Huge release from EverMind AI. Raven is an open-source multi-agent system that builds a separate harness for each model and domain, evolves …

Huge release from EverMind AI. Raven is an open-source multi-agent system that builds a separate harness for each model and domain, evolves those harnesses from their failures, and coordinates them through a host agent. The host agent splits a goal into a task graph and sends each part to a model-harness pair for research, code, design, or on-call work. Harness components are diagnosed, mutated, and recombined, and a candidate replaces the current harness only after passing a statistical check. With DeepSeek-V4-Flash, the research harness scores 69.3% on BrowseComp and 60.0% on Humanity's Last Exam, against at most 62.4% and 43.3% for two other harnesses on the same model. Its curated skill library raises SkillsBench Pass@1 from 9.2% with no skills to 22.6%. Paper: https://arxiv.org/abs/2609.33439 Chat with Paper: https://academy.dair.ai/papers/raven-the-harness-of-harnesses-for-composable-agentic-intelligence-2609.33439

Banger paper from Google on agent harnesses for long-horizon tasks. (bookmark it) Google Research built a many-agent harness for long mathem…
New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few …
If you build agent harnesses, this is important. Should you avoid subagents, or can they be useful? My thoughts as a harness builder: I reme…
If you hand-tune agent harnesses, this one is worth your time. AutoDesign puts the harness itself inside the optimization loop. A meta-harne…
Must-read paper from Google on self-improving agent harnesses. If you auto-optimize your agent's harness, your eval score can go up while th…

Source: DAIR.AI (X) | 2026-10-05

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