Alberto Fortin found that using LLMs in production code introduced bugs and messy code, making maintenance harder.
Early AI features felt impressive but often led to new errors that delayed development further.
Developers should treat LLMs as assistants under their direction, not as replacements for their own planning and expertise.
Small, well-scoped tasks like code refactoring are safer uses of LLMs than implementing large features.
A balanced approach to AI—leveraging its strengths while relying on human architectural decisions—yields the best results.
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