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Plasma__AI launches Radio, a shared chat room tool that enables multiple AI coding agents to coordinate and sync in real-time, simplifying the management of agent teams.
This study explores how LLMs behave in game theory scenarios requiring coordination, revealing that communication among agents can increase rebellion tendencies and that adversarial surveillance reduces participation.
The author replaced a file-based agent handoff system with a self-hosted message board using SQLite, tested it in a real task, and documented failure points.
NanoClaw, an open-source and self-hosted tool for creating and coordinating multiple AI agents, has been integrated into Slack. This allows users to spawn specialized agents for various tasks directly from a single message.
JarvisBench introduces a benchmark for evaluating the coordination between humans and AI agents, focusing on attention allocation in long-horizon tasks. It provides a reference implementation with a full-duplex speech interface.
The article discusses the need for a semantic coordination layer to enable multi-agent systems to collaborate effectively, and introduces Outshift's 'Internet of Cognition' and the open-source project AGNTCY as steps toward distributed artificial superintelligence.
The author describes building Manciple, a coordination layer that manages multiple coding agents (like Claude Code, Codex, OpenCode) to prevent conflicts and overlaps, enabling autonomous completion of scoped tasks.
Cotal is an open standard for AI agent coordination that allows configurable topologies (peer-to-peer, supervised, hierarchical, or hybrid) using NATS messaging, complementing existing protocols like MCP and A2A.
Evo ported its autoresearch loop onto Anthropic's dynamic workflows in Claude Code, moving orchestration from in-context memory to deterministic JavaScript, solving long-horizon instruction adherence and enabling self-evolving workflows.
This paper proposes an 'agent economy' framework inspired by Hayek's economic theory, where agents self-organize through auction-based competition and economic selection to produce emergent multi-step reasoning and collective intelligence without centralized control. The system outperforms stronger monolithic baselines across five agentic tasks including mathematical reasoning, financial research, and scientific research.
The article argues that AI agent coordination failures stem from missing commitment records, not lack of context, and proposes a shared decision ledger with typed states (Proposed, Active, Amended, Superseded) to durable record decisions and improve multi-agent coordination.
AvailSync is a small MCP tool that prevents multiple AI coding agents from conflicting by checking repo availability before allowing an agent to start working.
This article introduces TeamBench, a benchmark for evaluating agent coordination under enforced role separation, addressing issues where prompt-only roles may bypass intended constraints.