Shared language =/= shared meaning. And that can turn multi-agent systems into a game of telephone without any human in the loop being the wiser. Our @MicrosoftAI pre-print tests a solve: if agents don't agree on a definition, they can't use the term. The results: disagreement
AGENTS
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Richmond Alake teaches multi-agent systems at London ExCel Centre
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London has many wonderful things. The ExCel Centre isn't one of them. BUT…watching @richmondalake teach developers how to build their first multi-agent system *is* awesome, no matter where it's taking place (or however awkwardly shaped the room 😬).
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LangChain Showcases New Ecosystem Features at Google Cloud Next
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We’ll be at Google Cloud Next! If you’re attending, stop by Booth #5006 to see what’s new across the LangChain ecosystem: LangSmith for agent observability, evaluation, and deployment
LangSmith Studio for visual agent development
LangSmith Fleet for building agents with natural -
Intelligent Agents: Natural Language Automation Across Systems
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Enter intelligent agents (the practical layer): Ask in natural language. The agent pulls context across systems, then acts—send an alert, generate a report, flag an anomaly. Result → faster cycles, clearer visibility, and automation you can trust across existing
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Product Development Reimagined: PMs, Designers, and AI Agents
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The rules of professional product development are being rewritten in real time.
— Dan Shipper 📧 (@danshipper) 25 mars 2026
– PMs and designers can ship software as easily as engineers.
– Software is no longer just built for humans—it’s also built for agents as first-class citizens.
To better understand how we build… pic.twitter.com/9Ak63l1MljThe rules of professional product development are being rewritten in real time. – PMs and designers can ship software as easily as engineers.
– Software is no longer just built for humans—it’s also built for agents as first-class citizens. To better understand how we build -
DiscoveryPrime Turns Work Into Global Intelligent Labor Tournament
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DiscoveryPrime: Turning Work into a Global Tournament for Intelligent Labor A New Arena for the Future of Work : https://
linkedin.com/pulse/discover
yprime-turning-work-global-tournament-labor-vincent-boucher-lfdoe/
… #AGIALPHA #AIAgents #Jobs -
Learning Mechanisms Differentiate AI From Static Tool Libraries
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Yeah the learning mechanism is what separates this from static tool libraries
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Self-Evolving Agents: The Future of AI Technology
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Rightly said, I think self-evolving agents are the future.
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Snorkel AI Hiring ML Training Infrastructure Engineer for RL Scaling
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Scaling RL training for agentic models is one of the hardest infra problems in ML right now and honestly, one of the most exciting jobs🔥 Our research team @SnorkelAI is deep in RLFT (data valuation, curriculum learning, and more). We're #hiring an ML Training Infra engineer who's actually done this at scale with complex environments and medium sized models. If that sounds like you (or someone you know), DM me or drop a comment 👇 #MLJobs | Link in thread
→ View original post on X — @snorkelai, 2026-03-25 14:25 UTC
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Self-Evolving Agent Framework Learn Failures Rewrite Skills
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Let Agents Design Agents Memento-Skills is a self-evolving agent framework where agents learn from failures and rewrite their own skills. Most agent frameworks treat skills as static. You write them once, load them into context, and hope they work. When they fail, you debug