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Raven 0.2.0 — The Harness of Harnesses, built for RSI. 🐦‍⬛ One harness can't be best at everything. Raven combines its own specialist harnesses (Research, Code, Design, Oncall) with the agents you already use (Claude Code, Codex and more) into one team. And it's built for RSI, and not just at the skill level. The whole harness can be rewritten by AI: prompts, policies, strategy code, playbooks. Every sub-harness, including the orchestration layer itself, is its own instance that can be improved. With Raven you can: 1. Orchestrate many agents as one team. Raven's sub-harnesses and external agents work in one task graph with shared memory across sub-agents, powered by leading orchestration (0.963 Node F1 on the Multi-Agent Orchestration Benchmark). 2. Run long, complex tasks. Oncall and proactive execution keep work going for days, from scientific research loops to shipping a full Godot game. 3. Build vertical agents with RSI. Use Raven's RSI to develop and refine an agent for your domain, and we'll optimize it with you. Experimental for now; reach out to the Raven team(Discord:discord.gg/VVSm8MESch). More in the video and slides below. Open source, Apache-2.0. github.com/EverMind-AI/Raven (lots of work made with Raven lives there, and much of this launch's material was made with Raven too)

经历了不知道多少次的反复挣扎，我们决定把过去三年积累的 48 场内部主题分享、10 节推特增长课和 13 节出海实战课，累计 68 小时 14 分钟， 做成一份完全免费的 Playbook 分享给想做出海产品的大家！ 累计消耗 16.19 亿 Token，历时 31 天， 梳理出 15 个主题任务簇、270 个知识点、118 个案例和 226 项重复或冲突记录，制作 48 份逐章来源映射，核查 218 个外部网址， 最终重编为 9 个模块、48 篇、约 30.4 万字的 Playbook。 今天 Beta 版免费开放给大家 👉 chq.sh/pb 审美也绝对在线， 由出海去合伙人以及设计工程师 @Thons 反复校对打磨 从选品验证、设计、定价、发布，一直走社媒、增长、运营合规等等，希望对大家出海之路有所帮助！