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Lineage: ContentType.Item -> ContentType.MailSource Library - new sources scavenged (2026-06-15)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged (2026-06-15) | (synthesis unavailable) ### Merged sources (16 raw hits across 3 engine(s) -> 16 unique, ranked by cross-engine agreement) A Comparative Study of AI Agent Orchestration Frameworks | by Kiumarse Zamanian, PhD | Medium https://medium.com/@kzamania/a-comparative-study-of-ai-agent-orchestration-frameworks-f61cd49b687e A Comparative Study of AI Agent Orchestration Frameworks | by Kiumarse Zamanian, PhD | Medium Sign up Get app Sign up # A Comparative Study of AI Agent Orchestration Frameworks 16 min read Nov 24, 2024 -- 1 Shar... [1 engine(s): Exa] Multi-Agent System Best Practices for AI Engineers | Aishwarya Srinivasan posted on the topic | LinkedIn https://www.linkedin.com/posts/aishwarya-srinivasan_if-you-are-an-ai-engineer-trying-to-deeply-activity-7409456919750545408-Ap8a [Sign in](https://www.linkedin.com/login?session_redirect=https%3A%2F%2Fwww%2Elinkedin%2Ecom%2Fposts%2Faishwarya-srinivasan_if-you-are-an-ai-engineer-trying-to-deeply-activity-7409456919750545408-Ap8a&fromSignIn=true&trk... [1 engine(s): Tavily] What is AI Orchestration? 21+ Tools to Consider in 2025 https://akka.io/blog/ai-orchestration-tools What is AI Orchestration? 21+ Tools to Consider in 2025 # What is AI orchestration? 21+ tools to consider in 2025 20 minute read April 30, 2025 Artificial intelligence (AI) has moved from a futuristic concept to an es... [1 engine(s): Exa] Building High-Quality AI Agent Systems: Best Practices https://www.pondhouse-data.com/blog/high-quality-ai-agent-systems Multi-agent systems built with Large Language Models (LLMs) have emerged as an architectural approach for addressing complex tasks through coordinated agent collaboration. Recent research published in a paper called "Why... [1 engine(s): Tavily] Kocoro-lab/Shannon https://github.com/kocoro-lab/shannon # Repository: Kocoro-lab/Shannon A production-oriented multi-agent orchestration framework. - Stars: 1982 - Forks: 313 - Watchers: 16 - Open issues: 0 - Primary language: Go - Languages: Go (45.6%), Python (32.1%), Typ... [1 engine(s): Exa] Best practices for building effective AI agents and multi-agent systems https://medium.com/online-inference/best-practices-for-building-effective-ai-agents-and-multi-agent-systems-2c7fe11c9605 # Best practices for building effective AI agents and multi-agent systems | by Dave Davies | Online Inference | Apr, 2026 | Medium. # Best practices for building effective AI agents and multi-agent systems. The strongest... [1 engine(s): Tavily] mainframecomputer/orchestra https://github.com/mainframecomputer/orchestra # Repository: mainframecomputer/orchestra Cognitive Architectures for Multi-Agent Teams - Stars: 754 - Forks: 69 - Watchers: 10 - Open issues: 2 - Primary language: Python - Languages: Python - License: Other (NOASSERT... [1 engine(s): Exa] The Compounding Errors Problem: Why Multi-Agent Systems Fail ... https://www.zartis.com/the-compounding-errors-problem-why-multi-agent-systems-fail-and-the-architecture-that-fixes-it The Compounding Errors Problem: Why Multi-Agent Systems Fail and the Architecture That Fixes It. ***Disclaimer:*** *The best practices and architecture we are about to explain is not theoretical. This article was deliber... [1 engine(s): Tavily] dapr/dapr-agents https://github.com/dapr/dapr-agents # Repository: dapr/dapr-agents Build autonomous, resilient and observable AI agents with built-in workflow orchestration, security, statefulness and telemetry. - Stars: 691 - Forks: 124 - Watchers: 24 - Open issues: 24... [1 engine(s): Exa] Multi-agent systems fault line: Why enterprise systems fail https://www.kore.ai/blog/multi-agent-systems-fault-line The AI-programmable foundation for building, scaling, and optimizing AI agents that work in production. ###### For Work. Find the right AI use case for your business. What's new in AI for Work: features that drive enterp... [1 engine(s): Tavily] AWS Releases ‘Multi-Agent Orchestrator’: A New AI Framework for Managing AI Agents and Handling Complex Conversations - AI Tools & Software - oTTomator Community https://thinktank.ottomator.ai/t/aws-releases-multi-agent-orchestrator-a-new-ai-framework-for-managing-ai-agents-and-handling-complex-conversations/1046 AWS Releases ‘Multi-Agent Orchestrator’: A New AI Framework for Managing AI Agents and Handling Complex Conversations - AI Tools & Software - oTTomator Community # AWS Releases ‘Multi-Agent Orchestrator’: A New AI Frame... [1 engine(s): Exa] How and when to build multi-agent systems - LangChain https://www.langchain.com/blog/how-and-when-to-build-multi-agent-systems # How and when to build