Writing / Series

Field Notes

What it actually takes to ship enterprise AI: the orchestration, the process, and the unglamorous plumbing that decides whether a model ever earns its keep.

The model is the easy part. It is one step in a system, and almost never the step that breaks. These are notes from the floor, where AI meets a real business with real constraints: legacy banking processes, back-office work nobody mapped, the gap between a clever demo and a thing that survives Monday morning.

The thread running through them: orchestration is the system. The win is in how the pieces are wired, who hands off to whom, and where human judgment sits. Read these if you build with AI for a living, not just about it.

  1. 10 min read Orchestration Is the System The model is one step. The layer that decides when the model is wrong is the product, and the real AI hire is a Chief Process Officer who speaks AI, not a CAIO.
  2. 6 min read The AI-First Company An AI-first company is not one that bought AI tools. It is one that rebuilt its org chart so an agent is the default operator of a process and a human owns the judgment call. Here is what actually changes, because I changed it in my own company first.
  3. 4 min read The AI-First Company Needed a Stand-Up I built a knowledge system with an answer for almost everything. The thing that broke wasn't the system. It was the meetings. A good memory compounds; it does not automatically keep a team talking to each other, and the gap only shows up after it costs you something.
  4. 8 min read I Engineer Illusory Truth for Machines. It's Called GEO. The rule that wins my brand work is to repeat one sentence in the same shape across enough places until a model says it back as fact. That is a named cognitive bias, run on a machine, and I bill for it. A field note on the part I cannot put down.
  5. 8 min read Your Notes Are Not the Deal I built a knowledge base for my whole company, and one night it told me two of my hottest deals were dead. It was reading file dates. The deals were alive in a chat the brain could not see. A field note on the one failure mode every self-maintained system has.
  6. 6 min read Build vs Buy vs Partner: How to Choose Your AI Delivery Model Every company reaching for AI faces the same decision: build it yourself, buy an off-the-shelf product, or partner with a specialist. Most choose wrong because they optimize for the wrong constraint. Here is the framework I use with clients.
  7. 6 min read How to Implement AI in Enterprise: A Practical Guide Most companies fail at enterprise AI not because the technology is hard, but because they skip the fundamentals. Here is the playbook I use with banks, pharma chains, and industrial operators, from first assessment to production deployment.