Where platform strategy meets reality

TL;DR: AI query logs inside your enterprise tools are capturing real product feedback at the point of friction. The problem is your vendor probably has that data and you don't, and neither side has worked out how to share it.If this kind of practitioner-level product thinking is useful, the newsletter is where I work through the patterns I'm noticing across enterprise technology.

TL;DR: Most AI governance responses are missing two specific gaps: the contract you signed predates the platform you’re now running, and the binary approved/not approved model doesn’t fit an environment where AI is embedded across the stack at varying levels of risk. Both are fixable.

TL;DR: AI belongs in support models. The front-end case is real and the economics make sense.

TL;DR: AI is already inside most organisations, whether through vendor tools, employee habits, or leadership pressure. The real issue now is not whether to allow it, but how to identify where it is, what it is touching, and how to govern it without slowing the business down.If this piece resonated, share it with someone who is already trying to work out where AI is showing up inside their organisation.

TL;DR: OpenAI built the most recognised AI product in the world. Then spent 2025 launching video, hardware, a browser, shopping, and ads in what looked like an ecosystem play but felt more like building to be seen building.

TL;DR: Enterprise marketplaces vet apps at the point of entry. What happens after listing depends largely on the developer.