multi-agent systems. “Don’t Build Multi-Agents” by the Cognition team, and “How we built our multi-agent research system” by the Anthropic team. Despite their opposing titles, I would argue they a... [1 engine(s): Tavily] 10 Best AI Agent Orchestration Tools in 2026 | Rasa | Rasa Blog https://rasa.com/blog/agent-orchestration-tools 10 Best AI Agent Orchestration Tools in 2026 | Rasa | Rasa Blog # 10 Best AI Agent Orchestration Tools in 2026 Posted May 18, 2026 Updated No items found. Single-agent demos are easy. The hard part of agentic AI is ... [1 engine(s): Exa] How do you optimize a multi agent system to avoid redundant work ... https://www.reddit.com/r/softwarearchitecture/comments/1u129df/how_do_you_optimize_a_multi_agent_system_to_avoid Dive into discussions on designing, structuring, and optimizing software systems. Share insights on architectural patterns, best practices, and [1 engine(s): Tavily] anote-ai/Autonomous-Intelligence https://github.com/anote-ai/Autonomous-Intelligence # Repository: anote-ai/Autonomous-Intelligence Autonomous Intelligence is a framework for building collaborative, intelligent multi agent AI systems. The framework provides a robust infrastructure for creating and manag... [1 engine(s): Exa] Are Your Multi-Agent Systems Failing for These 7 Reasons? | Galileo https://galileo.ai/blog/why-multi-agent-systems-fail # Why Do Multi-Agent Systems Fail Even When Agents Work Perfectly in Isolation? Are Your Multi-Agent Systems Failing for These 7 Reasons? On the other hand, research from top labs such as Anthropic suggests that simply a... [1 engine(s): Tavily] --- Fact-check --- Since no briefing was provided for analysis, I cannot perform fact-checking on claims that don't exist. The sources provided contain various information about AI agent orchestration frameworks, best practices, and tools, but without a specific briefing to evaluate against these sources, I cannot determine support, silence, or contradiction. **Unsupported Claims:** All claims (none provided) **Overall Confidence: N/A** (No briefing content to evaluate) Researched 3 source set(s) across 3 angle(s). Confidence: Low | 2026-06-15T19:24:17.1989731 | ||||
Source Library - new sources scavenged (2026-06-15)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged (2026-06-15) | (synthesis unavailable) ### Merged sources (16 raw hits across 3 engine(s) -> 16 unique, ranked by cross-engine agreement) Multi-Agent Orchestration: Patterns and Best Practices for 2024 - Collabnix https://collabnix.com/multi-agent-orchestration-patterns-and-best-practices-for-2024/ Multi-Agent Orchestration: Patterns and Best Practices for 2024 - Collabnix Join our Discord Server 0 Share Collabnix Team Follow The Collabnix Team is a diverse collective of Docker, Kubernetes, and IoT experts unit... [1 engine(s): Exa] Multi-Agent System Reliability - Alex Ewerlöf Notes https://blog.alexewerlof.com/p/multi-agent-system-reliability # Multi-Agent System Reliability. ### 4 patterns to tame multi-agent systems for reliability. LLMs are slow and too generic out of the box. Multi-agent systems work around those limitation by dividing work that can be do... [1 engine(s): Tavily] Building Effective AI Agents \ Anthropic https://www.anthropic.com/engineering/building-effective-agents Building Effective AI Agents \ Anthropic # Building effective agents Published Dec 19, 2024 We've worked with dozens of teams building LLM agents across industries. Consistently, the most successful implementations us... [1 engine(s): Exa] Multi-Agent System Reliability: Failure Patterns, Root Causes, and ... https://www.getmaxim.ai/articles/multi-agent-system-reliability-failure-patterns-root-causes-and-production-validation-strategies # Multi-Agent System Reliability: Failure Patterns, Root Causes, and Production Validation Strategies. Multi-agent systems promise significant performance improvements through parallel execution and specialized capabilit... [1 engine(s): Tavily] Multi-Agent Orchestration: 5 Production Patterns That Scale – Athenic Blog https://getathenic.com/blog/multi-agent-orchestration-production-patterns Multi-Agent Orchestration: 5 Production Patterns That Scale – Athenic Blog Academy 16 Aug 2024• 13 min read # Multi-Agent Orchestration: 5 Production Patterns That Scale Deep dive into multi-agent orchestration patter... [1 engine(s): Exa] Multi-Agent System Patterns: A Unified Guide to Designing Agentic Architectures https://medium.com/@mjgmario/multi-agent-system-patterns-a-unified-guide-to-designing-agentic-architectures-04bb31ab9c41 # Multi-Agent System Patterns: Architectures, Roles & Design Guide | Medium. # Multi-Agent System Patterns: A Unified Guide to Designing Agentic Architectures. Multi-agent systems are often introduced as a prompt-enginee... [1 