Case Study
A common mistake in the current era of AI engineering is treating the LLM as an omniscient senior developer.
I initially experimented with feeding entire directories of the legacy Java application into the AI context window, asking it to refactor the whole system into FastAPI.
It was a spectacular failure. The sheer volume of undocumented business logic, historical patches, and sprawling dependencies caused context collapse. The AI hallucinated variables and missed critical edge cases. AI coding is powerful, but it is currently bound by complexity ceilings. You cannot throw a monolith at an LLM and expect a microservice in return.
This path doesn't work. Time to reconsider.