Optimizing a Shopping Agent Through Prompting and BenchmarkingOptimizing a Shopping Agent Through Prompting and Benchmarking
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Improved an existing shopping agent by treating the independent grading criteria as its specification. The process involved rebuilding its prompts around measurable requirements, testing one change at a time, and selecting GPT-6 (Astra) over Opus 5.1 based on actual graded performance. The resulting agent achieved a strong competition ranking and generated significant revenue.
Core skills: AI agent development, prompt engineering, benchmark analysis, model evaluation, and iterative optimization.
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