"4 Pitfalls in using AI to build software", according to Dane Balia.

"Pitfall #1: Poor problem framing." LLMs are sensitive to your exact choice of words.

"Pitfall #2: Over-reliance on AI."

"Feeding an AI your entire codebase won't magically solve architectural problems or replace developer intuition."

Really? I fed Cursor AI my entire codebase. We'll see how it goes.

He further breaks this down into "Expecting AI to understand under-stated requirements", "Not reviewing generated code for best practices or logic flaws", "Blindly implementing without understanding", and "Using AI for critical security or data handling without review".

"Pitfall #3: Providing insufficient context".

"This is the equivalent of asking a construction company to quote you on building a 3 bedroom house, but forgetting to highlight that the location is on a hill, in a remote location with poor to little infrastructure."

"Pitfall #4: Ineffective iteration".

"Not providing feedback on what worked/didn't work", "Starting over instead of building on previous responses", "Not clarifying misunderstandings in the AI's assumptions", "Failing to narrow down issues when debugging".

Solution: Improve your prompt engineering! (This ought to be a song. Maybe one of you can AI-generate it?)#solidstatelife #ai #genai #llms #codingai