A runtime platform for designing, deploying, and governing multi-agent workflows across enterprise tools using MCP and A2A protocols.
Added May 10, 2026
High opportunity (79%)
Enterprise engineering teams are building multi-agent systems from scratch, wiring up state management, tool contracts, handoff logic, and agent-to-agent communication without standardized infrastructure. Teams struggle with execution isolation, permission control, auditability, and cost governance when agents take over real workflows across internal organizations.
A platform that provides task orchestration, tool invocation via MCP, context and memory management, and multi-agent collaboration primitives out of the box. It includes a runtime and governance layer for execution isolation, permission control, auditability, evaluation frameworks, and cost governance, plus built-in support for A2A protocols and modern agent tool-discovery patterns.
MCP and A2A protocols are emerging as standards in 2025-2026, and enterprises from fintech to observability to restaurant tech are simultaneously hiring senior engineers to build multi-agent orchestration infrastructure in-house.
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So yeah, in one word, autogen is the multi-agent AI framework, and especially focusing on multi-agent conversations so that we can connect large-scale models, tools, and human inputs together to solve complex tasks. There can be multiple ways to understand this, so one way is to understand it as a programming framework for developers to build applications easily with some simple and unified abstraction so that they don't need to worry too much about the details, but can focus on how to define agents, how to get them to work with each other, and eventually reach the goal. It can also be understood as a tool to kind of scale up the power of diagram models and make them even more useful by connecting with other tools, non-large model tools or human collaborators, and kind of scale up both the complexity of a problem they can solve, the degree of automation to some extent.
Designing the orchestration model: how agents are composed, routed, scheduled, handed off to humans and operated across product surfaces and services. Creating and evolving agents for real People workflows, including tools, contracts, identity, scope, failure modes and regeneration strategies—not only prompts.
Architect Enterprise-Grade AI Platforms & Systems: Own the end-to-end technical strategy across model rollouts, eval infrastructure, tool orchestration, Model Context Protocol (MCP), and proactivity engines—enabling Asana to operate reliable agentic systems for top-tier enterprise customers.
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