Practical thinking on AI strategy, engineering, and adoption — written by people who build this for a living.
After 50+ deployments, we've identified the exact inflection point where promising pilots stall. Spoiler: it's rarely the model. It's almost always the people and the process.
The choice isn't technical — it's operational. Here's how to decide without getting lost in benchmarks.
How to frame value in terms that land beyond the tech team — and what metrics actually hold up to scrutiny.
Technical success means nothing if no one uses the system. Here's the adoption framework we've refined across projects.
Production AI isn't about peak performance — it's about what happens when the edge cases arrive. Which they will.
High trust, flat hierarchies, and strong data infrastructure. The structural advantages are real — if you know how to use them.