AI PM Guiding Principles
AI Product Management is as much Art as it is Science 🔥
Image: Banana / Plant / Flask by Max Gruber
Most AI products fail—not because the models are bad, but due to a few hard truths that product teams ignore.
I’m excited to share the guiding principles that have helped my team stay on track in the ever-evolving chaos of AI product development.
#DoMore
Guiding Principles
↳ Fall in love with the problem, not the technology.
↳ Be curious about orchestration—ask the right questions, not just the easy ones.
↳ Own the vision, the execution, and the responsibility—hold everyone accountable.
↳ Prioritize using data, value, effort, strategy, and pain points—but don’t ignore your gut.
↳ Measure outcomes, not outputs.
↳ Don’t start with features—start with OKRs.
↳ Don’t start with models—start with data.
↳ Design AI responsibly, with a human-in-the-loop.
↳ Above all else, prioritize the customer.
↳ Iterate, experiment, fail fast, and respond strongly after learning from failure.
↳ Have a bias to action—don’t wait for perfect info to inform decision-making.
↳ Shared success is the best success.
↳ Strategize and plan wisely, but don’t spend your whole life in JIRA.
↳ And most importantly—make time for deep thinking—recommend at least an hour every week.
AI is evolving fast, but the principles of great product management remain the same.
Next week I’ll be "delve-ing deep" into each topic—stay tuned!
