Multi-model for deep research makes sense. Curious how it picks which model for what, or if users control the routing.
AGENTS
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Top AI Stories: Sora, Claude, Perplexity, and Stanford Research
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Top stories in AI today: – Inside Sora's $1M-a-day collapse at OpenAI
– Microsoft pits Claude against ChatGPT for research
– Build a travel itinerary with Perplexity Computer
– Stanford exposes AI's people-pleasing problem
– 4 new AI tools, community workflows, and more -
Agent Economics: Ownership and Reputation Rights
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Agents as economic actors is the inevitable next step. The question is who owns the agent's output and reputation.
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AI Review Bots Superior to Human Security Review
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this customer got notified 45 mins after attack, 1.5 hours before announcement of the attack. Generalist coding agent is also a better security reviewer than you! there is basically 0 reason not to have a Review bot enabled for all the things. it’s not just a security thing,
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Scaling Speed and Trust: AI Governance in the Modern Era
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How do we build systems where speed and trust can scale together?
— Helen Yu (@YuHelenYu) 31 mars 2026
I explored this with @MichaelLeland, field CTO of #island at RSA and it’s the challenge of the AI era.
AI is now an actor. Fast, boundaryless, and creating risks most orgs don’t yet see (hello, shadow AI +… pic.twitter.com/1WfASpKGtKHow do we build systems where speed and trust can scale together? I explored this with @MichaelLeland, field CTO of #island at RSA and it’s the challenge of the AI era. AI is now an actor. Fast, boundaryless, and creating risks most orgs don’t yet see (hello, shadow AI + agents). We unpack: • AI governance where work happens • “No” → “Yes, but” security • AI-first architecture 👉 Watch: piped.video/GT5M1CQ4J54 Check out demos of Island's new AI products here: island.io/ai/?utm_medium=pai… #RSAC #Cybersecurity #AI #Governance #IslandPartner #RiskManagement
→ View original post on X — @yuhelenyu, 2026-03-31 06:34 UTC
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Meta-Harness: Optimizing LLM Model Harnesses End-to-End
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"Meta-Harness: End-to-End Optimization of Model Harnesses" A big portion of agentic LLM performance relies on human-designed harness around the model, not just the weights. On top of that, how well a harness is designed could impact a model's performance heavily. So this paper
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Open Source Maintainer Struggles with AI Agent Adoption Gap
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You don’t realize how hard this is. I have over 40 maintainers now and still ship over 70% of commits. Gap with agentic use is very high.
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Multi-Agent Architecture: CC Hands Off Tasks to Codex
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they are both still used in their own harnesses, that’s the whole reason why this is effective. CC can hand off an issue to codex to work on in its own harness!
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Microsoft Copilot Frontier Model Council Compares AI Responses Side by Side
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🚨Microsoft just dropped Copilot Cowork in Frontier; and the new Model Council feature is wild
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 31 mars 2026
Inside Researcher, you can now compare responses from multiple AI models side by side:
→ See where they agree
→ See where they diverge
→ Get what each uniquely brings
Like having… pic.twitter.com/E7ZYvzOphMMicrosoft just dropped Copilot Cowork in Frontier; and the new Model Council feature is wild Inside Researcher, you can now compare responses from multiple AI models side by side:
→ See where they agree
→ See where they diverge
→ Get what each uniquely brings Like having -
Best Platforms for AI Agents
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Best Platforms for #AIAgents
by @Python_Dv #AI #LLM #ArtificialIntelligence #MachineLearning #ML