Claude

TL;DR On 12 June 2026 at 5:21pm ET, the US government issued an export control directive ordering Anthropic to suspend all access to Fable 5 and Mythos 5 - globally, for every user, including Anthropic’s own employees The stated reason is national security: the government believes it has identified a method of jailbreaking Fable 5. Anthropic says the evidence was verbal only and describes a narrow, non-universal technique - essentially asking the model to read a codebase and fix software flaws Anthropic reviewed a demonstration and found it surfaced a small number of previously known, minor vulnerabilities that are widely available from other models Anthropic disagrees that a narrow jailbreak justifies recalling a commercial model deployed to hundreds of millions of people, and warns the same standard would “essentially halt all new model deployments for all frontier model providers” All other Anthropic models are unaffected. The company says it believes this is a misunderstanding and is working to restore access Four days. That is how long Mythos-class capability lasted as a publicly available product before the US government ordered it off the shelf. ...

TL;DR Bloomberg’s The Circuit with Emily Chang went inside Anthropic in a rare, in-depth episode released June 10, 2026. Dario and Daniela Amodei discuss the founding story, the Pentagon dispute, and why they say safety and commercial success are the same bet. Anthropic is now valued at $965 billion, eclipsing OpenAI’s $852 billion for the first time, after an 80-fold revenue surge in Q1 2026. The Pentagon story is not PR - Anthropic refused to remove safety guardrails from its military contract, was blacklisted by the Trump administration, and sued. A federal judge sided with Anthropic. A confidential S-1 IPO filing in June 2026 means this stops being a private company conversation soon. The Bloomberg Documentary: Emily Chang Inside Anthropic Bloomberg’s The Circuit has done this kind of access piece before - Zuckerberg, Musk, Jensen Huang. But the Anthropic episode feels different in tone. Emily Chang is not sitting across from a founder who has already won. She is sitting across from two founders in the middle of one of the most consequential moments in the company’s short history: record valuation, Pentagon litigation, IPO on the horizon, and model releases arriving fast enough that the competitive landscape changes every few months. ...

TL;DR Claude Fable 5 is Anthropic’s first Mythos-class model made safe for general use - state-of-the-art on nearly every benchmark Anthropic tested, with the gap widening on longer, more complex tasks Claude Mythos 5 is the same underlying model with cyber safeguards lifted for Project Glasswing partners; a biology trusted-access program is coming next Risky queries in cybersecurity, biology/chemistry, or suspected distillation attempts are routed to Claude Opus 4.8 instead - roughly 5% of sessions, with Anthropic acknowledging some false positives Pricing drops to $10 / $50 per million input/output tokens - less than half what Mythos Preview cost Fable 5 is free on Pro, Max, Team, and seat-based Enterprise plans through 22 June 2026, then moves to usage credits until capacity catches up Two months ago I wrote that Claude Mythos Preview was the benchmark breaker that would not be released - 93.9% on SWE-bench, thousands of zero-day vulnerabilities found autonomously, access restricted to a dozen companies through Project Glasswing. The question hanging over that post was whether Anthropic could ever democratise Mythos-level capability without democratising the offensive potential. ...

Dario Amodei is one of the few frontier-lab CEOs whose public talking points have not changed materially in five years. The same message he gave to small audiences in 2021 - that powerful AI is coming faster than people think, that the safety problem is real, and that the companies building it have an obligation to do so carefully - is the message he is giving to Congress and Davos in 2026. The thing that has changed is that he now runs the company most aggressively turning that message into a commercial position. ...

On 28 April 2026 Anthropic shipped a batch of nine creative-tool connectors for Claude, and one of them is the Ableton Knowledge connector. It is a small thing on the surface and a big thing underneath. Here is what it does, what it does not do, and why it matters if you spend your evenings inside Live or staring at a Push. What the Connector Actually Does The official Ableton connector grounds Claude’s answers in Ableton’s own product documentation for Live and Push. That is the whole pitch, and it is more useful than it sounds. ...