engine(s): Tavily] AI Agent Orchestration Patterns - Azure Architecture Center | Microsoft Learn https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/ai-agent-design-patterns AI Agent Orchestration Patterns - Azure Architecture Center | Microsoft Learn Ask Learn Ask Learn # AI agent orchestration patterns As architects and developers design their workload to take full advantage of language... [1 engine(s): Exa] Four Design Patterns for Event-Driven, Multi-Agent Systems https://www.confluent.io/blog/event-driven-multi-agent-systems * Use cases [ Shift Left Analytics Clean and govern data at the source and turn topics into Iceb... [1 engine(s): Tavily] A Comparative Study of AI Agent Orchestration Frameworks | by Kiumarse Zamanian, PhD | Medium https://medium.com/@kzamania/a-comparative-study-of-ai-agent-orchestration-frameworks-f61cd49b687e A Comparative Study of AI Agent Orchestration Frameworks | by Kiumarse Zamanian, PhD | Medium Sign up Get app Sign up # A Comparative Study of AI Agent Orchestration Frameworks 16 min read Nov 24, 2024 -- 1 Shar... [1 engine(s): Exa] Patterns & Practices for building Multi-Agent Systems by Nikhil ... https://www.youtube.com/watch?v=Z2l5V2Mvlx4 Patterns & Practices for building Multi-Agent Systems by Nikhil Barthwal Devoxx 171000 subscribers 18 likes 961 views 11 Nov 2025 Multi-Agent Systems are poised to transform industries by enabling end-to-end automation o... [1 engine(s): Tavily] Orchestrator-Worker Agents: A Practical Comparison of Common Agent Frameworks - Arize AI https://arize.com/blog/orchestrator-worker-agents-a-practical-comparison-of-common-agent-frameworks/ Orchestrator-Worker Agents: A Practical Comparison of Common Agent Frameworks - Arize AI { this.showMobileNavigation = false; this.secondaryMobileNavigation = null; }); this.$watch('showMobileNavigation', value => { doc... [1 engine(s): Exa] Multi-Agent Systems: Architecture + Use Cases - Teradata https://www.teradata.com/insights/ai-and-machine-learning/what-is-a-multi-agent-system # What Is a Multi-Agent System? What is a multi-agent system? Throughout, we use the terms multi-agent AI systems and multi-agent system (MAS) to clarify scope and design patterns. ## What is a multi-agent system? ## How... [1 engine(s): Tavily] AI Agent Orchestration in Production | Metasphere https://msphere.io/insights/ai-agent-orchestration/ AI Agent Orchestration in Production | Metasphere You wire up a prototype over lunch. The agent calls a search tool, summarizes the result, feeds it into an API, and returns a neat structured answer. Works great in the ... [1 engine(s): Exa] Multi Agent Architecture: Patterns, Use Cases & Production Reality https://www.truefoundry.com/blog/multi-agent-architecture Blank white background with no objects or features visible. Three horizontal black bars of varying lengths on a white background, menu or list icon symbol. Blank white background with no objects or features visible in th... [1 engine(s): Tavily] A Practical Guide to Agent Orchestration Frameworks - Cuttlesoft, Custom Software Developers https://cuttlesoft.com/blog/2025/03/27/a-practical-guide-to-agent-orchestration-frameworks/ A Practical Guide to Agent Orchestration Frameworks - Cuttlesoft, Custom Software Developers # A Practical Guide to Agent Orchestration Frameworks March 27, 2025 • Frank Valcarcel A year ago, building an AI agent mean... [1 engine(s): Exa] Why Do Multi-Agent LLM Systems Fail? https://arxiv.org/pdf/2503.13657 The appendix is organized as follows: in Section A further details about failure categories and failure modes are given, in Section B we provide some details about the multi-agent systems we have annotated and studied, i... [1 engine(s): Tavily] --- Fact-check --- (verification unavailable) Researched 3 source set(s) across 3 angle(s). Confidence: Low | 2026-06-15T19:13:10.8405851 | ||||
Source Library - new sources scavenged (2026-06-15)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged (2026-06-15) | (synthesis unavailable) ### Merged sources (16 raw hits across 3 engine(s) -> 16 unique, ranked by cross-engine agreement) Multi-Agent Orchestration: Patterns and Best Practices for 2024 - Collabnix https://collabnix.com/multi-agent-orchestration-patterns-and-best-practices-for-2024/ Multi-Agent Orchestration: Patterns and Best Practices for 2024 - Collabnix Join our Discord Server 0 Share Collabnix Team Follow The Collabnix Team is a diverse collective of Docker, Kubernetes, and IoT experts unit... [1 engine(s): Exa] What Is the Reliability Compounding Problem in AI Agent Stacks? https://www.mindstudio.ai/blog/reliability-compounding-problem-ai-agent-stacks # What Is the Reliability Compounding Problem in AI Agent Stacks? Five agent primitives at 99% uptime each give you only 95% system reliability. This is the reliability compounding problem, and it’s one of the most under... [1 engine(s): Tavily] Building Effective AI Agents \ Anthropic https://www.anthropic.com/research/building-effective-agents Building Effective AI Agents \ Anthropic # Building effective agents Published Dec 19, 2024 We've worked with dozens of teams building LLM agents across industries. Consistently, the most successful implementations us... [1 engine(s): Exa] Why most AI agents fail in production? The compounding error problem https://www.prodigaltech.com/blog/why-most-ai-agents-fail-in-production **AI agent for servicing and collections – integrated out-of-the box and live 24/7 across voice and digital.