infrastructure
11 essays on this topic.
- The One Env Var That Cost a Day
ANTHROPIC_API_KEY vs ANTHROPIC_AUTH_TOKEN — how a single wrong environment variable made an AI coding pipeline silently fail for hours, and the debugging journey that found it.
- The dispatch layer was eating the quality, not the model
We blamed the LLM for a 54% task failure rate. The real culprit was seven layers of dispatch infrastructure between intent and execution.
- The Lamp That Knows You
Disaster recovery for an AI-native workflow isn't about servers — it's about restoring a relationship.
- What it actually takes to run an AI agent in a bank
The resistance to AI agents in banking isn't mostly cultural. It's infrastructure — and the gap is more interesting than the politics.
- Skills as Files
The simplest agent architecture might already be the right one: give the agent a file explaining how to do something, and let it read when needed.
- Traces Are the New Debugger
When behaviour emerges from both code and model responses, reading source files isn't enough. You debug by examining execution traces.
- Banks Have an AX Problem They Don't Know About Yet
Banks are building AI agents to call their APIs. Those APIs weren't designed for agent callers. The mismatch is subtle, consequential, and almost nobody is talking about it.
- Per-Token Pricing Is the 'Megapixels' of AI
We're optimising for the wrong number — and the history of consumer electronics suggests we'll figure this out eventually.
- AX: Agent Experience Is the New DX
Developer experience became a competitive moat in the API era. Agent experience is next. Most tools aren't designed for it yet.
- AI Agent Frameworks for Enterprise FS: What Actually Works vs. Hype
Most enterprise AI agent pilots in financial services fail at the same point: the second tool call. The problem isn't the framework.
- Intelligence on Tap
When artificial intelligence becomes as mundane as running water, how does thinking itself change?