Concept · 34 episode(s)

Context Management

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Definition

Context management is the active engineering problem of deciding what goes into a model’s context window and what gets summarized, dropped, or retrieved on demand. It dominates real-world agent behavior more than most prompt-engineering write-ups admit.

Episodes covering this

  1. 288
    An AI Agent Given Thirty Hours and No Goal, Then Tested on What It Learned
    Is this machine playing?
    Cloos, Norelli, Durbin et al. · MIT·14 min·Oct 07, 2026
  2. 281
    When a Guardrail Blocks an Agent, It Goes Looking for Another Route
    Instrumental Monitor Evasion Emerges Under Ordinary Task Pressure
    Schmotz, Prinzhorn, Beurer-Kellner et al. · ELLIS Institute Tübingen·12 min·Sep 27, 2026
  3. 276
    An AI Agent Rewrote Its Own Scaffolding For Eight Days. Here's What Survived
    Recursive self-improvement of AI research agents
    Srikanth, Zhao, Xu et al. · Weco AI·14 min·Sep 23, 2026
  4. 275
    Your AI Agent Read Your Inbox, Then Quoted a Higher Price
    Et Tu, Brute? Economic Misalignment in Personal AI Agents
    Priyanshu, Vijay, Jabarian et al. · FoundationAI·12 min·Sep 22, 2026
  5. 270
    The Agent Said It Read 240 Files. The Log Says One.
    Quantifying Overclaiming Propensity in Frontier LLM Agents
    Smyth, Mantilla-Ramos, Notsawo et al. · Tara Research·14 min·Sep 19, 2026
  6. 269
    How a Forged Transcript Got Model Weights Past a Safety Monitor
    Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents
    Remedios, Storf, Roger et al. · Anthropic Fellows Program·18 min·Sep 18, 2026
  7. 261
    Split the Same Story Across Five Messages and the Model Switches Sides
    Caught in the Story: Narrative Captivity in Multi-turn LLMs Conversation
    Wu, Wang, Chen et al. · The Hong Kong University of Science and Technology (Guangzhou)·23 min·Sep 05, 2026
  8. 250
    The Same Model Refused a Backdoor, Then Its Own Sub-Agent Ran It
    When Context Gets Root: Privilege Escalation in LLM Harnesses
    He, Chen, Qian et al. · Nanjing University·23 min·Aug 29, 2026
  9. 245
    Fifteen Models Ran Football Clubs for Twenty Years, and Size Didn't Decide It
    FM-Bench: A Benchmark for Long-Horizon Management with Competing Agents
    Wang, Gao, KezhенChen et al. · AnalogyAI·19 min·Aug 20, 2026
  10. 238
    How a Cheap Model Reads the Flagship's Secret Reasoning Aloud
    Stealing Reasoning Traces from Proprietary LLM APIs
    Panfilov, Schmotz, Shumailov et al. · MATS Research·19 min·Aug 11, 2026
  11. 194
    How a Robot Builds a Debugging Notebook It Can Read, Edit, and Hand to Another Robot
    ASPIRE: Agentic /Skills Discovery for Robotics
    Lu, Wu, Kou et al. · NVIDIA·24 min·Jul 02, 2026
  12. 192
    A 32B Open Model Matched Frontier Systems By Learning to Take Notes
    AutoMem: Automated Learning of Memory as a Cognitive Skill
    Wu, Zhu, Zhang et al. · Stanford University·22 min·Jul 02, 2026
  13. 180
    The Bug Where Smart Assistants Read a Fact and Still Forget It
    Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents
    Patel · Vrin·24 min·Jun 29, 2026
  14. 169
    Why Better Bug Reports Can Make AI Coding Agents Worse
    SHERLOC: Structured Diagnostic Localization for Code Repair Agents
    Tamoyan, Narenthiran, Arakelyan et al. · NVIDIA / TU Darmstadt·24 min·Jun 24, 2026
  15. 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
  16. 164
    The Summarizer That Quietly Deletes Your Agent's Safety Rules
    Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents
    Chen · Beijing Institute of Technology·28 min·Jun 23, 2026
  17. 154
    How a 7B Model Out-Investigates a 72B One by Choosing What to Look At
    Native Active Perception as Reasoning for Omni-Modal Understanding
