Was talking to a friend working in a startup with an AI focused product and asked him how is AI helping them. He answered that it allows them to make releases faster. You should have seen the look on his face when I asked “so what? Are the releases bug free? Do they solve the business requirement without errors?” It blew his mind when I asked this and he told me they can now release the fix faster.
The above behavior is typical when you talk to AI proponents. The main selling point for them is that you can release faster. My counterpoint is that are the faster releases solving business problems faster? Or allowing you to push out fixes for stuff that doesn’t work/broke in production because you didn’t check it correctly? If it is the former then fantastic. That is what I need AI to help me do, nut if it is the latter then it is of no use to me or the business. People forget that IT is not there in a company to try out the latest tools or use the latest technologies. It is there to solve business problems and deliver solutions that help business proceed. If this means using a 30 years old technology because ‘it just works’ then that is what you do. Whatever we do that doesn’t give fast, reliable and efficient releases is of no use.
Taking the example of being able to release faster. It is awesome if I can release features faster to production, but if the release introduces bugs or breaks functionality it is worse than a slow release because till the fix is deployed their work is stuck or they are getting wrong information which means that the work needs to be redone post the fix being deployed. How is that a win for the business? Sure, in some cases it is a genuine win because you released a feature faster but in a majority of vibe-coded instances it is something that kind-of-sort-of works and you have to go back and release a fix because something broke. This is apparent in the stability and uptime of every single application/site that has boasted of using vibe-coding be it Microsoft with its multiple bug-fix releases, Twitter going down almost daily, Amazon services going down because of AI release deleting production data and many other such examples.
Another issue that people don’t really think about is maintainability of code. People tend to thing that code can easily be replaced with newer code when we need to, but the people who think like that never had to work with 30 years old legacy code that can’t be replaced because it is running critical systems and it is too expensive to replace. Every bank I have worked in has ongoing multi-year project to replace mainframes with newer systems. Think about that, mainframes are older than I am still run critical banking systems worldwide. Similarly we have other critical systems that run old code that has to be managed and with AI generated code that is difficult to achieve if you have not reviewed/updated/understood the code on an ongoing basis. It does get things to a working state (most of the time) but it also in a lot of cases create code that is very hard to maintain. For example, the below screenshot was posted on the vibecoding reddit a little while ago and this is similar experiences faced by others in the industry when they do pure vibe-coding.
r/vibecoding ( 19h ago )
vibe coded for 6 months. my codebase is a disaster.the app works. users are happy. revenue is coming in.( that’s
actually the only good part)but i just tried to onboard a dev to help me and he opened
the repo and went quiet for like 2 minutes. then said “what is
this.”6 months of cursor and lovable and bolt. every feature
worked when i shipped it. but nobody was thinking about
structure. the Al just kept adding. new file here, duplicate
function there, 3 different ways to handle the same thing
across the codebase.tried to refactor it myself last week. gave up after 2 hours.
the thing is so tangled that touching one part breaks
something completely unrelated.the generation was fast. the cleanup is a nightmare.
is there even a way out of this or do i just rewrite everything from scratch?
Finally, if AI/LLM’s were so good and perfect in generating code you wouldn’t need an industry wide media campaign to get people to use it, folks would use it on their own without companies having to track the usage and incentivize it. I have been coding for 28+ years now and have seen multiple advances/changes in how we code over the years. For example when IDE’s started supporting auto-complete for boiler-plate stuff people immediately started using it. When git came out folks started using it and immediately found it useful so no push was needed to get people to adopt the new tool. The same folks then pushed their work IT teams to start supporting git in the enterprise. If Microsoft/Amazon and other companies have to mandate their teams to use AI then it looks like the rank and file are not finding the tools to be that useful.
Personally I love it for Proof of Concept or quick and dirty prototyping/trying out new things. But before any code that is AI generated goes into production you need to ensure it is reviewed by a human who knows coding.
– Suramya