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learn ai agents & automation
tool use, planning, memory, and multi-agent systems — how llms move from answering to doing real work.
the curated path
curatedmixed~4 weeks, part-time
ai agents & automation
how language models stop just answering and start doing — using tools, planning, remembering, and coordinating to automate real work.
4 modules · 12 resources · checkpoint per modulestay current
what's new in ai agents & automation
- From Intent to Execution: Composing Agentic Workflows with Agent Recommendationproposes methods to automatically compose multi-agent systems by recommending which agents should handle specific user intents. helps practitioners build flexible, reusable agent families without manual orchestration.
- A Self-Healing Framework for Reliable LLM-Based Autonomous Agentsaddresses reliability challenges in llm-based agents by enabling them to detect and recover from failures without human intervention. critical for production deployments where agents must operate robustly in unpredictable conditions.
- TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Explorationuses agents to automatically explore and optimize llm fine-tuning configurations through tree-based search. reduces manual hyperparameter tuning effort for practitioners customizing models for specific tasks.
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