A working journal, writtenarguedsketchedin the open.
The Journal is written by the people who deliver the work — not by a content team and not by a model. Field notes from engagements we are mid-flight on, opinions formed by being wrong about things, and the occasional argument with a fashionable idea. We publish when there is something useful to say. Sometimes that is monthly. Sometimes it is not.
The most recent piece, written this month.
Why most enterprise AI pilots never reach production — and the four conditions that change that.
Eighteen months of pilot work across three sectors taught us that the gap between a working demo and a deployed system is not a technical gap. It is an organisational one. Here is what we have learned to look for before we agree to build.
Pieces worth going back to.
The case for retrieval-first architectures over fine-tuning, in seven failed projects.
Fine-tuning a frontier model looks like the obvious move when the demo data is yours. It almost never is. A note from the engineering bench on why we keep reaching for retrieval, what fine-tuning is actually good for, and the projects that taught us the difference.
Boards have stopped asking what AI is. They are starting to ask better questions.
A shift in the conversations we have been having in board rooms this year. The interesting boards are no longer asking what artificial intelligence can do. They are asking what it should be allowed to do, and on whose authority.
The Journal does not run on a content calendar. We publish when a piece of work has produced a finding the rest of the practice wants to share — and when the client has agreed to the framing. Some quarters that means three pieces. Some quarters it means one. We have never published filler and we do not intend to start.
If you would like to be told when something new goes up, the most reliable way is to ask. There is no newsletter, no opt-in, no automated drip. A senior at the firm will add you to a short list and email you a link the day a piece publishes.
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