Concept · 12 episode(s)

Context Quality

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Definition

Context quality is the (often underappreciated) observation that what you put in a context window matters more than how much you put in. Noisy, redundant, or poorly ordered context can hurt performance even when the relevant fact is technically present.

Episodes covering this

  1. 249
    The Chatbot Knows Your Facts And Still Won't Mention Them
    MemUse: Moving Memory Evaluation from Direct QA to Natural Integration in Long-Term Human-AI Conversation
    Sumida, Inoue, Kawahara · Graduate School of Informatics·19 min·Aug 27, 2026
  2. 214
    The Medical AI Answer That's Accurate, Sourced, and Still Wrong
    Deceptive Grounding: Entity Attribution Failure in Clinical Retrieval-Augmented Generation
    Caruzzo, Yoo, Kim · Lunit·13 min·Jul 13, 2026
  3. 182
    How a Tiny Model Too Weak to Plan Cuts a Bigger Agent's Hallucinations by 80%
    Grounded Iterative Language Planning: How Parameterized World Models Reduce Hallucination Propagation in LLM Agents
    Song, Cai · Emory University·17 min·Jun 29, 2026
  4. 151
    Why More Experience Made This AI Agent Worse, And How to Fix It
    Not All Skills Help: Measuring and Repairing Agent Knowledge
    Wang, Zhou, Liang et al. · UNC Chapel Hill·28 min·Jun 16, 2026
  5. 116
    Why Streaming Half a Reasoning Chain Beats Sending the Whole Thing
    Streaming Communication in Multi-Agent Reasoning
    Yang, Xu, Wang et al. · HKUST (GZ)·26 min·Jun 04, 2026
  6. 097
    Same Tokens, Same Cost, Wildly Different Results: What Actually Scales in AI Agents
    Scaling Laws for Agent Harnesses via Effective Feedback Compute
    Zhang, Wang, Xu et al. · Harbin Institute of Technology·25 min·May 29, 2026
  7. 078
    Training a Markdown File: When LLM Self-Improvement Borrows the Discipline of Neural Net Training
    SkillOpt: Executive Strategy for Self-Evolving Agent Skills
    Yang, Gong, Huang et al. · Microsoft·28 min·May 25, 2026
  8. 064
    When Agent Memory Stops Being a Database and Starts Being a Skill
    Auto-Dreamer: Learning Offline Memory Consolidation for Language Agents
    Ye, Liu, Wang et al. · University of Illinois Urbana-Champaign·30 min·May 22, 2026
  9. 057
    How Uber Caught 206 Leaked Credentials With an LLM-Powered Security Stack
    ADR: An Agentic Detection System for Enterprise Agentic AI Security
    Li, Hu, Xu et al. · Uber Technologies·28 min·May 19, 2026
  10. 052
    An Old Reinforcement Learning Tradeoff Sneaks Back Into LLM Agents
    Look Before You Leap: Autonomous Exploration for LLM Agents
    Ye, Shi, Liu et al. · University of Science and Technology of China / Meituan·23 min·May 18, 2026
  11. 035
    Why Frontier Agents Ask for Clarification at Exactly the Wrong Moment
    Ask Early, Ask Late, Ask Right: When Does Clarification Timing Matter for Long-Horizon Agents?
    Gulati, Gupta, Lumer et al. · PricewaterhouseCoopers U.S.·29 min·May 11, 2026
  12. 003
    How to Pick the Best of Sixteen Coding Agent Rollouts
    Scaling Test-Time Compute for Agentic Coding
    Kim, Yang, Niu et al. · Meta Superintelligence Labs / University of Washington·17 min·May 01, 2026

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