Agno – multi-agent framework, runtime and control plane
Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing. What makes it different • Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro). • Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI. • Integrated…
Agno – multi-agent framework, runtime and control plane launched on October 26, 2025 with 9 votes, #1,657 of 8,178 launches that month and more than 75% of that year's launches.
What it does
Agno turns agents into production software. Build agents in any framework. Run as a service. Ship to real users.
In the maker’s words, at launch
Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full…
Does a similar job
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Agno2025 · github.com · ▲326Build, run, and manage agent platforms. Contribute to agno-agi/agno development by creating an account on GitHub.
Agno – multi-agent framework, runtime and UI2025 · ashpreetbedi.com · ▲15The multi-agent framework, runtime, and UI built for speed.

Agyn, an open-source Kubernetes runtime for AI agentsMay 2026 · github.com · ▲9Agyn is an open-source Kubernetes-native runtime that moves AI agents like Claude Code and Codex from laptops to company infrastructure with the controls enterprises need. - agynio/platform

Agent framework that generates its own topology and evolves at runtimeFeb 2026 · github.com · ▲107Hi HN, I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools. Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were even worse. My reflections: 1. The "Toy App" Ceiling & GCU Trap Most frameworks assume synchronous sessions.…
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