Golden Paths for Machines
A golden path built for humans is a recommendation. A golden path built for a machine has to be an interface.
Field Notes
Writing on architecture, AI, and transformation, and the judgment required when systems stop behaving as expected.
A golden path built for humans is a recommendation. A golden path built for a machine has to be an interface.
A platform team that rules by doctrine gets compliance. A platform team that runs like a product gets adoption. Only one of those is worth anything.
A platform team is not a cost centre. It changes the marginal cost of safe change, and that is an economic argument, not a tooling one.
AI will make some teams smaller. It will not make the work lighter.
The next phase of AI-assisted engineering will not be more magical. It will be more explicit.
Agentic engineering is not the art of asking AI to do more. It is the discipline of making work explicit enough that machines can safely help with it.
The value of a platform is not the tooling. It is the organisational friction it makes unnecessary. Platform engineering is easy to justify badly. A team builds an
"Human oversight" is doing a lot of work in AI architecture diagrams. Too much, I think. It usually shows up as a reassuring little box near
Event contracts used to be guidance. With agents on the other end, they're the thing the system actually runs on.
The real architectural decision isn't how fast you process data. It's what you choose to treat as a fact, and whether the machines around it can reason about those facts without asking permission.
Why it is no longer just infrastructure For a long time, the data platform was treated as a supporting layer. A place where data was collected, transformed, stored,
A few years ago, most engineering organizations were constrained by the same thing: writing code was expensive. Not just in budget terms. Expensive in attention. In coordination. In
There’s a particular kind of frustration engineers know well: you pick up a Jira ticket and the description reads something like “Fix the thing from the meeting.” No context. No requirements/details.
Why the gap between delivery and value is rarely a technical problem, and what it actually takes to close it.
How GitHub Agentic Workflows + MCP turned my pull request reviews from context-switching nightmares into fully-loaded briefings
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