Tangled Circuit

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. @CopilotKit + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here: go.copilotkit.ai/built-in-agent…

Introducing Brain in Computer. Brain is a continuously learning memory system. Every task on Computer plugs into a context graph built by Brain. It makes Computer more stateful with every run. Available as a research preview for all Perplexity Max subscribers.

Introducing HyperView. Generative UI for coding agents. Terminal, diffs, live previews, anything. Your agent renders real UI for you while it works in a sandbox. Open-Source & Powered by Hyperbrowser Sandboxes.

docs for deno desktop: docs.deno.com/runtime/deskto…

Quack is a new protocol that enables client-server architecture for DuckDB over TCP/IP and HTTP(S), announced at AI Council 2026. It allows one DuckDB instance to act as a server and another as a client, with remote database attachment, query pushdown (computing on the server vs. the client), and token-based authentication. It allows whole new possibilities, as database clients are usually quite dumb; you can send a query and retrieve data. But with Quack, you could aggregate, you could build a whole ETL job, aggregation, or any business logic inside it Check out more at: ssp.sh/brain/quack-pr….

Before Fable 5 was shut down, it pushed Gemma 4 to 255 tok/s on WebGPU. Some didn't believe it was real. Today we're releasing the demo and kernels it wrote for you to see yourself. Run it locally in your browser. Agentic kernel optimization is the future of on-device inference

@berdyn Manitoba here home of the inland ocean

I feel like I don't follow enough Canadians on this app... are there any Canadians out there???

Electric Agents 0.6 is out! 0.6 rounds out what we launched in May: • Long-lived entities with StreamDB state • Spawn, fork, send, wake, signal, schedule • Local and remote agent runners • Desktop + mobile apps built on core APIs • PG sync triggers, MCP servers, webhook sources The ecosystem is converging on our thesis: the agent is the log. Electric Agents paints the picture for what is built on top.

兄弟们，我一直有个判断：OCR 这种活，早晚会被多模态大模型给吃掉。 这周看到百度发的 PP-OCRv6，我改主意了。 一个 1.5MB 的模型，能直接塞进浏览器里跑，单图最快 97 毫秒就能出结果，逐字识别的准确率还反超了 GPT-5.5、Gemini-3.1-Pro 和 235B 参数的 Qwen3-VL，我有点震惊了！ 对做产品的人来说，这比「又一个 SOTA」重要得多。我有测试，先往下看 👇

This is probably 1 year+ in the making To be released next week in Deno 2.9 Created by @undefined_void and @crowlKats

`deno desktop` has landed in main. You can try it out by running `deno upgrade canary` - Mac, Linux, and Windows support - Can generate pkg and msi installers - Supports cross-compile (generate .exe from mac) - Supports chrome (CEF) or native Webview for smaller binaries

Just Shipped: Flue 1.0 Beta Flue is the TypeScript framework for building the next generation of agents, designed around an open agent harness with zero LLM lock-in. It’s like Astro, for agents. Flue 1.0 has been redesigned around three core primitives: 🔁 Workflows — structured automations designed for background work, where your code drives the agent from start to finish. 🧭 Agents (New!) — autonomous, stateful loops where the model drives itself to complete a given task. 📡 Channels (New!) — connect agents to Slack, GitHub, Linear, Discord, Teams, and more. Flue handles the boilerplate for you. Everything shares the same durable foundation, powered internally by Pi, Vite, and Durable Streams. Deploy anywhere, use any LLM, and recover running agents across restarts and downtime. We’ve talked to a lot of teams building agents, and keep hearing the same thing: getting to production is hard work. We built Flue to help change that. Flue 1.0 Beta is available today. Give it a try and let me know what you think!

In partnership with @stripe, Hermes Agent now supports a full suite of Stripe skills. Your agent can buy things, pay per-call APIs, and provision its own SaaS, with configurable safety limits on every action.

You can now run a GPT-5.5-level model on your own computer for free. NVIDIA released Nemotron 3 Ultra as a full open model. And if you still need an API, it gets even cheaper. Atomic's tested it against GPT-5.5 on the same task: 3 HTML5 physics demos from scratch. GPT-5.5: 11k tokens, $0.57. Nemotron 3 Ultra: 11.3k tokens, $0.051. The output of Nemotron was better. The price was 10x lower.

AMD CEO Lisa Su just dropped the most powerful mini-PC ever built. "Lunchbox" sized and built to run 200B+ parameter local LLMs

oh my god its happening @MistralAI has officially confirmed the upcoming release of Le Chaton Fat - 30T MoE with 256 experts - 1M context window - multimodal and multilingual - outperforms Fable 5 on every benchmark

TWO BOXES THE SIZE OF A MAC MINI JUST RAN A 235 BILLION PARAMETER MODEL ON A DESK It is two NVIDIA DGX Spark units linked by a single cable. A year ago a model this size meant renting a GPU cluster by the hour. Now it sits next to your monitor for around $8,000. Here is the twist most people miss. Linking them does not create one shared 256GB memory pool. The model is split across both boxes, and that is the only reason a 235B model fits at all. It answers at roughly 10 tokens per second, and both chips sit at just 74 degrees while sipping around 50 watts. Every token stays on the desk. Nothing touches a cloud, and nothing leaves the room. The ceiling for what you can run at home just jumped from 70B to 235B. Bookmark this & Watch it run ↓

AN AMD ENGINEER SHIPS A PALM-SIZED MINI PC THAT RUNS 235B MODELS FOR $9/MONTH AND KILLS A $200/MONTH OPENAI OR CLAUDE CODE SUB at CES 2026 in las vegas, AMD CEO lisa su walked on stage with a small black box behind her, not a server, not a data center render, a mini PC the size of a hardcover book a few months later in shanghai she walked up to that same device and signed it with her name, the box is the gmktec EVO-X2, $1,700 once, AMD ryzen AI max+ 395 inside the chip is the first x86 silicon ever built that runs a 200 billion parameter model on one piece of hardware, 128GB unified memory, 110GB usable VRAM on linux, no separate graphics card it runs qwen 3 235B fully and smoothly, plus deepseek v3 and llama 3.3 70B with no quantization, kills a $440/month claude code, chatgpt, gemini and cursor stack for $9 in electricity setup takes 3 commands and 15 minutes, ollama loads the model, claude code points to localhost with one environment variable, same interface, zero per token fees, nothing ever leaves the machine the window is open, follow and bookmark before it closes

If you have: Hermes Agent Claude Code & Codex Handoffs Obsidian + QMD Memory System Run Agentic Loops Fleet Tailscale Mesh Cron Jobs + Kanban Board Agentic Workflows Congrats you are the top 1% of the AI god stack

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