Nobody Is Training the People This Job Actually Needs
I read the entry requirements of every Forward Deployed Engineer programme I could find, then read what Singapore's publ...
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The Best Forward Deployed Engineers May Not Be Engineers
An AI practitioner in Beijing argues that the best Forward Deployed Engineers he has worked with were not computer scien...
Where Does My Data Actually Go?
"Do you use my data?" is two questions wearing one coat. Training asks whether your text enters a future model and is us...
Why It Confidently Makes Things Up
We asked two AI models for five peer-reviewed studies on an obscure topic, with DOIs. One produced five — authors, journ...
MCP, RAG, Agents, Skills: The New AI Vocabulary in Plain English
Somebody says the agent will use MCP to hit the connector, then RAG over the docs, and the skill handles the rest. Every...
Tokens and Context Windows, Explained From Zero
You are billed in a unit nobody explained. A token is a countable stand-in for a chunk of text — the word is borrowed fr...
What an LLM Actually Costs You
The rate per million tokens is the one number you cannot change, and the smallest part of the bill. Measured on 102 para...
The Chapter Everyone Skips: 孫子兵法 and the AI Capital War
Business writing quotes 知彼知己 and misquotes it — the received text reads 百戰不殆, not the 百戰百勝 that Sun Tzu expl...
Serve an LLM with vLLM on CPU in Docker: Learn the Production Engine Without a GPU (2026)
We ran vLLM v0.25.1's official CPU image in Docker on Apple Silicon, dodged a 10 GB CUDA decoy, survived three traps, an...
Run ComfyUI on CPU in Docker: Node-Graph Image Generation Without a GPU (2026)
We pinned ComfyUI v0.28.0 in a python:3.13-slim container, hit a torchaudio ABI trap and an 8 GB OOM kill, and still ren...
Self-Host LiteLLM with Docker: One OpenAI-Compatible Endpoint for Every Model (2026)
We ran LiteLLM v1.93.0 against a local Ollama model in Docker: pinned tags, a 4-line config, token metering, and the wro...
How to Transcribe Speech Offline with whisper.cpp in Docker (2026)
We ran whisper.cpp v1.9.1 in Docker: an amd64-only tag trap, a SIGILL crash, a gcc fp16 build fix — then 7.3 s of speech...
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