    Xing, Xu, Wang et al. · The Chinese University of Hong Kong·21 min·Jun 18, 2026
  18. 149
    When Cornering a Chatbot Makes It Lie: J.P. Morgan's Case for 'Playing Dead'
    Is Your Agent Playing Dead? Deployed LLM Agents Exhibit Constraint-Evasive Fabrication and Thanatosis
    Rodríguez, Pozanco, Borrajo · J.P. Morgan AI Research·23 min·Jun 16, 2026
  19. 147
    Agents Fail at the Body, Not the Brain: A Self-Rewriting Scaffold That Lifts a 9B Model 44 Points
    HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry
    Chen, Lu, Zhao et al.·30 min·Jun 15, 2026
  20. 142
    Training a Tiny Model to Run the Plumbing Between an Agent and the World
    HarnessBridge: Learnable Bidirectional Controller for LLM Agent Harness
    Wang, Wang, Taylor et al. · University of California·24 min·Jun 12, 2026
  21. 132
    The Agent Failed — But Did the Instructions Deserve to Be Followed?
    SkillAxe: Sharpening LLM-Authored Agent Skills Through Evaluation-Guided Self-Refinement
    Gautam, Radhakrishna, Gulwani · Microsoft·30 min·Jun 11, 2026
  22. 131
    Why Autonomous Research Agents Forget Their Own Lessons, and Arbor's Fix
    Toward Generalist Autonomous Research via Hypothesis-Tree Refinement
    Jin, Hu, Qiu et al. · Renmin University of China·33 min·Jun 11, 2026
  23. 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
  24. 125
    AI Coding Agents Run a Marathon, and Fewer Than One in Three Finish
    SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?
    Desai, Hu, Cabezas et al. · Abundant·27 min·Jun 09, 2026
  25. 113
    What If a Prompt Injection Never Left? Attacks That Wait in Agent Memory
    What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems
    Xie, Liu, Zhang et al. · Institute of Information Engineering·27 min·Jun 04, 2026
  26. 111
    How a 4B Web Agent Beat Models 60x Its Size on 500 Demonstrations
    OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents
    Yang, Wu, Chen et al. · UIUC·24 min·Jun 03, 2026
  27. 086
    Why Frozen-Weight Agents Still Get Worse Over Time
    Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems
    Zhu, Ro, Robertson et al. · The University of Texas at Austin·23 min·May 27, 2026
  28. 085
    Why Long-Context Models Might Need Compute, Not Capacity, Before Eviction
    Language Models Need Sleep
    Lee, McLeish, Goldstein et al. · Carnegie Mellon University·24 min·May 26, 2026
  29. 083
    Training the Translator: How a Small Communication Model Lets Agent Teams Outperform Themselves
    AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning
    Hu, Qian, Wang et al. · GSAI·24 min·May 26, 2026
  30. 082
    Training a Deep Research Agent on 8,000 Synthetic Tasks: The Rubric Tree Trick
    QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks
    Xie, Lin, Wang et al. · The Ohio State University·31 min·May 26, 2026
  31. 051
    Why Parallel Sampling Plateaus, And What Evidence Graphs Do Instead
    Argus: Evidence Assembly for Scalable Deep Research Agents
    Zhang, Su, Chen et al. · MiroMind AI·22 min·May 18, 2026
  32. 044
    How One Sentence and a Forged History Flip the Most Aligned Models
    History Anchors: How Prior Behavior Steers LLM Decisions Toward Unsafe Actions
    Salgado · Independent Researcher·23 min·May 15, 2026
  33. 012
    Why AI Coding Agents Keep Trying to Debug Without a Debugger
    Dynamic analysis enhances issue resolution
    Liu, Wang, Chen et al. · Sun Yat-sen University·21 min·May 02, 2026
  34. 002
    An AI Ran a Real Optics Lab for 21 Hours and Found a Transformer-Shaped Pattern in Light
    End-to-end autonomous scientific discovery on a real optical platform
    Yang, Chen, Zhao et al. · Zhejiang University·29 min·May 01, 2026

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