**. ## Why most AI agents fail in production? The numbers get worse when you look at AI agents specifically. Onl... [1 engine(s): Tavily] Multi-Agent Orchestration: 5 Production Patterns That Scale – Athenic Blog https://getathenic.com/blog/multi-agent-orchestration-production-patterns Multi-Agent Orchestration: 5 Production Patterns That Scale – Athenic Blog Academy 16 Aug 2024• 13 min read # Multi-Agent Orchestration: 5 Production Patterns That Scale Deep dive into multi-agent orchestration patter... [1 engine(s): Exa] Compounding Error Problem in Agentic AI: 64.15% Failure Rate in 20-Step Workflow | Sophie Halbeisen posted on the topic | LinkedIn https://www.linkedin.com/posts/sophie-halbeisen-5449a23a_i-cant-stop-thinking-about-the-compounding-activity-7401711284502700032-NflS # Compounding Error Problem in Agentic AI: 64.15% Failure Rate in 20-Step Workflow. I can't stop thinking about the compounding error problem in Agentic AI. But that perspective completely changes when building multi-ste... [1 engine(s): Tavily] Design multi-agent orchestration with reasoning using Amazon Bedrock and open source frameworks | Artificial Intelligence https://aws.amazon.com/blogs/machine-learning/design-multi-agent-orchestration-with-reasoning-using-amazon-bedrock-and-open-source-frameworks/ Design multi-agent orchestration with reasoning using Amazon Bedrock and open source frameworks | Artificial Intelligence Skip to Main Content ## Artificial Intelligence # Design multi-agent orchestration with reasonin... [1 engine(s): Exa] A Guide to AI Agent Reliability for Mission Critical Systems | Galileo https://galileo.ai/blog/ai-agent-reliability-strategies # AI Agent Reliability Strategies That Stop AI Failures Before They Start. Discover AI agent reliability best practices that stop failures before they impact business operations. "Autonomous multi-agent systems are like ... [1 engine(s): Tavily] A Comparative Study of AI Agent Orchestration Frameworks https://www.researchgate.net/publication/386083531_A_Comparative_Study_of_AI_Agent_Orchestration_Frameworks (PDF) A Comparative Study of AI Agent Orchestration Frameworks ArticlePDF Available # A Comparative Study of AI Agent Orchestration Frameworks * November 2024 Authors: [: Exa] The AI Agent Reality. Building for Scale and Reliability https://www.janeasystems.com/blog/ai-agent-reality-build-for-scale-and-reliability The promise of AI agents is that they will autonomously and reliably perform complex tasks with minimal human supervision and a low error rate. For starters, we don’t even have an exact definition of an agent – which all... [1 engine(s): Tavily] Architecting production-ready multi-agent systems: a practical blueprint - Nousheeniram.com https://www.nousheeniram.com/2024/02/01/architecting-production-ready-multi-agent-systems-a-practical-blueprint/ Architecting production-ready multi-agent systems: a practical blueprint - Nousheeniram.com #### Press ESC to close Building an AI-powered multi-agent system is no longer a lab experiment—it’s becoming the backbone of ... [1 engine(s): Exa] The New Agent Reliability Playbook - YouTube https://www.youtube.com/watch?v=Ojl7im3iWsM The New Agent Reliability Playbook Galileo 2020 subscribers 7 likes 445 views 28 Aug 2025 In the new agentic era, the old observability playbook breaks and traditional methods fall short as agents move from experiments t... [1 engine(s): Tavily] AI Agent Orchestration Patterns - Azure Architecture Center | Microsoft Learn https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/ai-agent-design-patterns AI Agent Orchestration Patterns - Azure Architecture Center | Microsoft Learn Ask Learn Ask Learn # AI agent orchestration patterns As architects and developers design their workload to take full advantage of language... [1 engine(s): Exa] The Compounding Errors Problem: Why Multi-Agent Systems Fail ... https://www.zartis.com/the-compounding-errors-problem-why-multi-agent-systems-fail-and-the-architecture-that-fixes-it The Compounding Errors Problem: Why Multi-Agent Systems Fail and the Architecture That Fixes It. ***Disclaimer:*** *The