# claude-code

Clawd.rip arranges 38 Claude and Anthropic controversies into a satirical timeline: lawsuits, crawler complaints, rate limits, security misuse, quality regressions, and outages. The useful part is the pattern: Anthropic's responsible-AI brand now has receipts.

Anthropic explains how claude.ai, Claude Code, and Claude Cowork contain agents: model defenses miss, permission prompts create fatigue, and the hard boundary is the VM, sandbox, filesystem policy, and egress control.

Whether Claude Code works inside a large codebase is not just about model scores. The real question is whether the team has built rails for the agent: maps, automation, on-demand tools, symbol navigation, internal-system access, and someone to maintain the whole operating setup.

OpenAI and Anthropic both pushed /goal-like ideas into coding agents. A goal helps, but production agents also need strategy, constraints, health metrics, autonomy boundaries, and stop rules.

Thariq explains why HTML is replacing Markdown in Claude Code workflows: not as prettier output, but as readable, operable, shareable artifacts that keep humans inside the agent decision loop.

Anthropic's guide to connecting production agents to real systems. When agents move to the cloud, API / CLI / MCP all ship — only MCP compounds. Uses Cloudflare's MCP server (2 tools, ~2,500 endpoints, ~1K tokens) as the benchmark for remote-first design, intent-grouped tools, and production auth.

Anthropic's postmortem confirms Claude Code felt dumber because three independent changes stacked: reasoning effort demotion, cache optimization dropping thinking history, and Opus verbosity tuning. Fixed by April 20, with usage limits reset.

Garry Tan's agent screwed up twice this week — both bugs had the same shape: deterministic work done in latent space. His fix is skillify: every failure becomes a SKILL.md + deterministic script + tests + evals + resolver trigger. Ten steps. The bug becomes structurally impossible to repeat.

GP-175 covered Opus 4.7 hard specs. This is the workflow layer. Pawel Huryn argues intent is the new unlock. Two-layer CLAUDE.md, per-call effort toggle, batch questions, show-don't-forbid, kill stale scaffolding, review plans not diffs — plus Anthropic/OpenAI converging.

Anthropic released two Opus 4.7 best practices — a Claude Code guide and a full prompting docs page. 4.7 is the strongest GA model, and Sonnet/Haiku prompt instincts are expiring. One cheat sheet: three must-knows, effort ladder, 4.6→4.7 diffs, copy-paste snippets.

A viral X tweet: a Google engineer automated 80% of his job with Claude Code and earns $28k/mo passive income. We checked the four main claims — Karpathy didn't write that CLAUDE.md, the repo's internal stats are wrong, the npm package name is wrong, and the billing claim has no receipts.

Daniel San moved from VSCode to Ghostty, then invented a four-letter mnemonic (SAND = Split / Across / Navigate / Destroy) to burn Ghostty's panel shortcuts into muscle memory. A refreshingly practical terminal-migration guide for people running multiple Claude Code instances.

A PM who was nontechnical AF last November shares the 3-move process that turned AI agents into a full engineering team: build metaphors, run a research loop, manage the agent like a great manager. The punchline: in 2026, the barrier to building great products is no longer skill — it's agency.

JetBrains surveyed 10,000+ developers worldwide: 90% use AI tools at work, GitHub Copilot leads but its growth has stalled, and Claude Code grew 6x in six months with the highest satisfaction scores on the market.

SemiAnalysis argues leaked Claude Code source shows TypeScript becoming a language AI produces, consumes, and evolves. The post reads 600,000 leaked lines through memory architecture, KAIROS, security holes, and static types.

Most agent failures are not reasoning failures — they are fetch failures. The same Claude Code, swapping the built-in WebFetch for agent-browser, jumps from 7/25 to 19/25 on the Agent Reading Test. Same model, same prompt. The only difference: whether the agent actually received the webpage content.

Claude Code creator Boris Cherny cleared the air directly: every subscriber uses the same Opus 4.6 — there is no secret smarter model. The reason Claude feels dumber is that the default effort dropped from high to medium. One command brings it back.

3-minute lightning talk slides. AI has read almost everything — but some concepts aren't in training data yet. What you know that AI doesn't = your leverage.

A reverse-engineering tour of Claude Code's 55 directories and 331 modules: execution loop, context compaction, subagents, permissions, hooks, and the core lesson that environment design—not the model alone—determines agent outcomes.

Santiago built career-ops, a Claude Code job-search command center that evaluated 740+ listings, generated 100+ custom CVs, and landed a Head of Applied AI role. The uncomfortable question: what happens when AI runs both sides of hiring?