🎉Introducing PyFlue: The Python-Native Agent Harness Framework.🧰 💡Flue for Python: Fred K. Schott @FredKSchott CEO of HTML has launched Flue: The Agent Harness Framework for TypeScript. It brings programmable harness right into your agents rather than DIY plumbing. Python ecosystem already has 🦾 powerful AI/ML tools and frameworks and research initiatives but most frameworks asked users to build your own harness. Superagentic AI bringing this concept of Flue to Python 🐍 ecosystem. Here is PyFlue even even better 🤖 Agent = Model 💻 Harness 🧰 Memory 🧠 Almost all the feature of Flue plugged with @LangChain Deepagents harness built by @hwchase17 and team @Vtrivedy10 @sydneyrunkle and more coming soon. 👉 Stop building agent loops, start using a harness. 💻 Try PyFlue Now : super-agentic.ai/pyflue ⭐️ GitHub: github.com/SuperagenticAI/py… 📚Docs: superagenticai.github.io/pyf… 📙 Blog Post: super-agentic.ai/resources/s… #HarnessEngineering #AgentHarnesses

🌀OpenAI Agents SDK: The Dawn of Extreme Harness Engineering is Here @OpenAIDevs just dropped a game-changing update to their Agents SDK introducing a powerful open harness sandbox architecture that makes production-grade, long-running agents finally practical. 🛠️No more building fragile orchestration layers yourself. Files, shell access, declarative Manifest staging, snapshotting, and seamless partner sandboxes (Daytona, Modal, E2B, etc.) all in one clean package. ⛴️We moved fast at @SuperagenticAI : SuperOptiX v0.2.25 now ships full native integration with GEPA optimization running on top of this new runtime. 📙 Read the full story and GitHub 💻 Repo Link in the comment below 👇 The harness is becoming the new moat.🧰 Thanks to @stevendcoffey and team. 📙 Blog: super-agentic.ai/resources/s… 💻 SuperOptix Release: github.com/SuperagenticAI/su… #OpenAI #AgentsSDK #AgenticAI #AI #SuperOptiX #HarnessEngineering

🎉Meta-Harness: Yesterday, Stanford IRIS Lab released the official Meta-Harness reference code a powerful new way to let AI agents autonomously optimize the harness around a fixed LLM (memory, tools, validation, scaffolds, etc.) @SuperagenticAI has been building toward this moment since April 2. Today, I’m thrilled to announce the release of metaharness v0.2.0 : our full “official alignment” update. That aligns with official source code and introduce practical engine for coding agents. 🧰The era of manually tuning agent harnesses is over. The era of self-optimizing harnesses has begun. 📙 Read the full story in our new blog post: Stanford Dropped the Blueprint, We Shipped the Engine: metaharness v0.2.0 Brings Production-Ready Meta-Harness Optimization 👉 Read the blog here : super-agentic.ai/resources/s…💻meta-harness-repo-packaged-power-coding-agent-metaharness Repo: github.com/SuperagenticAI/me… 📙Docs: superagenticai.github.io/met… #AI #AgenticAI #OpenSource #LLM #MetaHarness #CodingAgents #StanfordAI