Five silent bugs that broke an LLM app without raising a single error

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A developer spent over two weeks building an AI agent that reads code review history from the pandas project and distills conventions from 86,000-plus comments stored in CockroachDB. Every major bug shared the same trait: no exceptions were raised, tests passed, and the demo appeared functional while a component quietly did nothing. One bug caused the agent to treat a model's string "false" as truthy, turning a refusal into a confident answer due to Python's bool coercion rules. Another silently discarded valid model responses because Pydantic rejected JSON null values for plain string fields, causing real maintainer corrections to be logged as ignored. A third bug left 68 of 79 scoped rules matching nothing for an entire week, since the model wrote SQL LIKE wildcards using percent signs instead of glob-style asterisks that fnmatch actually understands.

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