Concept · 22 episode(s)

Task Decomposition

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Definition

Task decomposition is the act of breaking a task into smaller, more tractable sub-tasks — the core skill of a planner, whether it’s a project manager, a compiler, or an LLM agent. The trick isn’t just decomposition but knowing when to stop decomposing.

Episodes covering this

  1. 190
    The Skill Every AI Manager Is Missing: Handing Out Exactly the Right Keys
    ClawArena-Team: Benchmarking Subagent Orchestration and Dynamic Workflows in Language-Model Agents
    Xiong, Ji, Qiu et al. · UNC Chapel Hill·21 min·Jul 02, 2026
  2. 188
    A Coding Agent Found a Hole in a Peer-Reviewed STOC Proof for Five Dollars
    Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics
    Moakhar, Gholami, Springer et al. · University of Maryland·20 min·Jul 02, 2026
  3. 166
    A Router That Beats the Frontier Models It Calls
    Sakana Fugu Technical Report
    Tang, Cetin, Xu et al. · Sakana AI·26 min·Jun 23, 2026
  4. 161
    A Robot That Plays Before You Give It a Job, And Why That Beats Retrying
    Playful Agentic Robot Learning
    Zhang, Ge, Yoo et al. · University of California·19 min·Jun 19, 2026
  5. 156
    Why More Human Demonstrations Made a Computer-Use Agent Worse
    ProCUA-SFT Technical Report
    Jung, Lu, Cui et al. · NVIDIA / University of Washington·20 min·Jun 18, 2026
  6. 130
    Why AI Agents Coordinate Better Through a Shared Board Than a Boss
    Decentralized Multi-Agent Systems with Shared Context
    Mao, Mirhoseini · Stanford University·34 min·Jun 11, 2026
  7. 117
    How an Open AI System Verified 672 Hard Math Proofs for Under $300
    Goedel-Architect: Streamlining Formal Theorem Proving with Blueprint Generation and Refinement
    Chung, Cai, Li et al. · Princeton University·26 min·Jun 05, 2026
  8. 110
    How an Agent Got 44 Points Better by Mining Its Own Scratch Paper
    Inducing Reasoning Primitives from Agent Traces
    Lei, Yan, Momo et al. · Carnegie Mellon University·27 min·Jun 03, 2026
  9. 107
    How a Market of Crippled AI Agents Outscored One Unrestricted Model
    Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions
    Qi, Su, Qu et al. · Harvard·26 min·Jun 03, 2026
  10. 102
    How to Catch an AI Attack That No Single Conversation Reveals
    Stateful Online Monitoring Catches Distributed Agent Attacks
    Brown, Bhargav, Santhanam et al. · University of Pennsylvania·24 min·Jun 01, 2026
  11. 100
    How a Prompt Wrapper Lets a Frontier Model Play Poker Like an Expert
    PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers
    Li, Wang, Huang · IIIS·29 min·May 29, 2026
  12. 095
    Seven Wins to Zero: How Organizing AI Agents Like a Lab Changes the Search
    AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation
    Gao, Fang, Zitnik · Harvard University·24 min·May 28, 2026
  13. 091
    When Better Fine-Tuning Can't Help: A Geometric Impossibility in LLM Causal Reasoning
    Why LLMs Fail at Causal Discovery and How Interventional Agents Escape
    Roy, Parbhoo · SIRE·24 min·May 28, 2026
  14. 076
    Same Model, Organized Differently: How an Agent Architecture Beat Frontier Systems at Research Math
    RMA: an Agentic System for Research-Level Mathematical Problems
    Zhao, Yuan, Choi et al. · Georgia Institute of Technology·22 min·May 25, 2026
  15. 075
    Growing Code and Proof Together: Verified Systems in Ten Hours Instead of a Year
    Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems
    Agarwal, Krentsel, Liu et al. · UC Berkeley·28 min·May 25, 2026
  16. 072
    A Robot Made Graphene Without Help, And Caught Itself Hallucinating
    Qumus: Realization of An Embodied AI Quantum Material Experimentalist
    Shi, Zheng, Juan et al. · Princeton University·29 min·May 23, 2026
  17. 067
    An AI Just Solved a 1996 Erdős Problem—and the Simplest Agent Won
    Advancing Mathematics Research with AI-Driven Formal Proof Search
    Tsoukalas, Kovsharov, Shirobokov et al. · Google DeepMind·31 min·May 22, 2026
  18. 066
    Why Giving an AI Agent More Tools Can Make It Worse at Using a Computer
    ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents
    Hu, Zhang, Xu et al. · Tongyi Lab·26 min·May 22, 2026
  19. 065
    One Loop to Optimize Them All: A Universal API for LLM-Driven Discovery
    optimize_anything: A Universal API for Optimizing any Text Parameter
    Agrawal, Lee, Tan et al. · UC Berkeley·27 min·May 22, 2026
  20. 063
    Why Web Agents Are Slow: A Compiler-Style Fix for Computer-Use Latency
    Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling
    Winston, Wang, Mirhoseini et al. · Stanford University·26 min·May 21, 2026
  21. 046
    When the AI Optimizer Edits the Grade Book: Why Harnessing Evolution Needs a Wall
    Harnessing Agentic Evolution
    Zhang, Gu, Ruan et al. · The Hong Kong University of Science and Technology (Guangzhou) / DeepWisdom·24 min·May 15, 2026
  22. 028
    Teaching a Model to Hire Copies of Itself: Recursive Agent Optimization
    Recursive Agent Optimization
    Gandhi, Chakraborty, Wang et al. · Carnegie Mellon University·23 min·May 08, 2026

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