{"id":24964,"date":"2025-09-10T08:01:04","date_gmt":"2025-09-10T06:01:04","guid":{"rendered":"https:\/\/comunicagenia.com\/blog\/multiagent-systems-when-ais-learn-to-work-as-a-team\/"},"modified":"2025-09-10T08:01:04","modified_gmt":"2025-09-10T06:01:04","slug":"multiagent-systems-when-ais-learn-to-work-as-a-team","status":"publish","type":"post","link":"https:\/\/comunicagenia.com\/en\/blog\/multiagent-systems-when-ais-learn-to-work-as-a-team\/","title":{"rendered":"Multiagent Systems: When AIs learn to work as a team"},"content":{"rendered":"

In the field of artificial intelligence (AI), multi-agent systems represent a fascinating frontier: an environment where multiple AIs collaborate to solve problems that would be too complex for one AI.<\/p>\n

Instead of relying on a single, monolithic model, tasks are broken down into smaller components, assigned to specialized agents.<\/strong><\/p>\n

This dynamic, similar to that of a highly efficient human team<\/strong>, is ideal for scenarios such as market research, process automation or the analysis of large volumes of data.<\/p>\n

How do AIs collaborate? Roles, communication and coordination<\/h2>\n

Cooperation in a multi-agent system is based on three pillars: defined roles, fluid communication and effective coordination. Each agent takes on a specific responsibility<\/strong>: one may search for information on the web, another analyze numerical data, and a third synthesize the findings into a coherent report.<\/p>\n

For this collaboration to work, agents follow interaction protocols that govern how they exchange messages, share tools (such as access to an API), or use shared memory to maintain context.<\/p>\n

**Assigning clear roles from the beginning and establishing error management mechanisms are key practices that ensure the robustness of the system and allow agents to work in parallel without conflicts.<\/p>\n

Practical guide to building a Multiagent System<\/h2>\n

Today, creating a multi-agent system is more accessible than ever thanks to modern frameworks. These are the essential steps:<\/p>\n

    \n
  • Define the purpose and objectives. It is necessary to clearly identify the problem to be solved. For example: create a system that prepares a report on investment trends in renewable energy. A concrete objective facilitates the design of the architecture.<\/li>\n<\/ul>\n
      \n
    • Choose the appropriate architecture. There are centralized models (with a \u201csupervisory agent\u201d that coordinates), decentralized (agents that interact autonomously) and hybrid models. To begin with, frameworks such as LangGraph or Microsoft’s AutoGen simplify integration with large language models (LLMs) such as those from OpenAI, Google or Mistral.<\/li>\n<\/ul>\n
        \n
      • Implement agents and tools. Once roles are defined, each agent needs the right tools. With Python and libraries like LangChain, it is possible to create a \u201cresearch agent\u201d that consults the web and an \u201canalyst agent\u201d that processes the collected data.<\/li>\n<\/ul>\n
          \n
        • Test and optimize. Deployment in a test environment allows interactions to be monitored and failures detected, such as inconsistencies in information or communication loops.<\/li>\n<\/ul>\n

          With solutions like Vertex AI’s Agents Development Kit (ADK), it’s even possible to prototype a working system in less than 100 lines of code.<\/p>\n

          Real world examples<\/h2>\n

          Multi-agent systems already generate a visible impact in different industries:<\/p>\n

          In research and development, Anthropic has designed systems where several agents investigate, analyze and synthesize information<\/strong> in parallel to answer complex questions, drastically reducing research cycles.<\/p>\n

          In finance, with Microsoft AutoGen, teams of agents are created that collaborate in the management of investment portfolios<\/strong>: one analyzes market data, another evaluates risks and a third proposes diversified strategies.<\/p>\n

          Projects like Sentient’s ROMA (Recursive Open Meta-Agent) deploy networks of agents to analyze activity on blockchains<\/strong>, trading volume and sentiment on social networks (X\/Twitter, Discord) in order to detect opportunities in real time.<\/p>\n

          These systems not only coordinate tasks, but can also learn collectively, improving their performance with each interaction.<\/p>\n

          The future is collaborative<\/h2>\n

          Multi-agent systems are turning individual models into teams capable of achieving goals that previously seemed unattainable. The true revolution is not only in creating more powerful AIs, but in teaching them to collaborate<\/strong>.<\/p>\n

          Those who want to delve deeper into the topic can explore the official LangGraph documentation or the AutoGen guides on GitHub. Also, communities like r\/AI_Agents on Reddit offer an active space to follow advances in this exciting technological frontier.<\/p>\n","protected":false},"excerpt":{"rendered":"

          In the field of artificial intelligence (AI), multi-agent systems represent a fascinating frontier: an environment where multiple AIs collaborate to solve problems that would be too complex for one AI. Instead of relying on a single, monolithic model, tasks are broken down into smaller components, assigned to specialized agents. This dynamic, similar to that of […]<\/p>\n","protected":false},"author":9,"featured_media":20528,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","_thinkrank_schema_form_data":"","_thinkrank_selected_schema_type":"","_thinkrank_additional_schemas":"","_thinkrank_canonical_url":"","_thinkrank_og_title":"","_thinkrank_og_description":"","_thinkrank_og_image":"","_thinkrank_twitter_title":"","_thinkrank_twitter_description":"","_thinkrank_twitter_image":"","_thinkrank_imported_from":"","_thinkrank_focus_keywords":[],"_thinkrank_focus_keyword":"","_thinkrank_robots_meta_enabled":0,"_thinkrank_robots_meta":"","_thinkrank_advanced_robots_meta":"","_thinkrank_exclude_from_search":0,"_thinkrank_exclude_from_archives":0,"_thinkrank_primary_category":0,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[719],"tags":[],"class_list":["post-24964","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"uagb_featured_image_src":{"full":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo.jpg",1408,768,false],"thumbnail":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo-150x150.jpg",150,150,true],"medium":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo-300x164.jpg",300,164,true],"medium_large":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo-768x419.jpg",768,419,true],"large":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo-1024x559.jpg",1024,559,true],"1536x1536":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo.jpg",1408,768,false],"2048x2048":["https:\/\/comunicagenia.com\/wp-content\/uploads\/2025\/09\/sistemas-multiagente-ia-trabajar-equipo.jpg",1408,768,false]},"uagb_author_info":{"display_name":"marketing","author_link":"https:\/\/comunicagenia.com\/en\/blog\/author\/marketing\/"},"uagb_comment_info":0,"uagb_excerpt":"In the field of artificial intelligence (AI), multi-agent systems represent a fascinating frontier: an environment where multiple AIs collaborate to solve problems that would be too complex for one AI. Instead of relying on a single, monolithic model, tasks are broken down into smaller components, assigned to specialized agents. This dynamic, similar to that of…","_links":{"self":[{"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/posts\/24964","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/comments?post=24964"}],"version-history":[{"count":0,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/posts\/24964\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/media\/20528"}],"wp:attachment":[{"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/media?parent=24964"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/categories?post=24964"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/comunicagenia.com\/en\/wp-json\/wp\/v2\/tags?post=24964"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}