Installing Quality Gates Into Your AI Workflow: Bringing Software Engineering Discipline Into Your Personal System
“It Runs” Does Not Equal “It’s Reliable” Most people’s acceptance criterion for a personal AI system is exactly one thing: does it run? If it produces a result, gives a reasonable-sounding answer, that counts as success. But the moment you actually rely on it to do real work for a while, you’ll hit a second problem: it runs, sure, but how do I know it ran correctly? This is exactly the most hidden risk of a personal AI system. AI doesn’t crash with an error — it will stably, confidently give you output that “looks very correct” — neatly structured, assertively worded, but possibly pointed in the wrong direction entirely. A traditional program’s bug shows a red screen, throws an exception; AI’s “bug” is a fluent, wrong paragraph. If your system has no mechanism at all for detecting when it’s wrong, you’ll charge full speed ahead on incorrect output. ...