"The more you add, the more you're taking away. Know when you need to stop."
A working document. Not a portfolio, not a blog. Practitioner notes from inside.
One operator. One codebase. One operating system that boots in seconds and maintains state across sessions. 26 years of digital craft compressed into infrastructure that makes a solo practitioner move at the speed of a team.
This is the practice of building with AI from the inside. Not tips. Not tutorials. The actual work — documented as it happens, proven by the commit history, refined by the corrections.
The model is a commodity. The situation is the edge.
Working notes and the daily argument: @tonycooperuk →
Operators on X keep saying they're four turns into an AI session and the context window's full. The replies miss the actual problem — they've been taught the wrong physics.
Every few weeks someone on X burns through their AI allowance in two turns and blames the model. The model is fine. They're paying for synthesis they could have externalised — and context discipline is the entire skill.
Government departments are funded to collect data, not to present it. The gap between what the state holds and what an ordinary person can use is structural, durable, and almost entirely unclaimed.
Suppliers with APIs get wired into the pipeline. Suppliers still emailing CSV files get checked when someone remembers. Not preference. Physics.
Prompt engineering is the wrong name. Context engineering — what I've been calling ingeniculture for a year — is the practice of building the room the LLM stands in.
Most AI workflows are prompts applied to empty rooms. This is what an operating system looks like instead — document tiers, named characters, a wiki the model can read, and a boot sequence that loads context before the first prompt arrives.
The AI reflects whatever substrate it meets. The dangerous case isn't where it refuses to answer. It's where it answers fluently and nobody in the room can tell it's wrong.
Every profession that charges for opaque expertise is about to discover the trail was always there. AI doesn't invent evidence — it surfaces what's already readable. The age of 'we did the work, trust us' is ending.
I'd never heard of grep and I've been building websites for twenty-six years. It turns out the simplest operation in computing — searching your own content — is the one most platforms make impossible.
I fed the same article to four frontier AI models. Three returned confident summaries — of articles I hadn't written. They didn't misread the content. They didn't know who I was. The insight that survived had vocabulary with no escape route.
I served every client in a single morning, and somewhere around the third one I realised I hadn't opened a browser. The speed wasn't the point — it was what I could see when the walls between my data sources came down.