AI Product Strategy in 2026
Moats from workflow, data, and trust—not foundation model picks. Wedge sequencing from Kaizen and Chromatics.
Read →Writing
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Not every post is equal. These are the essays and collections I'd hand a new reader — organized by theme, with the full archive at /blogs.
Reading path
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Featured
Pinned essays
Context Engineering for PMs
What to put in AI memory: canonical truth, exclusions, and freshness rules from Kaizen and Navbot.
Read →RAG vs Fine-Tuning vs Prompts
PM decision framework on data you control, change frequency, and eval pass rates.
Read →The Builder-PM Playbook
Reading code changes prioritization, scope, and engineering trust—from 863K+ downloads to 15+ products.
Read →From Demo to Production: Eval Gates
Golden sets and pass/fail thresholds before customers see AI—Navbot and AssetIQ lessons.
Read →Outcome-Driven Roadmaps
Name the number before the quarter. Every bet shows how it moves the metric—or it waits.
Read →Why Evals Are the New PRD for AI PMs in 2026
Probabilistic products need eval suites—not longer specs. Labeled test sets, rubrics, and ship gates.
Read →How to Scope AI Products That Move Revenue
Name the number before the model. Outcome-first scoping from AssetIQ and Toyota automation.
Read →Emerging Markets PM: Constraints as Moat
Offline-first, operator-heavy, margin-sensitive—why hard markets produce durable products.
Read →Product Management in Emerging Markets
Constraints as product advantage — offline-first, high-touch ops, cost sensitivity.
Read →Collections
Browse by theme
AI Product Management
Strategy, scoping, and shipping AI products that move business numbers — not just demo well.
Growth & Metrics
Outcome-first roadmaps, KPI design, and the metrics that prove product bets worked.
Emerging Markets PM
Building for real conditions — connectivity, operations, and adoption on the floor.
Product Leadership
Scope discipline, stakeholder alignment, and earning trust across eng and leadership.