Theme · 17 episode(s)

Agentic Workflows

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Definition

Agentic workflows are pipelines where one or more AI agents take actions, call tools, and pass intermediate state between steps to complete a larger task. They occupy the middle ground between rigid pipelines (every step fixed) and fully open-ended agents (every step decided on the fly).

Episodes covering this

  1. 072
    A Robot Made Graphene Without Help, And Caught Itself Hallucinating
    Shi, Zheng, Juan et al. · Princeton University·29 min·May 23, 2026
  2. 071
    When the Model Is Fine and the Plumbing Is Broken: Fixing Agents at the Interface
    Xu, Wen, Li · Peking University·23 min·May 22, 2026
  3. 066
    Why Giving an AI Agent More Tools Can Make It Worse at Using a Computer
    Hu, Zhang, Xu et al. · Tongyi Lab·26 min·May 22, 2026
  4. 065
    One Loop to Optimize Them All: A Universal API for LLM-Driven Discovery
    Agrawal, Lee, Tan et al. · UC Berkeley·27 min·May 22, 2026
  5. 063
    Why Web Agents Are Slow: A Compiler-Style Fix for Computer-Use Latency
    Winston, Wang, Mirhoseini et al. · Stanford University·26 min·May 21, 2026
  6. 062
    Treating Hallucinations as Exploits: A Gate-Based Architecture for Agent Safety
    Zhang, Zheng, Yang · Shenzhen University·24 min·May 20, 2026
  7. 059
    Firefly's Inversion: Building Verified Tool-Call Training Data by Working Backward
    Lu, Wang, Lu et al. · Northeastern University·22 min·May 20, 2026
  8. 057
    How Uber Caught 206 Leaked Credentials With an LLM-Powered Security Stack
    Li, Hu, Xu et al. · Uber Technologies·28 min·May 19, 2026
  9. 042
    An Agentic Scientific Computing System That Actually Remembers What It Learns
    Toscano, Chai, Karniadakis · Division of Applied Mathematics·30 min·May 13, 2026
  10. 035
    Why Frontier Agents Ask for Clarification at Exactly the Wrong Moment
    Gulati, Gupta, Lumer et al. · PricewaterhouseCoopers U.S.·29 min·May 11, 2026
  11. 034
    Catching Multi-Agent Deadlocks Before Deployment With a 40-Year-Old Tool
    Xia, Li, Ehsan et al. · Rutgers University·30 min·May 11, 2026
  12. 030
    Why Your AI Agent Won't Stop Working — and Each Model Falls for a Different Trap
    Xu, Wang, Zhang et al. · Zhejiang University·30 min·May 09, 2026
  13. 029
    Why Forty-Eight Percent on FrontierMath Isn't the Real Story in DeepMind's New Math Paper
    Zheng, Glehn, Zwols et al. · Google DeepMind·20 min·May 08, 2026
  14. 023
    Why a Small Agent Confidently Overwrites Memories It Doesn't Understand
    Mao, Zhao, Penn et al. · City University of Hong Kong·23 min·May 07, 2026
  15. 016
    Why Your Coding Agent Stalls While the GPU Runs Hot
    Wang, Ye, Xu et al. · Duke University·24 min·May 03, 2026
  16. 013
    Why Search Keeps Rediscovering the Same Workflow, and What That Means
    Du, Liu, Du et al. · Carnegie Mellon University·22 min·May 03, 2026
  17. 002
    An AI Ran a Real Optics Lab for 21 Hours and Found a Transformer-Shaped Pattern in Light
    Yang, Chen, Zhao et al. · Zhejiang University·29 min·May 01, 2026

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