The Middle Layer Is the Job

With traditional software, the feasibility question — can we build this? — usually gets answered early. With AI-powered products, quality only reveals itself at scale, with the messy real-world data and edge cases your controlled test environment never surfaced. That’s a different kind of PM challenge.

Security as a Growth Decision: A Founder’s Guide to SOC 2

The question is not “if” you need to invest in security, but when and how. The timing depends entirely on which situation you’re in, what “good enough” looks like for your business, and how much time you have to get there.

The Myth of “Good Data” in AI

It’s one of the most common reasons organizations stall on AI adoption, and it’s based on a belief that is only partially true. Yes, data matters. No, you don’t need perfect data to start.

Choosing Good: Reinvesting AI-driven efficiency into better outcomes, not just faster ones

AI is reshaping the classic “fast, cheap, good” tradeoff, with most AI implementations prioritizing speed and cost. But Marc De Pape argues that the true advantage lies with those who reinvest AI-driven efficiency into better outcomes, not just faster ones.