Vibe coding is the new AI thing advertised on social media. Unsurprisingly we have all the expected marketing material, the influencer posts, the drama of security issues and some pushback.

Obviously the problem with AI generated code is the bugs introduced, the security issues, the outdated code used on training etc. We all know that we know that it won’t get away.
So did everyone lost their minds and wagger the ai slot machine because its code sometimes can be ok?
Of course not.
Organisations avoid pushing unvetted code on production whether it is AI generated or human created. Every deployment that goes south comes along with incidents, post-mortems, claims, regulatory issues and even legal fees. There is no such thing as pushing code to prod lightheartedly whether it comes from an intern, a dev agency or some LLM.
And while the above stands correct it’s not preventing apps, developed with the help of LLMs, to get deployed out there. LLMs are used and will continue to be used. A big part of the Vibe Coding bragging comes from apps that solo entrepreneurs develop/try to develop. This will be/is a huge chapter of ai-generated code.
First will have to exclude a subset of greenfield software that get’s developed . For example you might use AI to create a data warehouse solution from scratch and utilise LSM indexes. Or you might want to apply the Raft consensus algorithm to a solution you created. If you operate at that level, you are already specialized in a field and you are sophisticated enough to know better. Even with AI based assistance it’s highly unlikely to deliver a dud. Proper checks regarding quality and security would be in place, thus future maintenance opportunities due to AI bugs are not there.
Reddit is actually a very nice place where you can see some real life stories of individuals embarking on creating their own software business. Me and most readers of this blog probably have a degree in engineering and software is our profession, yet it’s not that often that we get to see that reality. There are many individuals with zero relation to coding let alone software engineering trying to get in the business of software. It all starts with an idea and then all the steps needed to make it into a software business. Usually this is resource intensive since it needs to pay someone to do the coding. The funds can come either in the form of angel investment, personal finances and maybe relative’s finances. Once the capital is secured a developer/dev agency is hired to build the MVP, MVP is rolled out, demos are successful, customers love the product, hooray what a success!
Too optimistic right?
Now take a look at the cemetery. It is quite difficult to do so because people who fail do not seem to write memoirs, and, if they did, those business publishers I know would not even consider giving them the courtesy of a returned phone call (as to returned e-mail, fuhgedit). Readers would not pay $26.95 for a story of failure, even if you convinced them that it had more useful tricks than a story of success.* The entire notion of biography is grounded in the arbitrary ascription of a causal relation between specified traits and subsequent events. Now consider the cemetery. The graveyard of failed persons will be full of people who shared the following traits: courage, risk taking, optimism, et cetera. Just like the population of millionaires. There may be some differences in skills, but what truly separates the two is for the most part a single factor: luck. Plain luck.
Obviously we don’t get to know the actual failure rate of the attempts to turn an idea into a software business. However we do have an idea how expensive it is to fail when you embark on making a software business, and a big contributor to that is the cost of developers. On top of that there is also the hidden cost of the time someone spends on their idea preventing them from working/gaining experience on other activities.
This makes software a longshot, an expensive longshot.
The odds are high but the costs are considerable. From that perspective AI tooling makes total sense. Since the odds are high at least you need to keep the costs low.
If you think about it, the highly likely scenario of failure removes the needs for any maintenance/bug fixing :
- New app is developed using AI assistance
- New app fails
- Funding of failed app is ceased
- Failed app and its codebase is declared dead
- No furthers funds spend on a dead project
There is still the scenario of a successful MVP. Provided your initial attempts of rolling out your idea are successful fixing AI bugs is a privilege. It’s tempting to think that these successes will lead to more software in need of maintenance.
I believe it won’t be the case. If it’s easy for everyone to create software, then even on a successful MVP launch you still have lot’s of competition to deal with, thus more effort for less reward. Bad ratio of risk vs reward will prevent a product from being developed in the first place. At least for the products we’ve seen showcased using Vibe coding.
Equilibrium?
Do I believe engineers will have more work due to bugs? Not really. I do think there’s gonna be some AI inflicted pain but not as bad as mentioned. Indeed software could be developed with less resources but the easiness of doing so makes the implementation questionable. If anyone can do, it is it worth to develop that idea in the first place? Regardless attempts to make ideas into software will be there, should these attempts succeed, engineers will be there to help.










