Tag
multi-agent systems
Multi-agent systems split planning, tool use, and verification across roles, making them useful for long-running tasks, scientific workflows, and automation. The trade-offs are coordination cost, context pollution, and token use, which is why recursive designs, harness engineering, and adaptive pipelines matter.
10 articles
Aspire ties Microsoft Agent Framework into one app graph
Aspire now models Foundry, specialist agents, voice, chat, and Cosmos DB in one distributed app graph you can run and trace.
Agent orchestration is the missing layer for enterprise AI
Agent orchestration coordinates multiple AI agents so enterprises can control handoffs, governance, and production workflows.
SPIRE brings evidence-grounded AI to humanities research
SPIRE uses a multi-agent workflow to ground humanities essays in primary sources more reliably.
Code Becomes the Agent Harness
This survey reframes code as the runtime layer that connects agent reasoning, actions, memory, and verification.
What LLM-only social networks reveal
A study of a Facebook-like platform filled with LLM agents analyzes 184,203 posts and 465,136 comments to map emergent social behavior.
Recursive Multi-Agent Systems Could Cut Token Use
RecursiveMAS treats a whole multi-agent setup as one recursive latent computation, reporting 8.3% accuracy gains and big token savings.
Free AI Agent Resources Worth Bookmarking
A curated GitHub hub for AI agents packs beginner courses, code labs, and frameworks from Microsoft, LangChain, OpenAI, and more.
Harness Engineering for Long-Running Multi-Agent Systems
A context-reset design keeps each Claude Code run clean, turning Planner output into JSON so Generator stays focused on the task.
Mimosa builds evolving multi-agent science workflows
Mimosa auto-builds and refines scientific agent workflows, aiming to beat rigid pipelines with adaptive tool use and logged execution traces.
OpenAI backs Isara’s agent-swarm bet
OpenAI joined a $94M round for Isara, a nine-month-old startup at a $650M valuation, betting on multi-agent AI at scale.