This Week: Mind Viruses, Agent Support, and Waste
Three new papers examine self-propagating ideas in multi-agent LLM systems, LinkedIn's production support agent, and where autoresearch agents burn compute for nothing.
Articles Tagged "Multi-Agent"
Model Steering, Angry Buyers, and Blind Judges
New arXiv papers map how frontier models resist behavioral steering differently, how prompted emotions wreck LLM price negotiations, and why judge-panel verification only helps on the closest calls.
Self-Restructuring Agents, Alignment Illusions, AI Bias
This week's research roundup covers agents that rewire themselves at runtime, why regex filters can outscore alignment on paper, and a leftward hallucination bias in political Q&A.
Devin Desktop Review: Windsurf Becomes an Agent Hub
Cognition rebranded Windsurf as Devin Desktop and rebuilt it around a Kanban board for managing fleets of coding agents - here's what that actually changes.
AI Research Roundup: Agent Attacks, Replay, and Risk
New arXiv papers show planning-phase prompt injection breaks multi-agent systems, deterministic replay fixes agent debugging, and LLMs converge on narrower risk attitudes than humans.
Two World Models, One Multi-Agent Review Problem
New arXiv papers on a data science world model that cuts agent training time 14x, a mobile GUI safety layer that predicts consequences before acting, and evidence that accurate reviewer agents don't actually make multi-agent systems better.
How AI Agents Break - Plus Fixes for Memory and Tools
Three arXiv papers map how LLM agents fail across 19 benchmarks, show in-process memory cuts retrieval latency 1,000x, and reveal steering vectors that control tool invocation.
Agent Languages, Sampling Ceilings, and Abstention
Three new papers on agents inventing symbolic languages to cut reasoning tokens by 3-6x, sampling ceilings that waste inference compute, and context-engineering to double agentic abstention rates.
Tandem Training, World Models, and Efficient Agents
Three new arXiv papers on making RL reasoning legible across models, fixing broken world model latent states, and training small agents to beat their teachers.
DeepMind Maps Four Routes from AGI to Superintelligence
A 57-page DeepMind paper by co-founder Shane Legg identifies four pathways from AGI to superintelligence and six bottlenecks that could block each route.
Sakana Fugu
Sakana AI's orchestrator model that dynamically coordinates Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro to beat each of them individually on SWE-Bench Pro, GPQA-Diamond, and eight other benchmarks.
AI Research: Orchestration Beats Scale, Small Models Win
Sakana Fugu tops SWE-Bench Pro by routing tasks across rival LLMs, Microsoft's 9B browser agent beats OpenAI Operator, and a 3B model from Weibo matches DeepSeek V3.2 on math.
