here's a fragment of a diligence run putting several primitives together. claims arrive. system requests evidence for low-confidence ones. a contradiction is detected. contradiction triggers a patch. all tracked this uses: objects, relations, behaviors, relation behaviors,
SYSTEMS
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Graph-Based Architecture for AI Agent Knowledge and Behavioral State Management
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the core concept is a graph that represents everything about the agents knowledge, history, behaviors, capabilities graph is made of events
behaviors react to graph changes
relationships can carry behaviors
patch & propose to edit graph
views are scoped view of graph
frames are -
Architecting State Layers for Long-Running AI Agent Coordination
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current agent systems coordinate through conversations and workflows. Active Graph explores what happens when agents coordinate through evolving shared state instead this proposal suggests that long-running agents need a proper state layer with: types, persistent, reactive,
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Core components of agentic AI: from thinking to doing
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Agentic AI = systems, not models • Intelligence (LLMs)
• Memory
• Tools
• Feedback loops That’s how AI moves from thinking → to doing Via Giuliano Liguori (
@ingliguori
) #AI #AIAgents #AgenticAI -
30 Agents Every AI Engineer Must Build – production-ready agents
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
Building Complex Multi-Agent Systems for App Development and Automation
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🚨 Agent Swarms – Multi-Agents Delegate Complex Prompts To Sub-Agents
— Abacus.AI (@abacusai) 20 mai 2026
Use Gemini 3.5 Flash, Opus 4.7 and GPT 5.5 xHIgh to create complex multi-agent system
A master agent can orchestrate several worker agents to just do things
Build full-stack apps, mobile apps and automate… pic.twitter.com/5IDAvesIgwAgent Swarms – Multi-Agents Delegate Complex Prompts To Sub-Agents Use Gemini 3.5 Flash, Opus 4.7 and GPT 5.5 xHIgh to create complex multi-agent system A master agent can orchestrate several worker agents to just do things Build full-stack apps, mobile apps and automate
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Google’s AI Agents Build Working Operating System in 12 Hours
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Google's Antigravity 2.0 built the core framework of a working operating system in 12 hours, spinning up 93 sub-agents and processing billions of tokens for under $1,000 in compute costs.
— Chubby♨️ (@kimmonismus) 20 mai 2026
On stage, the team booted Doom on the AI-built OS.
Just imagine all the possibilities in… pic.twitter.com/yT2RffsjrwGoogle's Antigravity 2.0 built the core framework of a working operating system in 12 hours, spinning up 93 sub-agents and processing billions of tokens for under $1,000 in compute costs. On stage, the team booted Doom on the AI-built OS. Just imagine all the possibilities in
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Supercomputer runs Gemini, video AI leaps forward
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Le superordinateur Higgsfield tourne maintenant sur Gemini.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 19 mai 2026
Texte plus précis. Motion cinématique. Contrôle image par image.
Recherche alimentée par une connaissance globale réelle.
C'est complètement dingue !
L'IA vidéo vient de changer de niveau. pic.twitter.com/1WMJ0rZMkDLe superordinateur Higgsfield tourne maintenant sur Gemini. Texte plus précis. Motion cinématique. Contrôle image par image. Recherche alimentée par une connaissance globale réelle. C'est complètement dingue ! L'IA vidéo vient de changer de niveau.
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Google launches Gemini 3.5 Flash, a step toward digital employees
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Google acaba de lanzar Gemini 3.5 Flash.
— Nico (@nicos_ai) 19 mai 2026
Y estamos mucho más cerca de los primeros empleados digitales reales.
→ planifica tareas complejas durante horas
→ divide el trabajo entre subagentes
→ trabaja sobre codebases enormes
→ usa herramientas y ejecuta acciones
→… https://t.co/L2qsKVSqDS pic.twitter.com/wBsqThLNTsGoogle has just launched Gemini 3.5 Flash. And we're much closer to the first truly real digital employees. → plans complex tasks for hours → divides work among subagents → works on massive codebases → uses tools and executes actions → maintains massive context
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Google announces Gemini 3.5 Flash as fast, capable model
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Highly capable models that are fast are super important. Our new Gemini 3.5 Flash model is a great mix of fast and capable.