Research Preview: Cross-Industry Patterns in AI Product Management
A preview of an upcoming research paper analyzing 100+ AI product launches across healthcare, fintech, edtech, and consumer tech to surface universal failure and success patterns.
Stakeholder Management for AI Products: A PM's Survival Guide
AI products have a stakeholder challenge that no PM school prepares you for. The data science team speaks a different language than engineering. The executives think AI can do everything. The users think it will take their jobs. Here is how I navigate all of it.
MLOps for Product Managers: What You Need to Know
You do not need to implement MLOps. You do need to understand it well enough to know when your engineering team is cutting corners and what it costs you. Here is the practitioner's guide for AI product managers.
Why AI Teams Need Product Managers, Not Project Managers
Most enterprise AI teams are staffed and managed like software delivery projects. This is a category error. AI product development requires a fundamentally different management model — one built around uncertainty, not milestones.
Break Into AI Product Management
A practical guide to transitioning into AI PM - what's actually different, what technical depth you need, and how to build a portfolio that gets you hired.
Building Production Agent Systems: Lessons from the Trenches
Demos of AI agents look magical. They browse the web, write code, send emails, book meetings. Production agent systems look different. They time out, get stuck in loops, call tools with malformed arguments, and confidently complete the wrong task. Here is what I have learned building them.
AI Product PRD Template: The Practitioner's Version
A PRD template built specifically for AI products — not a generic PM template with 'AI' bolted on. Includes sections for data requirements, model evaluation, failure mode mapping, and regulatory considerations.
Product Breakdown: Epic's GenAI Strategy — Why the EHR Giant Will Win the Healthcare AI Race
Epic has distribution, data, and trust. Startups have speed and innovation. Here's why distribution wins.
Vector Databases Compared: Pinecone vs Weaviate vs Chroma vs Qdrant
Pinecone, Weaviate, Chroma, and Qdrant all store and retrieve vectors — but they make very different tradeoffs on performance, cost, operational complexity, and features. Here's how to choose.
Why Domain Expertise Beats Model Performance
The AI product that wins in a competitive market isn't usually the one with the highest accuracy. It's the one that fails gracefully, with predictable failure modes that domain experts can handle. Domain expertise determines how you build for failure, and that's what users trust.
AI Product Metrics That Actually Matter: Beyond Accuracy
The most common product review question I get in AI initiatives is some version of: "What's the model accuracy?" It'
Product Metrics Dashboard Template for Enterprise AI
The Ethlore Story: Where D2C Sarees Meet AI
Ethlore is a D2C handloom saree brand I'm building with my brother. We source directly from Indian weavers, sell on Shopify, and are slowly bringing AI into inventory and marketing. Here's the honest story.
Pricing AI Products: Models That Work
AI product pricing is harder than SaaS pricing because the value delivered is variable, the cost to serve is variable, and buyers are skeptical of promises they can't verify. Here's the pricing model analysis I use when designing AI product economics.
Multimodal AI in Enterprise: Beyond Text
Most enterprise AI in 2024 was text-in, text-out. 2025 is when multimodal became practical. Vision models can read charts, identify defects, and process medical images. Here is where multimodal is actually delivering value in production.