Orpheus, An Agent runtime that scales on queue depth and not CPU
Orpheus is an Agent Runtime that solves the 'Silent Failure' of CPU autoscaling. It scales on queue depth, persists memory, and recovers from crashes automatically. - arpitnath/orpheus
Orpheus, An Agent runtime that scales on queue depth and not CPU launched on February 4, 2026 with 6 votes, #1,572 of 16,627 launches that month and more than 75% of that year's launches.
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Tilde.run – Agent sandbox with a transactional, versioned filesystemMay 2026 · tilde.run · ▲205Tilde started from a simple observation: AI agents are only as useful as the environment they can work in. Giving an agent a prompt is easy. Giving it the right files, credentials, tools, context, and execution environment, safely and repeatably, is much harder. Over the past year, we learned a lot

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.…
Platos | The runtime for Managed AgentsMay 2026 · platos.dev · ▲11Your agents. Your servers. Your keys. Your model.
Agno – multi-agent framework, runtime and control planeOct 2025 · agno.link · ▲9Hi 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…
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