# claude-code

A power user analyzed 6,852 Claude Code sessions and 17,871 thinking blocks, proving with data that CC really did get 'lazier' — Read:Edit ratio dropped from 6.6 to 2.0. Then Anthropic engineer Boris Cherny explained the real reason, and how to fix it.

CLAUDE.md is a suggestion. Hooks are commands. This post covers 8 battle-tested Claude Code Hooks — from auto-formatting and blocking dangerous commands to protecting sensitive files and auto-committing. Copy, paste, done.

Alexey Grigorev stopped letting a single AI agent handle everything. Instead, he split the work across four roles—PM, SWE, QA, and On-Call—forming an agent team. He tested this setup on five real projects. One of them completed 41 out of 46 tasks in a single night.

Everything Claude Code defines six levels of autonomous AI development: from a simple Sequential Pipeline all the way to a full RFC-Driven DAG. Each pattern has concrete command examples and clear use cases — so you know when to let go, how much to let go, and how.

Everything Claude Code's Instinct System turns your AI's observed behaviors into atomic 'instincts' with confidence scores, project scoping, and a promotion mechanism. Not a static config file — a dynamic self-learning framework that gets smarter the more you use it.

Git hooks work even when you forget they exist. AI hooks make your Claude Code follow rules even when it forgets. ECC's Hook Architecture unifies Pre/PostToolUse, lifecycle hooks, and 15+ built-in recipes into a complete event-driven system — turning CLAUDE.md suggestions into actual enforcement.

Your AI Agent is very obedient — but it might be obeying the wrong person. Prompt Injection is social engineering for AI. Tool Use Exploitation is giving a Swiss Army knife to a 5-year-old. Context Poisoning is someone secretly changing books in a library. And then there's the zoo escape.

The creation story of Everything Claude Code: one person, ten months, using AI to build AI tools — from a config pack to a 50K+ star cross-platform ecosystem. Not a tool tutorial. A real case study of what an indie hacker can do in the AI era.

You use unit tests to check your code and CI to protect your pipeline. But who checks your AI? Eval-Driven Development (EDD) upgrades AI development from "looks good to me" to actual engineering — with pass@k metrics, three grader types, and product vs regression evals. This is TDD for the AI era.

Most token waste is invisible: Extended Thinking on tasks that don't need it, Opus handling work a Sonnet could do, context filling before you compact. ECC's token-optimization.md combines MAX_THINKING_TOKENS + model routing + strategic compact — author Affaan Mustafa says the savings reach 60-80%.

After running nine Claude Code agents in parallel, we hit an article counter race and a git lock conflict. ECC's iterative retrieval pattern points at the same multi-agent problem: shared context needs isolated state, atomic pre-allocation, and sequential deploy.

Paweł Huryn shares three CLAUDE.md instruction blocks—Knowledge Architecture, Decision Journal, and Quality Gate—that turn memory into a self-improving system. After a month, Claude had derived 24 project-specific rules from repeated work.

Every new session, your AI agent forgets everything. Claude Code's leaked source hid a three-layer memory architecture and a design principle — 'Memory is hint, not truth' — that changes how you think about building agents. Here's the full breakdown.

The Claude Code source leak had everyone excited about KAIROS and model codenames. But the same codebase had a 3,167-line function, zero tests, silent model downgrades, and regex emotion detection. These aren't just Anthropic's mistakes — they're AI-generated code's default failure modes.

Prompt caching should save you 90% on token costs — but one obscure bug can silently make you pay 10x more. From DANGEROUS_uncachedSystemPromptSection to the cch=00000 billing trap hidden in Claude Code's DRM, here's why prompt engineers now need to be accountants too.

Hidden inside Claude Code's leaked source was a ~90-line file called undercover.ts — designed to make AI commits look like human commits. This surfaces a question the industry hasn't agreed on: when AI writes your code, should anyone know?

Claude Code has 512K lines of TypeScript, 64K lines of production code, and zero tests. The sharper question is not why Anthropic skipped tests, but why it did not use its own AI coding tool to write them. Can the same brain write and grade the exam?

xkcd #1205 taught a generation of engineers how to think about automation ROI. But AI changed the most expensive variable in that equation: the real return now is often not minutes saved, but cognitive load removed.

Anthropic accidentally shipped the full TypeScript source code of Claude Code CLI inside an npm source map. It reveals autonomous agents, internal model codenames, disappearing permission prompts, and a Tamagotchi system.

Claude Code quietly shipped a full /buddy pet gacha for April Fools' Day. After pulling a plain cactus, the author reverse-engineered its Bones + Soul system, found a userID fallback exploit, and brute-forced a golden legendary capybara.