TL;DR A Claude Code skill is just a folder with a SKILL.md file - YAML frontmatter plus natural-language instructions - and the same folder works across Cursor, Gemini CLI, Codex, and a dozen other tools The format is model-agnostic because it contains no provider-specific syntax; any instruction-following model can read it, and any harness that loads markdown can execute it Progressive disclosure keeps large skill libraries cheap: only names and descriptions load at session start, with full instructions loading only when a skill is activated The portability is practically valuable - version-controlled runbooks that survive tool switches, model upgrades, and team growth without being rewritten Core skills are genuinely portable; advanced frontmatter extensions (like allowed-tools or context: fork) are tool-specific and may need tuning across harnesses Most of the tooling I have written about over the last year has been provider-specific. A particular model, a particular harness, a particular set of features. The thing I find interesting about agent skills is that they are not. ...

TL;DR Problem: a local agent that can only chat is a toy. The value is in what it can do. Answer: Model Context Protocol servers, running locally on the Mac Studio, expose filesystem, calendar, mail, notes, and a handful of custom tools. Runtime: one supervisord config, a small router, and per-server allowlists so nothing escapes its box. Security posture: no tool runs without a policy, secrets live in the macOS Keychain, and every call is logged to a local SQLite file I can grep at 11pm. Result: I can phone the agent (see How to Phone Your Home AI Agent), ask “move the CI failure email to triage and put a 15 minute hold on my calendar at 4”, and it actually does it. Why MCP and Not “Just Functions” Before MCP I had a directory of half-finished Python shims. Each one spoke a slightly different dialect: one took JSON arguments, one took positional args, one returned markdown and one returned a dict. Adding a new tool meant editing the agent prompt, the router, and the caller. ...

TL;DR Problem: a home agent with tools but no memory is a very well-read goldfish. Every morning it re-meets you. Answer: split memory into three layers - working, episodic, and semantic - and give each layer its own store and its own rules for what gets written. Where it lives: SQLite for episodic and facts, a local vector store for semantic search, and a tiny policy file that decides what is worth remembering in the first place. How it plugs in: a memory MCP server that exposes recall, remember, and forget - nothing else. Result: the agent can say “last Tuesday we tried restarting the Postgres container and it worked” and mean it. It also knows what not to store. The Goldfish Problem The home agent I built over the last few weeks can do real things now. It can read my mail, move files around my workspace, turn lights off, and check my calendar. What it could not do, until this week, was remember any of it. ...

Databricks announced this week that Anthropic’s Claude Opus 4.7 is now live on the platform. The headline from Databricks’ own benchmarking is the part worth pausing on - 21% fewer errors than Opus 4.6 on the OfficeQA Pro document-reasoning benchmark when the model is grounded in source information. That single number tells you more about where enterprise AI is going than any launch keynote. Why This Matters More Than Another Model Announcement Most Claude releases get surfaced the same week across the API, Amazon Bedrock, Google Cloud’s Vertex AI, and Microsoft Foundry. That was true of Opus 4.7 on April 16 as well. The Databricks story is different because Databricks is not just another hosting destination - it is where the actual enterprise data lives. ...

TL;DR Token costs don’t scale linearly with productivity - the context window compounds with every follow-up message, so a five-message conversation can cost 2-3x more than one well-structured request Compression is your biggest lever: cutting a prompt in half before sending it reduces cost and often improves answer quality by removing noise Batch tasks that share context together; don’t batch unrelated tasks - real batching spreads the setup cost across related work Build reusable systems (templates, project files, prompt prefixes) instead of solving the same problem repeatedly and paying the context cost each time Prompt caching can cut input token costs by 80-90% on workloads with stable prefixes - the single biggest structural saving most teams are missing If you’re paying attention to your Claude usage, you’ve probably noticed something: your token bills don’t scale linearly with your productivity. Sometimes a conversation that feels quick costs three times more than expected. Other conversations that took hours feel suspiciously cheap. ...