Developer Shares 'Prototype and Port' Method for Using AI on Complex Codebases

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A developer building a beat-maker web app shared a workflow for using Claude AI effectively on large, complex files. Instead of feeding Claude a 1,500-line HTML file directly, he first prototyped the core logic in small, isolated Python scripts to prove the concept worked. He built scripts to read, access by index, and replace items in a JSON array of drum presets, verifying each step against real data. Once the logic was confirmed, he mapped each prototype element to its equivalent in the web app — such as a JSON file to an in-memory array, or a command-line argument to a dropdown menu. With a clean conceptual map in hand, he wrote a single precise prompt to port the proven logic into the actual project, minimizing errors caused by irrelevant code noise.

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