Notes from production.
Configuration architecture, multi-agent systems, cost governance, evals, and the production assumptions that quietly stop holding when AI meets the real world.
Our AI ROI Framework
A three-part field guide for business leaders measuring AI financial impact — pilot-to-rollout adoption gaps, the ROI framework that holds up to CFO scrutiny, and the hard-vs-soft savings question. Pairs with an interactive framework.
Enterprise Agentic Configuration & Performance Assessment: Interactive Dashboard
A live, navigable view of a mid-sized enterprise assessment — current vs. optimized state, performance trajectories, scalability curves, and a 30-day action plan.
Configuration, Not Prompts: Why AI Systems That Scale Don't Hide Their Rules
The systems that work have explicit contracts. The ones that fail have hidden prompts. Most AI agents hide what they do — the ones that scale declare it.
AI Works. That's the Problem: Why Cost Control Becomes Infrastructure
AI adoption accelerates faster than cost predictability. Our experience with a few configuration classifications optimization that turned cost control into infrastructure.
Three Questions Worth Asking Your AI Team This Week
If the answers are uncomfortable, we should talk. A diagnostic for production AI eval practice.
Seven Wrong Theories
My AI debugged itself six times in a row and got it wrong every time. Can you spot the flaws before I did?
Building a Multi-Agent Compliance System
A practitioner's guide to eval-driven dev, adversarial testing and prompt engineering for high-stakes AI agents.
Tests, Evals, and the Substrate That Moves
Why production AI needs behavioral measurement, not just correctness checks.