Developer Spent 10x Longer Debugging AI-Written Code Than Writing It by Hand

A developer building a data pipeline that pulled from three APIs and loaded a Postgres database let an AI write most of the code, then spent about 14 hours debugging it against roughly 90 minutes of original writing time. The code looked clean and well-documented, yet the pipeline crashed nightly at a precise time, 2:37 AM. Examining the failures, the author found that AI tools tend to break at the edges, such as incorrect API usage, deprecated parameters, and mixed synchronous and asynchronous library calls. Overly abstracted helper functions also caused trouble when their assumptions were wrong, such as a webhook signature check that assumed lowercase hex input. The author argues that the confident quality of AI output discourages the review that would catch these errors.