
Insights
Practical notes on enterprise AI
Field notes from the work — what actually ships, what doesn't, and why. No hype.
April 15, 20267 min readAI strategyEnterpriseDelivery
How to scope an AI proof-of-concept that actually ships
Most enterprise AI POCs fail not on the model — they fail at the boundaries. Here's the scoping discipline that separates pilots that survive from pilots that die in the lab.
April 8, 20269 min readLLMArchitectureCost
Choosing the right LLM for enterprise workflows
GPT-class isn't always the answer. We walk through the decision matrix we actually use — closed vs. open-weight, hosted vs. private, and how to think about cost, latency, and risk together.
March 29, 20266 min readAI strategyCostOperations
The hidden costs of AI adoption (and how to budget for them)
Inference is rarely the biggest line item. Eval infra, human review, vector storage, and observability are where AI projects quietly burn budget — here's how to plan for it.