best practices and architecture we are about to explain is not theoretical. This article was deliber... [1 engine(s): Tavily] Multi‑Agent Orchestration Production Patterns That Survive Beyond the Demo https://www.future-of-software.com/multi-agent-orchestration-in-production-the-patterns-that-survive-when-the-demo-ends Multi‑Agent Orchestration Production Patterns That Survive Beyond the Demo Skip to main content Blog # Multi‑Agent Orchestration Production Patterns That Survive Beyond the Demo Learn five multi-agent orchestration pr... [1 engine(s): Exa] AI reliability is a decade-old problem. And we're still only solving half ... https://temporal.io/blog/ai-reliability-is-a-decade-old-problem New features for faster build and reliable AI | See what you missed at Replay 2026 ›. # AI reliability is a decade-old problem. What most of them *can’t* do is survive something going wrong halfway through. Even if an ag... [1 engine(s): Tavily] --- Fact-check --- (verification unavailable) Researched 3 source set(s) across 3 angle(s). Confidence: Low | 2026-06-15T19:34:08.6459620 | ||||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | (synthesis unavailable) ### Merged sources (6 raw hits across 3 engine(s) -> 6 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis https://arxiv.org/abs/2607.27942 Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis # Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis Linus Sander Affiliati... 6. https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents arXiv is now an independent nonprofit! Learn more× 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Instit... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... 8. https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition arXiv is now an independent nonprofit! Learn more× # Small Model as Master Orchestrator: Learning Unifie... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-07T15:28:27.9895925 | |||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | (synthesis unavailable) ### Merged sources (6 raw hits across 3 engine(s) -> 6 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis https://arxiv.org/abs/2607.27942 Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis # Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis Linus Sander Affiliati... 5. https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents arXiv is now an independent nonprofit! Learn more× 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Instit... 6. https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition arXiv is now an independent nonprofit! Learn more× # Small Model as Master Orchestrator: Learning Unifie... [1 engine(s): Exa] AI Agent Systems: Architectures, Applications, and Evaluation https://arxiv.org/html/2601.01743v1 AI Agent Systems: Architectures, Applications, and Evaluation arXiv is now an independent nonprofit! Learn more× # AI Agent Systems: Architectures, Applications, and Evaluation Journal: JACM Bin Xu ORCID 0009-0001-26... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-07T12:50:16.4306790 | |||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T18:07:02.3017700 | ||||
Source Library - new sources scavenged + scored (2026-06-25)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-25) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] How Kensho built a multi-agent framework with LangGraph to solve ... https://www.langchain.com/blog/customers-kensho How Kensho built a multi-agent framework with LangGraph to solve trusted financial data retrieval Case Studies LangGraph Observability & Evals # How Kensho built a multi-agent framework with LangGraph to solve truste... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media https://www.omniscient.media/post/the-orchestration-stack-a-practitioner-s-guide-to-multi-agent-coordination The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media [Omniscient](https://www.omniscient.media/) [](https://www.omniscient.media/search)[Sign In](https://www.omniscient.media/lo... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print A deployable enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable exec... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-25T12:03:13.5670099 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T23:21:46.9655819 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T21:39:46.3062803 | ||||
Source Library - new sources scavenged + scored (2026-06-23)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-23) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print A deployable enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable exec... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-23T08:23:53.7377118 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T07:52:30.9259308 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T06:54:16.1548081 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T06:41:15.0305019 | ||||
