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The Mythical Man-Month, Reread in 2026: Why Adding Ten Subagents to Finish in an Hour Is the Same Curse as Hiring Ten People to Finish in a Month

An in-depth look at the GitHub project agent-mythical-man-month-2026 (《agent 时代的人月神话》): an 18-chapter reread of Fred Brooks' 1975 classic, written in the 2026 AI-agent context by one purposeful author plus several agents. Covers the core ideas (harness as a state machine, context as the only variable, the halting-problem prediction, Brooks' Law in dual forms, No Silver Bullet), design philosophy (one surgeon + an agent support team, three 10x effects, audit vs correction rights, documentation as source code), a detailed tutorial and an 18-chapter guide

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Soup: Fine-Tune an 8B LLM on a 4 GB Laptop GPU with This One-Command CLI

An in-depth look at MakazhanAlpamys/Soup — a CLI-first LLM fine-tuning tool. Explore how Layer Streaming fine-tunes Llama-3.1-8B at 119.6 tok/s on a 4 GB GPU, how bit-exact testing proves correctness, why it chooses to refuse rather than warn, and the measurement-driven design philosophy behind it, complete with a full tutorial

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Traction by Gabriel Weinberg & Justin Mares: Why "Failing to Get Customers" Is the #1 Startup Killer

An in-depth look at Traction: How Any Startup Can Achieve Explosive Customer Growth by DuckDuckGo founder Gabriel Weinberg and Justin Mares (Chinese edition 《拉新：快速实现用户增长》). Built on interviews with 40+ founders, it breaks down the core ideas (Traction trumps everything, the 50% rule, three phases, Critical Path), the Bullseye framework, and all 19 traction channels — with a double-verified, honest evaluation

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