standing context that shapes every draft before you type.

See the same task run with and without standards

One spec, two setups, both asked for four options. Judge the difference yourself instead of taking my word for it.

Build your instruction set from work you've already done

Ask two real threads how you worked, and it hands back candidate standards for you to sort.

Why this topic matters

A polished first draft is the expensive kind. It reads fine, so you send it, and the assumption nobody named comes back as rework. You don't lose an afternoon, you lose a sprint. Saved prompts only help on the days you remember them. Standing context sits under every draft. I'll run one task with it and without, and you'll leave with a scaffold for your own.

You'll learn from

Jason Prunty

Product design leader, UX professor, writes Designing Intelligence.

I have led product and design for fifteen years at SigFig, Envestnet Trust Services Exchange, and Billtrust, and taught design and UX for close to twenty at Thomas Jefferson University and CCNY. Most recently I taught AI practice to MFA students at the School of Visual Arts.

Most people teaching AI workflow arrive from engineering. I arrive from design, which means I care less about what the model can do and more about where your judgment enters the work.

I build in this space as well as teach it. My latest product, isthisoriginal.com, checks whether an argument is genuinely new or already in circulation. I write Designing Intelligence, on how human and machine intelligence develop together, and run withMission.tech.

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