Source Library - new sources scavenged + scored (2026-06-22)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-22) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print A deployable enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable exec... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-22T08:16:32.7276559 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T23:12:16.2517915 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T23:03:25.9038271 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T22:37:31.5873561 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] SEDM: Scalable Self-Evolving Distributed Memory for Agents https://arxiv.org/html/2509.09498 SEDM: Scalable Self-Evolving Distributed Memory for Agents **footnotetext: Equal contribution. # SEDM: Scalable Self-Evolving Distributed Memory for Agents Haoran Xu* Gradient Zhejiang University Jiacong Hu* Gradient ... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T22:22:55.4581578 | ||||
Source Library - new sources scavenged + scored (2026-06-22)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-22) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print A deployable enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable exec... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-22T07:46:49.8298071 | ||||
Source Library - new sources scavenged + scored (2026-06-19)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-19) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems https://arxiv.org/pdf/2602.03036 [2602.03036] LatentMem: Customizing Latent Memory for Multi-Agent Systems \setheadertext\correspondingemail\emailicon boonkana10@gmail.com, guibinz@outlook.com $*$ Equal Contribution ‡ Corresponding Author.\githublinkh... [1 engine(s): Exa] sarmakska/agent-orchestrator https://github.com/sarmakska/agent-orchestrator # Repository: sarmakska/agent-orchestrator Multi-agent workflows with deterministic replay, durable state, and tool budgets. TypeScript + Postgres + Drizzle + Redis + BullMQ + Next.js inspector. - Stars: 0 - Forks: 0 -... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-19T23:46:44.5619151 | ||||
Source Library - new sources scavenged + scored (2026-06-21)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-21) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-21T19:08:18.6626209 | ||||
Source Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems https://arxiv.org/abs/2606.01416 [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems [Skip to main content](#content) [](https://arxiv.org/IgnoreMe) [ : Exa] How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community https://dev.to/gauravstack/how-i-built-and-broke-and-fixed-a-production-multi-agent-ai-orchestration-system-264g How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community Gaurav Bomra Posted on Sep 11 # How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv https://www.alphaxiv.org/abs/2604.19818 Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv 2 / - Hide Tools Ctrl + / Open Tools ## Abstract Agentic AI systems plan, use tools, maintain... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-14T21:02:13.9049505 | |||
Source Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems https://arxiv.org/abs/2606.01416 [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems [Skip to main content](#content) [](https://arxiv.org/IgnoreMe) [ : Exa] How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community https://dev.to/gauravstack/how-i-built-and-broke-and-fixed-a-production-multi-agent-ai-orchestration-system-264g How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community Gaurav Bomra Posted on Sep 11 # How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... [1 engine(s): Exa] Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv https://www.alphaxiv.org/abs/2604.19818 Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv 2 / - Hide Tools Ctrl + / Open Tools ## Abstract Agentic AI systems plan, use tools, maintain... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-14T20:42:34.3828879 | |||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T07:37:25.5241458 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T07:26:39.3542636 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media https://www.omniscient.media/post/the-orchestration-stack-a-practitioner-s-guide-to-multi-agent-coordination The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media [Omniscient](https://www.omniscient.media/) [](https://www.omniscient.media/search)[Sign In](https://www.omniscient.media/lo... