There are not a lot of signs of agentic AI ramping into production at normal companies so far. There is a lot of boosterism from tech companies about agentic AI. Without trillions spent on agents by enterprises, the whole thing could come crashing down… Kudos to Tavis McCourt
AGENTS
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SkillOS: Open-Source AI-Agent Work Compounding Framework
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MONTREAL.AI just shipped SkillOS. An open-source proof that AI-agent work can compound. Jobs become traces.
Traces become tested skills.
Tested skills improve unit economics. 62% cost ↓
62% time ↓
+46 pts quality Proof: https://
montrealai.github.io/skillos/ GitHub: -
AI Agents Reshaping Search and Information Discovery
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Search is changing faster than ever — and AI agents could completely reshape how people discover information, businesses and services online With Google integrating AI deeper into Search, Maps and digital assistants, the traditional search journey is evolving from
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Deep Agents v0.6 Introduces Delta Channels for 100x Checkpoint Storage Reduction
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Deep Agents v0.6 brings Delta channels, reducing checkpoint storage by up to 100x for long-running agents, without sacrificing observability or resilience. Here’s a 200-turn coding agent session.
Without Delta Channels: 5.3GB of checkpoint storage
With Delta Channels: 129mb -
Run your personal AI company with Alook’s AI agent team
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Run your personal AI company with a team of AI agents! Alook is an open-source collaboration platform for AI coding agents. Self-hosted and local-first. The setup: Define an org structure. Give each agent a role – dev, ops, research, whatever you need. Set reporting lines.
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AI Agents Automate Task Distribution and Team Coordination
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Works with Claude Code, Codex, and OpenCode out of the box. Define the org chart once, assign work from the top down, and have agents handle the rest, including handoffs among themselves. Every completed task feeds back into a shared memory layer, building SOPs the whole team
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Alook: Open-Source AI Agent Team Orchestration Platform
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Alook launched an open-source platform that lets a single person run an organized team of AI agents, with defined roles, reporting lines, and real email coordination between agents.
— 🚨 AI News | TestingCatalog (@testingcatalog) 27 mai 2026
Close the screen and terminal, the agents keep running, and the work lands in your inbox. pic.twitter.com/zkmRiyidSoAlook launched an open-source platform that lets a single person run an organized team of AI agents, with defined roles, reporting lines, and real email coordination between agents. Close the screen and terminal, the agents keep running, and the work lands in your inbox.
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Open-Source Avatars Level Up with AVTR-1 Locally
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OPEN-SOURCE AVATARS JUST LEVELED UP@avaturn_me just open-sourced AVTR-1, and the tech is pretty wild.
— Charly Wargnier (@DataChaz) 27 mai 2026
> clone the repo
> download the weights
> then run a conversational avatar locally on your machine at almost zero cost 🔥
repo + weights + demo links below 🧵↓ https://t.co/IbrBKsDFylOPEN-SOURCE AVATARS JUST LEVELED UP @avaturn_me just open-sourced AVTR-1, and the tech is pretty wild. > clone the repo
> download the weights
> then run a conversational avatar locally on your machine at almost zero cost repo + weights + demo links below ↓ -
Claude Features Enable AI Integration into Real Workflows
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Claude is more than a chatbot • Projects → persistent context
• Artifacts → live outputs
• MCP → external tools
• Connectors → enterprise knowledge
• Rules → operational consistency AI becomes powerful when connected to real workflows. Via Giuliano Liguori -
AI Agents Have Three Memory Layers: Working Memory
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You use AI agents every day.
ChatGPT, Claude, Gemini, Cursor. They remember what you said, who you are, and what you've worked on before. But this memory has three layers, not one. Working memory
Your current chat. Whatever you typed five messages ago. Gone when you close