Notes from a conversation with Gregor Hohpe — author of The Software Architect Elevator and Enterprise Integration Patterns, former principal at AWS and Google. The bad architects are easy to spot. The great ones are invisible — everything just works, and nobody can say exactly why. Gregor Hohpe on what separates the two, and how […]
Read More →Your agentic app just ran a search. The tool returned 500 results as JSON. Your agent appended all of it and fired off an API call — 45,000 tokens to answer a question that needed maybe 4,500. Tejas Manohar, a senior engineer at Netflix, hit this problem every day. He was running out of tokens […]
Read More →You give your AI coding agent a task. It gets to work. Thirty tool calls later you have code — and it’s not what you needed. The agent understood the words but missed the intent. It made a dozen small decisions that individually seemed reasonable, and collectively built the wrong thing. This isn’t a capability […]
Read More →You’ve seen the numbers. 7B. 70B. 405B. Everyone talks about parameter counts. But what are they? Why does size matter? And what actually happens when you hit “Generate”? This post covers the mechanics: what parameters are, where they live in the model architecture, how scaling affects them, and what that means if you’re running or choosing […]
Read More →TL;DR: The Kano Model isn’t just a PM’s tool — it’s a critical framework for engineers to evaluate feature value, manage technical debt, and define MVPs. By categorizing requirements into Must-be, One-dimensional, and Attractive qualities, teams can align technical execution with user satisfaction dynamics. Nowhere is this more visible right now than in AI agentic coding tools, where yesterday’s delighters […]
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