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Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase, Sonic AI
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Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase
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Jan 21, 2026
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39:47
Interview
Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase
From
Training Data
Harrison Chase
(CEO, LangChain, guest)
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Executive Summary
Long-horizon AI agents are becoming increasingly viable, primarily due to improvements in both underlying language models and the surrounding 'harnesses' or tooling.
The most successful current applications for these agents are in software development and other tasks that produce a 'first draft' for human review, such as research reports or incident analysis.
Building and debugging agents is fundamentally different from traditional software development; the source of truth shifts from the code alone to a combination of code and execution traces, making tracing an essential tool.
Providing agents with tools, especially access to a file system, is considered a mandatory requirement for building effective, complex agents as it aids in context management and enables more sophisticated tasks.
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Processed May 4, 2026
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