How to Build AI Product Strategy (By OpenAI’s Product Lead)
Author: Miqdad Jaffer — Product Lead @ OpenAI, EIR @ Product Faculty Publication: The VC Corner (100K subscribers) Date: August 26, 2025
Note: Full article is behind a paid subscription wall. Summary below is from public excerpt.
Build AI products that scale profitably, retain users, and defend against commoditization.
Overview
Miqdad Jaffer (Product Lead at OpenAI) outlines a 4-part framework for AI product strategy. The core thesis: in every technology wave, there are two types of founders — those who ride the hype and get crushed under their own costs, and those who turn the wave into a moat and dominate a market for a decade.
The 4-Part Framework
The article promises a framework covering:
- Scalable profitability — don’t burn money on inference; design for unit economics
- User retention — AI products that users come back to (not just try once)
- Defensibility — moats against commoditization (LLM prices keep dropping)
- Strategy that compounds — building on your own data, network effects, and workflows
Key Takeaways (from excerpt)
- “In every wave of technology, there are two types of founders: Those who ride the hype and get crushed under their own costs. Those who turn the wave into a moat and dominate a market for a decade.”
- Written by someone who lives this daily as OpenAI’s Product Lead
- Published on The VC Corner (100K subscriber newsletter)