Agentic AI isn’t about learning 10 steps. It’s about mastering 4 loops: Perception → Memory → Planning → Action. Frameworks change. Autonomy principles don’t. Build agents that think in systems, not prompts.
SYSTEMS
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Multi-Agent Systems: Do Homogeneous Agents Really Improve Performance?
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Are multi-agent systems necessary? Here is a great new paper addressing this. The big assumption most AI devs make today is that more agents lead to better performance. But here is the overlooked reality: most multi-agent systems are homogeneous. All agents typically share
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Agentic AI: Beyond Chatbots – A Complete System Architecture
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Agentic AI isn’t a smarter chatbot. It’s a system: Inputs → Reasoning → Memory → Planning → Action → Feedback. If it can’t act, learn, and adapt — it’s not agentic.
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Team Achieves Impressive PostgreSQL Scaling Success
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the team has done an incredible job of scaling postgres:
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Multi-Agent Systems: The Future of Connected Intelligence
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Kai-Fu Lee (founder of Sinovation Ventures) explains how the future is all about multi-agent systems.
— Rohan Paul (@rohanpaul_ai) 23 janvier 2026
1 agent today is like a pre-internet PC, useful but isolated. Connect agents, and they share context, split tasks, and coordinate instantly.pic.twitter.com/RpquPA7pIQKai-Fu Lee (founder of Sinovation Ventures) explains how the future is all about multi-agent systems. 1 agent today is like a pre-internet PC, useful but isolated. Connect agents, and they share context, split tasks, and coordinate instantly.
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Raleigh Uses AI Vision and Digital Twins for Safer Streets
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.@RaleighGov is proving how fast-growing cities can turn real-time AI into safer streets and smoother mobility.
— NVIDIA AI (@NVIDIAAI) 21 janvier 2026
By combining vision AI, digital twins, and AI agents, the city is transforming traffic management and urban response:
🚦 95% accurate vehicle detection to improve… pic.twitter.com/ZcdxjPYRwE.
@RaleighGov is proving how fast-growing cities can turn real-time AI into safer streets and smoother mobility. By combining vision AI, digital twins, and AI agents, the city is transforming traffic management and urban response: 95% accurate vehicle detection to improve -
Productivity: Systems Over Prompts for Sustained Execution
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Productivity prompts don’t create productivity. They create clarity — once. The real leverage: • habits
• systems
• feedback loops AI helps you think faster.
Only systems help you execute better. -
Context Breakdown: The Hidden Challenge in AI Systems at Scale
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Most AI systems don’t fail because of bad prompts.
They fail because context breaks at scale. If you’re building AI agents, LLM workflows, copilots, or automation, this is the layer that quietly decides whether your system is reliable or unpredictable. We’re hosting a 5-hour, -
Databricks Co-founders Speaking at Scaled ML 2026 Conference
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Databricks co-founders @matei_zaharia and @istoica05 will be speaking at #ScaledML 2026! This event brings together the creators behind systems like Apache Spark™, CUDA, TensorFlow, ImageNet, Tesla FSD, and more to explore large-scale learning, distributed systems, and next-generation AI hardware. Join us on January 29th: scaledml.org/
→ View original post on X — @reza_zadeh, 2026-01-20 20:10 UTC
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Hand Gesture Recognition Transforms Workspace Productivity
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What if your desk could understand your hand gestures? Carlo’s #SmarterSpaces project will test hand-pose detection on Metis to trigger intuitive “super commands”, like screenshots or OCR. A playful, powerful upgrade for the workspace. Follow along: https://
eu1.hubs.ly/H0qHV9r0