
Deep Agents
ProjectWatch8AI-driven trading platform
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.@Rippling AI runs on Deep Agents and LangSmith. Here’s how they shipped to millions of users in 6 months. https://t.co/jxDxKIjW0F
Managed Deep Agents keeps the project shape you already know: ↳ AGENTS.md, skills/, subagents/, + tools.json Context Hub gives your agent a managed place to retain and update this context across sessions, allowing agent definition to evolve over time. https://t.co/jx3E0Sn2XH
Come talk AI agents with us in Amsterdam ☕ Excited to join @GenLayer and @0G_labs for Agents & Coffee during Dutch Blockchain Week. See you in Amsterdam on June 23, 2–5 PM GMT+2. First 50 attendees get free coffee. Register here: https://t.co/OYFybysiDt https://t.co/FuhpfLt8Xw
Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get production-grade performance from models like @Kimi_Moonshot, @Alibaba_Qwen, and @DeepSeek_ai at 20x+ lower cost than closed frontier APIs. More on tuning: https://t.co/6sU4M8qjRV
RT @hwchase17: Managed deep agents is the easiest way to build and deploy long horizon agents Private preview, dm me if you want access
Deep Agents v0.6 brings Delta channels, reducing checkpoint storage by up to 100x for long-running agents, without sacrificing observability or resilience. Here’s a 200-turn coding agent session. Without Delta Channels: 5.3GB of checkpoint storage With Delta Channels: 129mb
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