Enterprise RAG Architecture Guide
Vendor Evaluation Framework for AI/ML Platforms
Most vendor evaluations for AI/ML platforms are theater. You run a demo on clean data, get impressive benchmark numbers, and then spend six months post-procurement discovering all the things that don't work. Here's how to run an evaluation that actually predicts production performance.
AWS HealthLake vs. Google Cloud Healthcare API: Building Healthcare Data Platforms
If you're building a healthcare data platform today, you're almost certainly choosing between AWS and Google Cloud as your foundation. Both
The AI Product Manager's Toolkit: 10 Frameworks That Work Across Industries
After building AI products across healthcare, edtech, and CPG, I've distilled the frameworks that actually survive contact with real organizations. These 10 tools work regardless of industry — because the hard problems in AI product management are fundamentally the same.
RICE for AI: Modified Prioritization Framework
Standard RICE doesn't work for AI products because 'confidence' means something different when a model is involved. Here's the modified version I use across healthcare, fintech, and consumer AI.
User Research for AI Products: What Changes
Standard user research methods mostly apply to AI products, but several things are different enough to matter: users can't articulate what they want from AI outputs they've never seen, trust is dynamic not static, and prototype testing with static mockups misses the core AI interaction.
AI Vendor Evaluation Scorecard for Life Sciences & Healthcare
AI Product Metrics That Actually Matter
Accuracy is not a product metric. It tells you how your model performs on a test set. It doesn't tell you whether users trust it, whether it changes behavior, or whether it creates business value. Here's the metric stack I actually use.
AI Product Management Interview Prep: 50 Questions You'll Actually Get Asked
AI product management roles are among the fastest-growing and most competitive PM positions in the market right now. They are also among the most distinctly
Build vs Buy Matrix for AI Products: The Complete Framework
Stop treating build vs buy as a binary. There are 4 options, 6 decision axes, and a set of hidden costs most teams discover too late. Here's the complete framework.
Understanding AI Inference Costs at Scale
At low volumes, AI inference costs are invisible. At scale, they become the biggest line item in your infrastructure budget. The cost levers — token economics, batching, caching, distillation — can reduce costs by 80% without sacrificing quality.
From Enterprise PM to AI PM: A Career Transition Guide
When I transitioned from engagement management at HCLTech into an AI product role, I did not have a computer science degree, I had never trained
AI Product Roadmap Prioritization: Beyond RICE
RICE works fine when you know what you're building. AI products break that assumption constantly. Here's how I've adapted roadmap prioritization for the realities of probabilistic outputs, model drift, and shifting accuracy benchmarks.
Transformer Architectures Explained for Product People
Transformers are the engine inside every large language model you're building on. Understanding how they actually work changes how you scope features, set expectations, and make architectural decisions.
AI Product Manager Interview Guide: 50 Questions You'll Actually Get Asked
50 real AI PM interview questions organized by category — product sense, technical depth, AI/ML specific, stakeholder management, and case studies. With frameworks for answering each one.