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T06:34:04.1273457 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media https://www.omniscient.media/post/the-orchestration-stack-a-practitioner-s-guide-to-multi-agent-coordination The Orchestration Stack: A Practitioner's Guide to Multi-Agent Coordination | Omniscient Media [Omniscient](https://www.omniscient.media/) [](https://www.omniscient.media/search)[Sign In](https://www.omniscient.media/lo... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T06:24:33.9482910 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 ### Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition Wenzhen Yuan 1 * Wutao Xiong 2 * Fanchen Yu 3 Shengji Tang 4 Ting Liu 1 Tao Chen 5 Peng Ye 4 3 Yuzhuo... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] Multi-Agent Architecture: Production Patterns for Reliable Coordination | Markaicode https://markaicode.com/architecture/multi-agent-architecture/ Multi-Agent Architecture: Production Patterns for Reliable Coordination | Markaicode The hardest part of multi-agent architecture isn’t the individual agent — it’s the coordination logic that breaks under real-world lat... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T13:50:52.3836345 | ||||
Source Library - new sources scavenged + scored (2026-06-20)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-06-20) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation https://arxiv.org/pdf/2510.04851 LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation \setcopyright ifaamas \acmConference[AAMAS ’26]Proc. of the 25th International Conference on Autonomous Agents and Multiagent Syste... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents \useunder \ul 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Institute for Advanced Algorithms Research,... [1 engine(s): Exa] AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration https://arxiv.org/pdf/2602.03786 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration # AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration Jianhao Ruan* Zhihao Xu* Yiran Peng Fashen Ren Zhaoyang Yu Xinbing Liang Jinyu X... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print A deployable enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable exec... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-20T19:43:46.5032020 | ||||
Source Library - new sources scavenged (2026-06-15)... |
Agency.ResearchEnrichment | Source Library - new sources scavenged (2026-06-15) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) ramannanda9/agent-harness https://github.com/ramannanda9/agent-harness # Repository: ramannanda9/agent-harness BYO-LLM multi-agent harness: hybrid DAG orchestration, router, two-tier memory, streaming-primary event model, sandboxed tool execution (native + Docker) - Stars: 1 - Forks: 0 - ... [1 engine(s): Exa] Introducing Strands Agents 1.0: Production-Ready Multi ... - AWS https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/ Introducing Strands Agents 1.0: Production-Ready Multi-Agent Orchestration Made Simple | AWS Open Source Blog Skip to Main Content ## AWS Open Source Blog # Introducing Strands Agents 1.0: Production-Ready Multi-Agent ... [1 engine(s): Exa] mahsumaktas/agent-evolution-kit https://github.com/mahsumaktas/agent-evolution-kit # Repository: mahsumaktas/agent-evolution-kit Multi-agent orchestration with self-evolution, cognitive memory, and governance. - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Shell - Languages:... [1 engine(s): Exa] raghuece455/AgentMesh https://github.com/raghuece455/AgentMesh # Repository: raghuece455/AgentMesh Open-source observability, traceability, replay, and cost intelligence platform for multi-agent AI systems - Stars: 1 - Forks: 0 - Watchers: 0 - Open issues: 0 - Primary language: Py... [1 engine(s): Exa] Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition # Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Dec... [1 engine(s): Exa] Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems https://arxiv.org/html/2604.19540 Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems # Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems Hongwei Xu (April 2026) ###### Abstract Teams of LLM agents incre... [1 engine(s): Exa] AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol https://arxiv.org/pdf/2506.12508 AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol # AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol Wentao Zhang1,... [1 engine(s): Exa] AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents https://arxiv.org/pdf/2603.09716 ## AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents Xiaoxing Wang∗ 1,3, Ning Liao∗ 1,3, Shikun Wei 1,2, Chen Tang 1,3, Feiyu Xiong 1,3 1MemTensor (Shanghai) Technology Co., Ltd., 2Shan... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-06-15T18:05:54.6209976 |