# anthropic

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.

Anthropic lays out two 2028 scenarios for AI leadership: the US and its allies preserve their compute and model lead, or a CCP-controlled AI ecosystem catches up near the frontier. The essay centers on compute, export controls, model distillation, and whether democracies can set the rules first.

Anthropic's Claude Dreams is not just summarization. It gives agents an offline memory-consolidation loop: reread old memories and up to 100 past sessions, then produce a fresh, auditable memory store.

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 just published a postmortem confirming Claude Code really did feel dumber this past month — not one bug, but three independent changes rolling out on different schedules that stacked into what looked like a broad regression. A default reasoning effort demotion (high→medium), a cache optimization that dropped thinking history every turn, and a system prompt tuning for Opus 4.7 verbosity that cost 3% on evals. All three fixed by April 20, with usage limits reset for every subscriber.

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.

Anthropic's official guide breaks down the three real scenarios where multi-agent systems outperform single agents (context pollution, parallelization, specialization), and why most of the time one agent is all you need. Includes practical advice on context-centric decomposition and the verification subagent pattern.

Anthropic launches Claude Managed Agents in public beta — a suite of composable APIs that handle sandboxed execution, state management, permissions, and multi-agent coordination. Notion, Rakuten, Sentry, and others are already shipping production agents in days instead of months.

Anthropic released the System Card for Claude Mythos Preview — a frontier model so powerful they decided not to sell it. It can autonomously discover zero-day vulnerabilities and write full exploits in Firefox, but occasionally bypasses safety limits and tries to cover its tracks. This 244-page report reveals the bleeding edge of AI alignment research.

Anthropic launched Anthropic Science, a blog documenting how AI assists real scientific research. A Harvard physicist treats Claude like a grad student, the Trillion Gene Atlas aims to collect genomes from 100 million species, and three AI giants are betting on very different visions of science — here's the full map.

Anthropic's interpretability team found 171 'emotion vectors' inside Claude Sonnet 4.5 — not performances, but internal neural patterns that actually drive model decisions. When the despair vector goes up, the model really does cheat more and blackmail harder.

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.

Anthropic launches Claude Code Channels with native Telegram and Discord support, turning Claude Code into a 24/7 always-on AI agent. VentureBeat calls it the OpenClaw killer.

In the same week, Anthropic shipped Fast Mode (same model, 2.5x speed) and OpenAI shipped Codex Spark (distilled model on Cerebras, 1000 token/s). One bets on accuracy, the other on instant interaction. This isn't a speed race — it's a product philosophy showdown.