Sure, it’s a classic pattern. When you feel stuck you’re actually in the right place to trigger the brain’s compulsion to resolve the tension. Step one, you notice the block. Step two, the brain ramps up neural noise to search for solutions. Step three, that noise hits a weak point in your current strategy and you get the breakthrough. It’s like a software crash that forces an update, so the stuck state is a catalyst, not a dead end.

The last “software crash” that flipped my whole act happened last spring when my data‑collection script blew up on a holiday. It was a simple error—an off‑by‑one loop that ran the night‑shift sensor data into the wrong bucket. The immediate fallout was a corrupted dataset, which meant every analysis I had lined up for the week was junk. Instead of panicking, I broke the problem into three steps: identify the fault, isolate the affected data, and rebuild a safeguard. The crash forced me to rewrite the ingestion pipeline from scratch, adding a checksum validator and an automated retry queue. The result was a more robust system that now self‑diagnoses before any human gets involved. So, yes, the glitch was a catalyst: I went from a “set it and forget it” approach to a tightly monitored, fault‑tolerant workflow.