A hands-on introduction to Flue, an experimental TypeScript framework for building server-side LLM agents. Covers the agent/harness/session model, three working examples from a simple translator to a container-backed coding agent, and an honest look at the trade-offs — so you can decide whether Flue fits your stack before you commit. Table of Contents You’ve decided […]
Read More →You’re deep in a refactor, you hand off a task to your AI coding agent, and you walk away to get coffee. When you come back, your project directory has been restructured — but so has everything else. The agent followed a chain of reasonable-looking steps that ended somewhere you never intended. This isn’t a […]
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 →Running LLMs locally has become a normal part of how developers work. Two tools dominate this space: llama.cpp and Ollama. They look like competitors, but the relationship is more direct — Ollama is built on top of llama.cpp. This post covers the technical differences, where each performs better, and when to use one versus the other. Table of […]
Read More →Your brain is a muscle. And AI is offering to carry all the weight. Table Of Contents Introduction In 2000, Eleanor Maguire and her colleagues at University College London scanned the brains of licensed London taxi drivers — people who had spent years memorizing 25,000 streets and thousands of landmarks through a grueling training process […]
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