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Developer Builds Custom IDE After LLMs Struggle to Manage Complex Codebases

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A software developer spent several years experimenting with large language models to determine whether they could independently break down, solve, and assemble complex software projects. Early attempts using large instruction sets proved unmanageable, as both the developer and the AI grew confused by the volume of rules. Switching to a Retrieval-Augmented Generation approach with atomic rules introduced a new set of unresolved questions around knowledge splitting, rule verification, and contradiction handling. A key limitation emerged around 3,000 lines of code, where context windows filled rapidly and models lost coherent understanding of the overall project. This led the developer to abandon off-the-shelf tools, build a custom IDE, and adopt design principles centered on transparency, verifiability, and reproducibility for AI-assisted development.

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Developer Builds Custom IDE After LLMs Struggle to Manage Complex Codebases · ShortSingh