?What are real examples of vibe-coded products that actually shipped to production?

On Hacker News, commenter K0balt described building production firmware end-to-end with LLM assistance — sensors, wire protocols, RF systems, swarm networks, around 10-20 KLOC of C++ per project. The method: specify, specify, specify. First you use the LLM to help you write a spec ... Make sure the spec is correct and matches the user story and edge cases. The LLM is good at helping here too. Then break down separations of concerns, APIs, and interfaces. Each step is followed by a re-evaluation of the entire stack before moving forward. K0balt’s reported outcome: doing what used to take 2 devs a month, in 3 or 4 days on my own. The key constraint they name: You still need seasoned engineers to manage it and catch the occasional bad judgment. Pattern: vibe coding succeeds when the architecture and constraints are front-loaded before any code is written — the LLM is treated as a fast obedient junior, not an architect.

On Hacker News, commenter Shabamed shared a 3-step methodology behind shipping multiple production apps using Cursor with very little manual intervention: Step 1: architecture first (before a single line of code) ... Step 2: turn the architecture into small boring tasks ... Step 3: now I let Cursor work (with rules). Before opening Cursor, they draft an architecture.md and tasks.md in plain ChatGPT — folder structure, where state lives, how things talk. Then strict rules to Cursor: minimal code only, no refactors unless asked, no unrelated changes, don’t break existing behavior, stop after each task so I can test. Their framing of why most vibe coding fails: intent isn’t frozen. When intent is fuzzy AI fills gaps with guesses. Those guesses compound. That’s how you get “it worked yesterday” bugs. Pattern: success comes from physically separating planning artifacts (markdown docs) from execution sessions (Cursor) — once you mix them, intent drifts and the model invents.

On a Show HN post, Jaycobski wrote: I’m a marketer (6 years in SaaS) who spent the last year learning to build software using purely AI assistance (“vibe coding”). I just shipped my first production app for the Oil & Gas industry. The product, BasinCheck, replaces clipboard and Excel workflows for Safety Managers in the Permian Basin — offline audits, hot work permits, automated OSHA 300 logs. A niche B2B vertical that traditional dev teams wouldn’t bother building at startup-scale ROI. Pattern: vibe coding’s success cases cluster in places where (1) the builder has deep domain knowledge in a non-software field and historically couldn’t translate it into code, and (2) the vertical is narrow enough that big SaaS vendors haven’t bothered — so the LLM’s imperfect output is still better than the spreadsheet that currently exists.