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Can AI agents remember and reuse solutions across domains like humans do?

In this episode of the Colaberry AI Podcast, we unpack the game-changing innovation behind AGENT KB — a new framework designed to give AI agents long-term, cross-domain memory for solving complex problems. Built on a “Reason-Retrieve-Refine” pipeline, Agent KB could mark a shift from task-specific AI to experience-driven intelligence.

Here’s what you’ll learn:
 🧩 Why most AI agents repeat the same mistakes — and how Agent KB solves that
 🧠 How it builds a hierarchical experience base from previous problem-solving
🤖 The teacher-student multi-agent structure for smarter inference
🚀 Real-world performance on GAIA & SWE-bench for code reasoning and repair
🔄 Why this is a big leap toward adaptive, reusable AI

📖 Ref:
Agent KB by Vlad Bogo

🎧 Listen to the episode on audio:
👉 Colaberry Podcast

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This podcast is for educational and informational purposes only. All referenced content is credited to its original authors. If you believe any portion of this episode infringes upon rights or contains inaccuracies, please contact us at [email protected] and we will take prompt action.

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