The article argues that AI is collapsing traditional product org roles into lean, fast-learning teams.
Outline
- Introduction: The Relay Race is Over
- Old model: Product development as a relay (research → design → engineering → PM).
- Problem: Handoffs dropped the baton; slow, disconnected, customer left waiting.
- AI’s impact: Ends the relay, enables collision—small, cross-functional teams learn and ship fast.
- The Four Collapses
- Discovery → Delivery: LLMs and synthetic data blur the line between ideation and working prototypes.“The demo is the research.”
- Research → Telemetry: Experiments replace surveys; data and logs drive learning.“Questions turn into dashboards.”
- Design → Code: Designers build testable flows; engineers focus on performance, not pixels.“Design and engineering stop orbiting separately.”
- PM → Market: Planning and building merge; focus on impact, not process.“The plan is short because the loop is fast.”
- The New Product Unit
- Roles collapse into:
- Systems Designer (flow, prompts, demo)
- Product Engineer (runtime, safety, scale)
- Model (LLM suite: generates, critiques, enforces style)
- Leadership’s job: Accelerate learning, not just set strategy.
- Weekly Operating Cadence
- Monday: Ship change to cohort
- Tuesday: Review metrics
- Wednesday: Demo, decide (double-down, pivot, delete)
- Thursday: Apply learnings, expand if signal is strong
- Friday: One-slide recap (beliefs, learnings, next steps)“This is how you learn in weeks what used to take quarters.”
- Leadership Upgrade
- Directors: Measured by speed of learning and killing bad ideas.
- Principal ICs: Guardians of system defaults and resilience.
- The Artifact Stack
- What matters: Demo, guardrail spec, one key metric, 30/60/90 plan.“Everything else is noise.”
- Why Teams Got Smaller
- Not anti-headcount; smaller teams learn faster, and AI rewards speed of learning.“Ship. Measure. Decide. That’s the job now.”
Summary
AI has fundamentally changed how product organizations operate. Instead of siloed roles and slow handoffs, the best teams now work as small, cross-functional units where learning and shipping happen almost simultaneously. Traditional boundaries—between research, design, engineering, and product management—are collapsing. The new model values speed to learning, rapid iteration, and ruthless focus on what actually improves users’ lives. Leadership is now about accelerating this cycle, not just setting strategy. The only artifacts that matter are those that drive learning and decision-making. In this new world, teams are smaller not because of cost-cutting, but because learning compounds—and AI pays interest to those who learn fastest.
