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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TRIBE v2: Meta’s Trimodal Brain Encoder Creates Neural Digital Twins
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Meet TRIBE v2: A Trimodal Brain Encoder Creating #Digital Twins of Neural Activity
— Ronald van Loon (@Ronald_vanLoon) 27 mai 2026
by @AIatMeta
#NeuralNetworks #FutureTech #Innovation #DeepLearning #AI pic.twitter.com/nXueGRFIxTMeet TRIBE v2: A Trimodal Brain Encoder Creating #Digital Twins of Neural Activity
by @AIatMeta #NeuralNetworks #FutureTech #Innovation #DeepLearning #AI -
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 -
Side-by-Side Interleaved Reasoning lets AI think silently before sharing certainties
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Your AI could think silently before speaking—and only share what it’s certain of! Researchers from Zhejiang University, William & Mary, UIUC, UBC, CUHK, Fudan, and Stony Brook University introduce Side-by-Side (SxS) Interleaved Reasoning. Instead of forcing every thought into
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Codex allocates 2% context, warns when adding skills
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Problem is that codex gives me 2% of my context so random stuff adding skills gives me warning messages.
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Claude Code Harness: Fixing AI Coding Session Breakdowns
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You won't run Claude Code the same way after this. AI coding sessions often fall apart the same way. You ask for a feature, nine files get edited, something silently breaks. Claude Code Harness wraps the model in a real delivery loop. It forces a strict cycle before any
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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