Product Strategy: Async Video Platform AI Pivot

Scenario: 6-month product roadmap for a Loom-like async video platform ($12M ARR, 2M users) pivoting to AI-powered async communication hub. Team: 12 engineers, 3 PMs, 2 designers. Key tension: improve existing video editor vs. build AI meeting summaries vs. launch team knowledge base. Board pressure to show 40% ARR growth.

Skill applied: product-strategy v1.0.0

Frameworks used:

Vision-to-Roadmap Cascade — translates the “async communication intelligence” vision into falsifiable pillars, confidence-rated bets, and quarterly milestones
Strategic Bet-Sizing — sizes three competing investments (AI Intelligence at 55%, Editor Hardening at 30%, Knowledge Base at 15%) with hypotheses, kill criteria, and portfolio balance check
Option-Value Sequencing — demonstrates why AI summaries must come before knowledge base (information-gated sequencing), with counterfactual analysis for each ordering decision
Strategic Tension Surfacing — identifies 5 tensions (growth vs. retention, platform vs. product, speed vs. quality, individual vs. team, AI cost vs. margin) with explicit resolution costs
NOT-Doing Section — 5 deprioritized items with opportunity cost assessment (mobile app, meeting bot, enterprise SSO, advanced editor, analytics dashboard)
Resource Allocation — capacity model with 70/20/10 split, per-bet allocation, over-capacity risk acknowledgment
Roadmap Communication — board deck vs. team all-hands narrative arcs

Key outputs:

Vision statement with falsification test (15% AI engagement threshold)
3 strategic bets with full hypothesis/confidence/investment/kill structure
Month-4 critical gate decision (expand knowledge base or redirect to AI iteration)
5 NOT-doing items with reconsider-if triggers
6-month gate structure with pass/marginal/fail criteria per month
4 adversarial self-critique weaknesses
Evidence summary: 23 citations, T1-T4, zero T5-T6

What the skill adds vs. generic AI: A generic prompt produces a feature list with dates. The product-strategy skill produces a decision architecture — falsifiable vision, confidence-rated bets with kill criteria, information-gated sequencing with counterfactuals, explicit tensions with named costs, and a NOT-doing section that makes deprioritization decisions transparent. The board sees bets and outcomes; the team sees milestones and gates; customer success sees capabilities and timelines — same strategy, different views.