Agentic Ai

Summary: Muse Glimmer in 30 Seconds Muse Glimmer is a 30 billion parameter agentic model released by Meta Superintelligence Labs on August 10, 2026. The weights are open under Apache 2.0. No cloud needed. Four-bit quantization shrinks the language model to under 20 GB, so it runs on a single consumer GPU with 24 GB or 32 GB of memory. It reads text and images, and returns text. Default context window is 128K tokens, and the model supports more. It clears its size class on agentic tests: 75.5 on MCP Atlas (Gemma4-31B 54.2, Qwen3.6-27B 62.5). On math, 94.7 on AIME 2026. The bundled DFlash drafter speeds generation up 3.1x on an RTX 5090 and 1.8x on an M5 Max. It is distilled from Muse Spark, Meta’s cloud model, so the big model’s agentic behavior is transferred into a small one. On the same day Zuckerberg announced that the weights for Muse Spark 1.2, Meta’s flagship model, will be opened too. No date, just “soon.” An AI agent normally means an API key, an internet connection and a bill that ticks up with every request. Meta just tried the opposite. ...

You want to tell an AI “read this file”, “pull that record from my database”, “close this issue”. The model cannot do any of it on its own, because it has no access to your machine, your database or your accounts. MCP exists to close exactly that gap. It puts a standard connection layer between the AI application and the outside world 🔌 What Is MCP? MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems. ...

“Agentic AI” is the most-discussed term of 2026, and most of what gets written about it looks at the same angle: enterprise transformation, productivity gains, automated customer service. All true, and none of it answers the question a developer actually has: how does this thing work? This post takes that angle. How the loop turns, which component actually executes tool code, why memory became its own architectural layer in 2026, and where these systems break 🤖 ...

On July 21, 2026, Google announced three new Gemini models at once: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and the defense-focused Gemini 3.5 Flash Cyber. The theme of the announcement is clear: not higher scores, but getting the same job done with fewer tokens. As agentic workflows move into production, the bill is driven less by how smart a model is and more by how many tokens that intelligence burns. Google aimed straight at that. Here are the details. ...

OpenAI has announced GPT-5.5, its smartest and most intuitive model to date. Introduced as “a new class of intelligence,” it is poised to fundamentally change how we get work done on a computer. 🚀 Introducing GPT-5.5 A new class of intelligence for real work and powering agents, built to understand complex goals, use tools, check its work, and carry more tasks through to completion. It marks a new way of getting computer work done. Now available in ChatGPT and Codex. pic.twitter.com/rPLTk99ZH5 ...