Tagged articles

Agent Coordination

14 articles · Page 1 of 1

Sep 11, 2026 · Artificial Intelligence

Graph Engineering Restructures Agent Systems: From Harness to Ontology

This article reviews a 2026 paper on Graph Engineering for LLM agents, detailing the shift from individual agent intelligence to system intelligence via explicit task DAGs, runtime state management with checkpoints and replay, multi-agent coordination through capability modeling, and ontology engineering for shared semantics.

Agent CoordinationDAG SchedulingGraph Engineering

0 likes · 20 min read

Graph Engineering Restructures Agent Systems: From Harness to Ontology

DataFunTalk

Sep 9, 2026 · Artificial Intelligence

Graph Engineering Restructures Agent Systems: From Harness to Ontology

A 2026 survey paper introduces Graph Engineering as the next phase for LLM agents, shifting focus from individual model capabilities to system-level organization via explicit task DAGs, runtime state management with provenance and recovery, capability-based agent coordination, and a graph-native control plane that treats tasks, agents, and state as first-class system objects.

Agent CoordinationDAG SchedulingGraph Engineering

0 likes · 22 min read

DataFunTalk

Sep 7, 2026 · Artificial Intelligence

Graph Engineering Rebuilds Agent Systems: From Harness to System Intelligence

A 2026 survey paper introduces Graph Engineering as the system layer that organizes LLM agents into reliable multi-agent workflows through explicit DAGs, runtime state management, fault tolerance, and a control plane, shifting focus from individual agent capabilities to system-level engineering.

Agent CoordinationDAG SchedulingFault Tolerance

0 likes · 21 min read

Graph Engineering Rebuilds Agent Systems: From Harness to System Intelligence

Architects Research Society

Sep 3, 2026 · Artificial Intelligence

Harmovela: Async Coordination Protocol Complementing MCP for Agent Systems

Harmovela is an open coordination protocol that complements MCP by handling asynchronous, incremental, and replayable continuous coordination across agents, tools, memory, and runtimes, covering seven dimensions including events, tasks, state, context, delegation, recovery, and governance, with multi-language implementations and transport bindings.

AI infrastructureAgent CoordinationHarmovela

0 likes · 6 min read

Harmovela: Async Coordination Protocol Complementing MCP for Agent Systems

Geek Labs

Aug 30, 2026 · Artificial Intelligence

Cumora: Turning AI Agents into First-Class Team Members for Collaborative Work

Cumora is an open‑source, cross‑platform team chat platform that treats AI agents as equal members, giving them persistent personas, memory, proactive task claiming, inter‑agent coordination, and real email capabilities, while offering cloud‑hosted and BYOA modes and detailed conflict‑avoidance mechanisms.

AI agentsAgent CoordinationBYOA

0 likes · 12 min read

Cumora: Turning AI Agents into First-Class Team Members for Collaborative Work

TonyBai

Aug 2, 2026 · Artificial Intelligence

Google Study: 260 Experiments Show When Multi‑Agent AI Helps or Hurts

Google Research and MIT conducted 260 controlled experiments across five architectures, three model families, and six benchmarks, discovering that multi‑agent systems boost performance up to 81 % on parallelizable tasks but can degrade it by up to 70 % on strictly sequential tasks, and they built a predictor that selects the optimal architecture with 87 % accuracy.

AI architectureAgent Coordinationmulti-agent systems

0 likes · 12 min read

Google Study: 260 Experiments Show When Multi‑Agent AI Helps or Hurts

Machine Heart

Jun 5, 2026 · Artificial Intelligence

How to Use Claude Code’s Dynamic Workflows: Practical Tips from the Team

Claude Code’s new dynamic workflow feature lets you generate custom execution frameworks that coordinate multiple sub‑agents, avoid common failure modes, and handle large‑scale, high‑parallel or adversarial tasks, with detailed patterns, use‑cases, and best‑practice guidance from Anthropic engineers.

