AI prototypes are easy to applaud. Production AI is harder: it must be useful on an ordinary Tuesday, accountable when it is wrong, and economical at scale.
Start with a decision, not a model
The strongest AI products begin with a specific decision or workflow whose quality, speed or cost can be measured. “Add AI” is not a strategy. “Reduce contract review time without increasing risk” is.
Design the human boundary
Successful systems make it obvious what the AI can do, what evidence it used and when a person must intervene. Confidence comes from legible limitations—not theatrical certainty.
Good technology does not ask people to trust magic. It earns trust by making judgment visible.
Build evaluation into the product
Offline benchmarks are only the beginning. Teams need scenario libraries, quality rubrics, cost thresholds and production feedback loops that improve with real use.
Treat adoption as engineering work
AI changes roles, incentives and habits. Pair technical delivery with workflow design, enablement and clear ownership or even excellent models will become shelfware.