Product Manager Hub
Product leaders are making AI-era calls with recycled advice. I collect frameworks, failure patterns, and decision criteria from real practice—and make them usable through writing, ProductBot, tools, and advisory.
How to engage
Same problem—better decisions—different ways in. Learn, ask, go deeper, or connect with me.
Essays and build notes that turn industry lessons into usable judgment.
Concrete plays for AI strategy, prioritization, and decision work.
Ask grounded product questions—answers rooted in curated PM knowledge.
Bring the same library into Claude Desktop when you work day to day.
Go deeper with the full advisor and growth tools when you are ready.
Work with me directly when you need a partner on AI-era product decisions.
Quick paths
From the library
What we're collecting and sharing—strategy theory, AI judgment, and notes from building real solutions.
MCP isn't a technical detail—it's a strategic decision about whether your AI product can evolve independently of your model vendor. Here's how to think about it.
Anthropic's internal analytics went from 21% to 95% accuracy with zero model improvement. What that means for where AI moats actually live—and why you're fighting for the wrong layer.
Speed and feature parity are the trap. The moat moves toward embedded domain knowledge and workflow depth before foundation models commodify the gap.
ProductBot
ProductBot answers from curated product leadership knowledge—not generic chat. Ask about strategy, prioritization, AI decisions, or how the hub works.
FAQ
Straight answers about the hub, ProductBot, and how to get help.