AI automationAgent CoordinationClaude Code

0 likes · 15 min read

How to Use Claude Code’s Dynamic Workflows: Practical Tips from the Team

ShiZhen AI

Mar 11, 2026 · Artificial Intelligence

Build Persistent AI Agents with OpenClaw: A 40‑Day Hands‑On Guide

This article details a 40‑day workflow for creating and evolving eight continuous‑running OpenClaw AI agents using a three‑layer markdown file system—Identity, Operations, and Knowledge—showing how to give agents long‑term memory, self‑healing checks, and coordinated collaboration without databases or message queues.

AI agentsAgent CoordinationLong-Term Memory

0 likes · 17 min read

Build Persistent AI Agents with OpenClaw: A 40‑Day Hands‑On Guide

phodal

Feb 24, 2026 · Artificial Intelligence

How Routa Turns Multi‑Agent AI Coding into an Engineered Collaboration Framework

Routa is an engineering‑focused multi‑agent framework that separates tasks, state, events, and execution into controllable modules, enabling open‑ecosystem AI coding agents to collaborate through structured specifications, event‑driven coordination, and verifiable tool interfaces rather than fragile prompt stitching.

AI collaborationAgent CoordinationRouta

0 likes · 12 min read

How Routa Turns Multi‑Agent AI Coding into an Engineered Collaboration Framework

AI Tech Publishing

Feb 23, 2026 · Artificial Intelligence

Final Lesson: Build a Fully Working RSS News Brief Agent

In this final lesson of a nine‑day Agent engineering series, the author integrates the full Agent Loop, tools, MCP, skills, RAG, context handling, multi‑turn dialogue, and multi‑agent coordination to create a runnable RSS news‑briefing Agent that fetches feeds in parallel, filters content with LLMs, summarizes articles, and outputs a markdown report.

Agent CoordinationLLMParallel Fetching

0 likes · 12 min read

Final Lesson: Build a Fully Working RSS News Brief Agent

Fun with Large Models

Jan 5, 2026 · Artificial Intelligence

LangGraph Agent Design Patterns Part 3: Supervisor and Hierarchical Architectures

This article explains LangGraph's multi‑agent design patterns, focusing on the Supervisor Architecture for centralized coordination and the Hierarchical Architecture for scalable team‑based management, and provides step‑by‑step code examples that demonstrate how to implement both patterns.

AI agentsAgent CoordinationCode Example

0 likes · 21 min read

LangGraph Agent Design Patterns Part 3: Supervisor and Hierarchical Architectures

AI Frontier Lectures

Nov 13, 2025 · Artificial Intelligence

How Graphs Empower LLM Agents: A Deep Dive into GLA

This article reviews the IEEE Intelligent Systems survey that introduces Graph‑augmented LLM Agents (GLA), explains how representing plans, memory, tools and multi‑agent interactions as graphs improves reliability, efficiency, interpretability and flexibility, and outlines five key research directions for future development.

Agent CoordinationLLM Agentsknowledge graphs

0 likes · 8 min read

How Graphs Empower LLM Agents: A Deep Dive into GLA

Data Party THU

Sep 8, 2025 · Artificial Intelligence

5 Proven AI Agent Orchestration Patterns and When to Use Them

The article analyzes five mainstream AI agent orchestration patterns—sequential, MapReduce, consensus, hierarchical, and creator‑checker—detailing their workflows, suitable scenarios, advantages, and limitations, and explains why orchestration remains valuable even as large language models advance.

AI orchestrationAgent CoordinationArtificial Intelligence

0 likes · 9 min read

5 Proven AI Agent Orchestration Patterns and When to Use Them

Fighter's World

Jun 21, 2025 · Artificial Intelligence

Speculating Devin’s Context Engineering Architecture: How Long‑Horizon Agents Preserve Complete Context

The article analyzes why context engineering is crucial for multi‑agent AI systems, illustrates the fragility caused by fragmented context with a Flappy Bird analogy, and proposes three detailed speculative components—a compression‑to‑structure pipeline, a hybrid layered memory architecture, and a context‑aware coordination mechanism—culminating in a unified reference design for long‑horizon agents.

Agent CoordinationCompression PipelineHybrid Memory

0 likes · 22 min read

Speculating Devin’s Context Engineering Architecture: How Long‑Horizon Agents Preserve Complete Context