The politicians imprison people to hide their crimes

spaceX $SPCX is up 18% today breaking past $200 per share i guess supply control rockets is bullish?

Starlink connecting schools on remote islands!

🚨 BREAKING: Someone just leaked the ENTIRE system prompt of Claude Fable 5 and Anthropic CANNOT DELETE IT. It was public on GitHub within 24 hours of launch. 120,000 characters. 1,585 lines. 27,000 tokens. And what they're hiding will shock you: ↳ Fable 5 and Mythos 5 are the SAME MODEL. Fable just has extra safety filters locked on. Mythos doesn't but they're restricting who gets access. You're paying for the same thing with different guardrails. ↳ Knowledge cutoff is end of January 2026. Not May or March or JANUARY. They let you think it was newer. ↳ Claude is EXPLICITLY TOLD to avoid bullet points and lists unless you ask. That weird prose everyone noticed? It’s programmed not a feature, but a prompt instruction. ↳ Copyright hard limit nobody talks about: quoting 15 words from ANY source triggers a SEVERE VIOLATION flag. One quote per source maximum. After that the source is CLOSED to Claude forever in that chat. ↳ New persistent storage API buried in there. Artifacts can now store and retrieve your data across sessions using key-value pairs. Most users have NO IDEA this exists. ↳ MCP app connectors are baked INTO the prompt. Claude can search for and suggest third-party integrations MID-CONVERSATION without telling you it's doing it. ↳ The prompt includes full instructions for Claude Cowork, Claude in Chrome, Claude in Excel, and Claude in PowerPoint. These are not just integrations. They're tools Claude USES on you. ↳ This prompt is ONLY for Claude.ai's consumer chat. API users get NO system prompt. Claude Code has completely different secret instructions. The repo is CL4R1T4S by Pliny the Liberator. 26.4K stars. Same repo that leaked ChatGPT, Gemini, Grok, Cursor, Lovable, Replit, and Perplexity. The original leak post hit 700K views in 48 hours. If this gets taken down you'll lose access. Bookmark it NOW.

can someone please explain to me why $HYPE is pumping again

On your own local device 325 GB VRAM 💀

I'm having a break. I'll be back when Fable is. Bend2 should come 2 weeks after that... I've been working 24/7, made a LOT of progress with Fable, but this weekend bots just regressed shit we had fixed. I'm tired & stressed Sorry :( Below is a chart I'm not proud of

New cursor model being teased at compile - same size as Claude opus and gpt 5.5 - trained from scratch, no more kimi base - 10-20x more compute vs composer - generally intelligent, not just coding Releases in the “Next couple of weeks”

Here's our forecasted Claude spend, broken down by team. Engineering is highest at $3.1k/person/month. No surprise. The interesting part is who's right behind them.

WHAT THE HELL is happening in AI? A 3B parameter model just put up coding benchmark scores in the same league as Claude Opus 4.5. 3 BILLION. The weights are on Hugging Face, anyone can test it. I genuinely don't know if this is a breakthrough or if the benchmarks are broken.

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🚨BREAKING: The U.S government gave Anthropic 90 minutes to shut down Fable and Mythos “Amazon AND others” called senior administration officials to warn about models’ capabilities Then: 1:00pm: Government calls. “Take it down.” Cites “national security threat.” No details. Anthropic asks what the threat is so they can fix it. Government said NO. 5:30pm: Commerce letter arrives with export controls. You have 90 minutes…

The streets of New York City are going to be absolute, beautiful chaos until sunrise. The Garden is shaking! 🗽🔥 Knicks win the NBA 2026 championship!

day 4 of posting the hype chart until it hits $100 $HYPE

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Karpathy said something you'll regret ignoring: "Remove yourself as the bottleneck. Maximize your leverage. Put in very few tokens, and a huge amount of stuff happens on your behalf." Loop engineering is the exact thing that does that. In a hand-run session, the operator handles two things: - deciding what the agent runs next - and checking its output before the next step Both are manual, and both decide how far the agent gets on its own without the operator. Loop engineering moves both steps into the system. A core operating structure surrounds the loop, and the diagram below depicts it. - A schedule decides what to run - Loop is the maker that produces the work - A separate checker agent grades the output - A file on disk holds the state they both read. The loop runs until either done, max iterations, or an exhausted budget. Here are some practical engineering considerations: 1) A model grading its own output justifies what it already did instead of catching where it failed. That's why a separate checker's findings return to the maker as the next instruction. And the cycle repeats until the checker finds nothing left to fix. 2) A loop with no stop condition burns tokens, and the cost climbs fast once sub-agents and long runs add up. That's why the exit must be set before the loop runs, not while it is running. A simple exit could be: ↳ fix only the major issues, run one final pass, and stop after two loops, with "all tests pass and lint clean" as the rule that ends it. 3) State has to live on disk, not in context. The model forgets everything between runs, so an MD file or a knowledge graph holds what is done and what is still open. Each run reads it and writes back to it, which lets a loop pick up again after days. 4) The lower the verification bar, the safer the loop. Boring, repetitive checks like a stale version string or a missing test are trivial to verify, so a loop runs them with little risk while the operator is away. Judgment-heavy work is loopable too, but only as far as the checker can confirm the result. Let's look at how an unattended loop fails in two ways. 1) It reports done when nothing is actually verified. The separate checker exists to prevent it, but it merges code faster than anyone reads it, so over weeks, the team stops understanding its own codebase while every check stays green. Green tests say the code passed the tests, not that anyone knows what shipped. Someone still has to read what the loop merges. 2) The checker keeps a running loop honest, but it only catches failures inside a run. The harness around the loop, like the prompts, tools, and checks wrapped around the model, still drifts and breaks in production as models change. That repair loop is usually run by hand based on observability traces. My co-founder wrote a detailed walkthrough (with code) on making that harness repair itself, where a failing trace gets diagnosed, the fix is verified against the exact input that failed, and the failure is locked as a regression test so it cannot recur. Read it below.

BREAKING: President Trump says Iran is expected to sign a nuclear deal tomorrow and the Strait of Hormuz will immediately reopen to all traffic. Trump also says the U.S. will destroy Iran’s remaining nuclear material “if necessary.”

Unlink let's you make arbitrary actions private on any EVM chain. It's perfect for: - defi protocols - wallets - payment processors - bridges - RWAs And many others. Expect to see more adoption soon.

NEW blog post is up! "Has AI Already Killed How-To Nonfiction? Sales Trends, My Personal Data, and What It Might Mean for the Future" My head has been spinning after getting a spreadsheet roughly a week ago. Before we dive into my dirty laundry, let’s state the obvious: millions of people have a vague sense that AI is changing things. And LLMs sure are convenient for getting answers quickly. My team and I use Claude and other tools daily. But far fewer people have first-hand experience with the speed and intensity of disruption that’s happening. Not in a year, not in six months, but right now. So let me show you, using my own books as the cadaver on the table, what a fatality looks like. (Link below)