How much of "vibe coding" is actually just disciplined QA? Curious what others have found.
I'm a veteran and solo founder with no formal coding background. Spent the last few weeks directing Replit's AI agent (with Claude as a strategic/QA partner) to build a real production app, entirely from my phone.
The part that surprised me: the "vibe" is the easy 20%. The other 80% was the same discipline any build needs — catching bugs by hand (missing auto-capitalization, a timezone off-by-one, a file upload limit rejecting real phone photos), refusing to accept "it's fixed" without proof, running full walkthroughs section by section, chasing root causes instead of patching symptoms.
That's made me rethink what "vibe coding" even means. It's not skipping the engineering discipline — it's relocating it. Instead of writing code, you're writing precise instructions, reviewing output critically, and doing QA like a hawk. If anything it demands more discipline, not less, because you can't rely on catching mistakes by reading your own code — you have to actually test everything.
For others who've directed an AI agent instead of hand-coding: has your experience matched that, or did you find a different bottleneck? What ended up being the hardest part for you — the instructing, the reviewing, or something else entirely?
Replies
It arguably requires much more scrutiny because, as Dijkstra put it, the testing shows the presence of defects, not their absence. When AI writes the code, you don't necessarily know what you are even trying to disprove - let alone the introduced unknown unknowns. That applies to every test path, assumption, and edge case, but especially to security.
AI is also prone to introducing regressions in seemingly unrelated places, which calls for high degree of automated testing. Paradoxically, AI can handle this quite well. Automated tests build a useful requirements harness that provides a constant feedback loop for the implementation. But this part still requires human review.
In the end, AI prompting can be seen as another higher-level programming language: it moves the developer further away from the source code, but still demands the same disciplined approach.