An AI Agent that runs 24/7 as a lightweight background process, continuously processing, consolidating, and connecting information. Just an LLM that reads, thinks, and writes structured memory. Built with Gemini 3.1 Flash Lite.
AGENTS
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DeepAgents CLI: Exploration Tool for AI Agents
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definitely is! we have deepagents cli which is our exploration
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DataAISummit 2026: Building Accurate Grounded AI Agents
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#DataAISummit 2026 is less than two months away! Join us June 15-18 for practical insights and real-world case studies on transforming your organization with data and AI.
— Databricks (@databricks) 12 avril 2026
Across 800+ sessions, you’ll hear from teams on how to:
• Build AI agents that are accurate and grounded… pic.twitter.com/Qjf8wehQmJ#DataAISummit 2026 is less than two months away! Join us June 15-18 for practical insights and real-world case studies on transforming your organization with data and AI. Across 800+ sessions, you’ll hear from teams on how to: • Build AI agents that are accurate and grounded
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LangChains create-agent vs DeepAgents SDK comparison
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LangChains create-agent is a super minimal agent sdk If you want a more batteries included – that’s deepagents Middleware lets you extend both of them and customize behavior in a more advanced way
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AI System Consistency and Context Complexity Trade-offs
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Thanks for the clarification! Your analogy about saving the stranger vs saving the dog makes a lot of sense. This is my non-expert POV, but I’ve been wondering if agentic behavior becomes less consistent as systems become more complex and are given more context. And does that
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Parallel Agentic Workflows skill now live for all CLI agents
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Skill for Parallel Agentic Workflows is now live Works w/ any CLI agent harness
(Codex, Claude, Kimi, OpenCode, Droid, etc) Be warned this was vibecoded from my workflows, not fully tested Should be a GREAT STARTING POINT nevertheless Give the screenshot below to your agent -
Permission Ladder for AI Agent Autonomy and Scale
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This isn’t a “learn AI agents” roadmap. It’s a permission ladder for autonomy. Skills → memory → coordination → control → monetization. Skip steps and you don’t get scale — you get outages.
→ View original post on X — @ingliguori, 2026-04-12 17:25 UTC
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Vibe-coding with Codex Cli using parallel agents for implementation
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You don't even need the skill that
Codex Cli is currently vibe-coding Take this screenshot and tell an agent-after it gives you an implementation plan-to use 1 of the 2 paths (you need to specify) for the actual implementation using parallel agents Done -
Openclaw Agent Implementation for Specific Use Case
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Openclaw agent that he is using for his use case
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Advanced Autonomous Agents Interacting With Physical World Mid-2030s
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I see this as a route for advanced autonomous agentic AI (neurosymbolic & neuromorphic) to experience and interact with the physical world in the mid 2030s onwards