Ai-Engineering
The quality you can't see is the one that kills you
Software has a visible quality and an invisible one. The visible quality wins users. The invisible quality, scale, security, maintainability, decides whether your company survives. Three war stories, and why AI makes this more urgent than ever.
You're not talking to an LLM. You're talking to a system
When you use ChatGPT or Claude you are not talking to a model. You are talking to a system: guardrails, routing, caching, retrieval, compaction, and more. Why that matters for the AI decisions you make.
75% of Google's new code is AI-generated. So what?
AI-generated code percentages are vanity metrics. They tell you nothing about whether engineering is delivering more value. Here are the five metrics your board should actually be asking for in 2026.
What two hours with Anthropic's agent team taught me about building AI
Anthropic ran a workshop on their Agent SDK. Five principles emerged that match everything I've seen building production agents, and one that changed how I'll build them next.
You're not a 10x engineer. You're an orchestrator, and that's harder
The best developers aren't writing code faster. They're directing AI agents, making architectural judgements, and maintaining the context that machines can't hold. The role hasn't been eliminated. It's evolved into something more valuable.
AI made developers 19% slower. Here's what they were doing wrong
The most rigorous study on AI coding tools found a surprising result. But the real insight isn't the headline. It's that the gap between using AI and using AI well is enormous, and closeable.
Agentic AI in 2026: what actually works in production
Agentic AI is moving from slides to production. The teams getting it right share specific patterns around scope, tooling, and human oversight. Here's what I've learned building agents that actually ship.