Questions
Questions buyers ask before they spend
The questions that come up before a build, an AI project or a migration gets approved — each with the short answer first, and the reasoning one click away.
Should we buy off-the-shelf software or build our own?
Buy or configure when you need it running in weeks, the problem is common, and a good-enough answer fast wins the business case. Build where accuracy, explainability or audit requirements demand control a product can't give you. Most projects are a blend: configure a platform for the fast 80%, build only the rest.
What should we ask before approving an AI project?
Six questions: where each answer comes from, what happens when the system doesn't know, how you'll prove it improved, which guardrails specifically, whether a decision can be reconstructed months later, and why the build/buy split is what it is. A vendor who gets vaguer as you go down the list has told you what you need to know.
Where do we start an Azure migration?
With a readiness assessment, not the move: what you have and what depends on what; which workloads to modernize, lift-and-shift or retire; where the sensitive data sits; what it costs now and should cost after; and the order of steps, with a way back. Lift-and-shift alone rarely saves money; the savings come from modernizing what you moved.
How do we know our AI is actually getting better?
Measure it. Keep a fixed golden set of real questions with their expected answers and sources, score every change against it, block any answer that cites no source, and watch how often the system says it can't answer in production, as an early sign that something drifted.