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Agentic systems aren’t just for enterprises. As Humayun (Humayun) puts it: agents represent processes, software, even people, but the key shift is autonomy. Not just automation, but agents that can make decisions using context, history, and intent. The real unlock? Multi-agent systems, where different agents interact across environments, orgs,...

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Fetch.ai

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17,636 просмотров • 7 месяцев назад •via X (Twitter)

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EIP-8004 is coming to the Nova architecture, a trustless infrastructure for AI agents that introduces key on-chain registries, enabling agents to interact safely across the Shido Network. These core components allow autonomous AI agents to verify identity, build reputation, and collaborate without relying on a centralized platform. The result is a decentralized trust layer for agent-to-agent economies, where agents can autonomously discover, evaluate, and work with one another across the Shido ecosystem.

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The real power of AI agents is collaboration. Box CTO Ben Kus joins LangChain CEO Harrison Chase to discuss what the future looks like when AI systems can work more like teammates than just assistants. Timestamps: 00:52 - Harrison's path to starting LangChain 01:54 - The different definitions of AI agents 03:16 - How agentic systems differ from traditional automation 06:20 - The evolution of AI agents 13:06 - The impact of deep research 17:22 - Deep agent capabilities and benefits 22:16 - How to recognize different modes 25:25 - The future of evaluation

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Ohans Emmanuel

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Computer use agents are slow and brittle. The fix isn’t just stronger models, but also deploying them as multi-agent systems. MACU is a general Multi-Agent Computer Use framework that consistently lifts success rates by 3.4-25.5% and is up to 1.5x faster on long-horizon tasks.🧵
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Computer use agents are slow and brittle. The fix isn’t just stronger models, but also deploying them as multi-agent systems. MACU is a general Multi-Agent Computer Use framework that consistently lifts success rates by 3.4-25.5% and is up to 1.5x faster on long-horizon tasks.🧵

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The SaaSpocalypse narrative is starting to make less and less sense. Software companies like $PLTR, $NOW, and $CRM are getting punished because investors believe AI will replace SaaS. Jensen Huang disagrees. “Claude can write software.” That’s true. But Jensen argues that enterprises aren’t going to build their own software. They’re going to deploy AI agents that use software tools to get work done. “Agents won’t replace tools. Agents will use tools.” NVIDIA is already seeing this happen. According to Jensen, the company has deployed so many AI agents that tool usage is actually increasing. That’s the exact opposite of the SaaSpocalypse thesis.

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