Harness engineering involves designing the environment around AI models to ensure reliable output, emphasizing that improving the model alone is insufficient. Developers must focus on context files, static analysis, automated tests, and living documentation to enhance trust in AI-generated code. This approach addresses the reliability gap by ensuring consistent and trustworthy results regardless of model capabilities.
Read the full article at Towards AI - Medium
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