Agentic LLMs keep failing the same way because they lack specific, reusable capabilities. Stanford's TRACE diagnoses those gaps from an agent's own trajectories, synthesizes one verifiable training ...
In this tutorial, we reconstruct the VideoAgent workflow as a runnable, API-key-free multi-agent pipeline. We build an intent parser, an agent library, a tool router, a graph planner, and a ...
Example: AI analyzes your AirfoilTools add-in, finds the best airfoil from 1,538 profiles, stores results in SQLite, and shows a popup—all in one command!
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