Dvalium

[Developers @XDevelopers]

Announcing the hosted X MCP.

Agents now have access to the best real-time information source in the world.

Connect Grok, Cursor, or any MCP-compatible AI tool to the X API without any setup!

Check it out here: https://t.co/5MzPYwGFzD

[Anatoli Kopadze @AnatoliKopadze]

Spotify Chief Architect, Niklas Gustavsson:

"Once we implemented loops in our workflow, our agent success rate went from 20-30% to 80%."

26 minutes with Claude Code creator Boris Cherny on how Spotify runs AI agents across 20 million lines of code.

Today 73% of their code is written by AI, most merged without a human ever seeing it.

The model matters less than the loop you build around it.

Watch it, then read the full guide on building loops below.

[Thomas (Tom) Lee (not drummer) FundstratDirect.com @fundstrat]

Crypto is a hyper volatile asset and some macro headwinds are weighing on Bitcoin and ETH $BTC $ETH

- headwinds: markets see Fed hike, Clarity Act purgatory, AI 🤖 FOMO, and private credit hurting flows

- tailwinds in place: tokenization a megatrend, crypto downstream of AI 🤖, money is becoming digital / software and sentiment so bad (peak pain?)

Great speaking with @Scaramucci on this

[Gad Saad @GadSaad]

Happy birthday to a truly legendary intellectual!

[David Hunter @DaveHcontrarian]

Here's my latest & very timely interview recorded 6/24/26 with Alex Smith @pinnacledigest.Lots of good questions & good discussion about the stock,bond & metals markets,the coming global bust & what will follow. https://t.co/QEl1xOaFBl

[Ivan Fioravanti ᯅ @ivanfioravanti]

Best way to really enjoy the power of GLM 5.2 is using zcode to drive it. It's tailor made on the model and the additional services offered by @Zai_org

You can find it here: https://t.co/pQzwkLyLs2

[Matthew Berman @MatthewBerman]

I said this was going to happen. Chinese open source is looking quite attractive as toke spend keeps increasing. The vast majority of use cases don’t require the absolute frontier of intelligence.

This will become a big problem. If US enterprise is built on Chinese models, we will become reliant on Chinese chips as the chip<>model codesign becomes more codependent.

[Ihtesham Ali @ihtesham2005]

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab.

The model is called GLM 5.2. It was built by Z. AI.

You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario.

It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved.

It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance.

Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it.

The method is called distillation.

Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training.

It is a cheat sheet. It is the answer key to the exam.

And here is the part that should worry everyone.

Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers.

Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total.

The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027.

Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait.

The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next.

The question is just whether the open weight half of that stack is American or Chinese.

Right now it is Chinese.

WATCH THE FULL PODCAST ON @theallinpod

[Polymarket @Polymarket]

JUST IN: A new Chinese AI model from Zhipu AI reportedly matches Claude Mythos’ performance at finding security bugs.

[Marc Andreessen 🇺🇸 @pmarca]

Many smart people/AI insiders are saying GLM-5.2 is the first Chinese AI model to match and often beat the American big lab public AI models with no compromises. Incredible timing given current events.

[Elon Musk @elonmusk]

@wholemars @TovikkaX The production shortfall relative to demand is insane. MUCH higher production is needed.

[Brian Armstrong @brian_armstrong]

Yep

[Parker Conrad @parkerconrad]

We launched Rippling Data Cloud today - an all-in-one rebuild of the modern data stack, with AI deeply integrated throughout.

Why would you want an org-and-employee-centric data stack? Well, here’s how I used Rippling Data Cloud to help with token burn and cut AI slop. 1/

https://t.co/2rhp8x3KVn

[Elon Musk @elonmusk]

Tim Cook, who told The Wall Street Journal that the jump in costs was unlike anything he had seen “in any area in over 40 years.”

Biggest price jump in anything I’ve ever seen too. https://t.co/aypJGgssnN

[Nous Research @NousResearch]

Hermes Agent can now /learn from anything: feed it directories of any source material (code, API docs, manuals, PDFs, configs) and it distills a verifiable reusable skill

[Brian Feroldi @BrianFeroldi]

Jason Zweig on reasons to not allocate 100% to stocks:

[Andrej Karpathy @karpathy]

This is a new paradigm for interacting with Claude that is significantly more "inline" with all the other human activity org-wide. Once you do all of the under the hood engineering work to make this "just work" (e.g. across tools, integrations, compute environments, memory, security, etc.), Claude basically joins the team in a seamless way - you can talk to it as you would talk to a person and it can help with a very large variety of workloads.

Imo this is the 3rd major redesign of LLM UIUX. The first paradigm was that the LLM is a website you go to, the second was that it is an app you download to your computer. This third one is that it is a self-contained, persistent, asynchronous entity with org-wide tools and context, working alongside teams of humans. It really takes a while to wrap your head around it, but it works and it is awesome.

[Anatoli Kopadze @AnatoliKopadze]

Peter Steinberger, the guy who built OpenClaw just shared his actual workflow:

"Each loop is so much faster now that I ship more than ever with way less effort."

19 minutes from the person who knows more about AI agents and loops than anyone else.

Watch it, then read the full guide on loops below.

[Elon Musk @elonmusk]

True

[Vinod Khosla @vkhosla]

More than one way to get to to SOTA performance . Exciting.