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Context Engineering for AI Agents: 4 Failure Modes to Avoid Analytics Table
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Learn more about Context Engineering here → https://ibm.biz/~5YM1VAeG0 More context should make AI agents better. It often does the opposite. Martin Keen explains context rot, the four major context failure modes, and how context engineering improves long-running AI agents. Learn why better agents often require less context, not more. 00:00 - Bigger Context Windows, Better AI Agents? Not So Fast 00:45 - Context Rot: Why AI Models Become Less Reliable Over Time 01:05 - What Is Context Engineering and Why Does It Matter? 01:50 - Inside an AI Agent’s Context Window: What’s Taking Up Space? 04:35 - Context Poisoning: When Bad Information Becomes ‘Truth’ 05:20 - Context Distraction: How Long Histories Derail Agent Performance 06:03 - Context Confusion: Why Too Many Tools Hurt AI Accuracy 06:55 - Context Clash: When Conflicting Information Breaks Reasoning 07:32 - 4 Context Engineering Fixes: Validate, Compact, Curate & Prune 09:50 - The Key Lesson: Why AI Agents Often Perform Better with Less Context AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/~D9ApFMnpA AI was used in the creation of the transcript and metadata for this video. #aiagents #contextengineering #aiworkflows #ai --------------------------------------------------------------------------------------------------------- Find us on YouTube: 🔵 IBM Technology: https://www.youtube.com/@IBMTechnology 🔵 IBM: https://www.youtube.com/@IBM 🔵 IBM Developer: https://youtube.com/@IBMDeveloperAdvocates
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