07/10/2026
This is a story a lot of software teams are quietly living right now.
You build a GenAI prototype. It works; actually works. Summarizes documents, answers questions, pulls data. The team is excited, leadership is excited, customers are going to love it.
Then someone asks: "Okay, but what happens when this goes to production?"
And suddenly the room gets a little quieter. What data can the model actually see? Who's on the hook if it gives a wrong answer? Can a bad actor manipulate the system prompt? What if a future version doesn't just respond; it acts?
That's the moment a lot of ISV teams realize they've been thinking about AI as a product problem, when it's actually an operational risk problem.
We wrote about how to get ahead of it: a practical AI Governance Framework that covers everything from knowing what AI you actually have running (spoiler: it's probably more than you think), to building guardrails into your architecture, to modernizing legacy platforms without blowing them up.
It's a bit of a long one, but it's the kind of read that might save your team a very stressful quarter.
👉 https://zurl.co/eBbbq