Vibe coding requires more than a vibe

Vibe coding, or the act of using AI to write pieces of software, has taken off in 2026 due to the benefits it promises. Folks without development backgrounds are afforded the potential to produce fully formed, powerful tools with merely a prompt or two, saving countless hours of coding training. These can often be created with far fewer resources and wind up custom-tailored to the needs of an organization. More than a third of all code produced globally, 41%, has been written by AI.

Even seasoned developers have started adopting vibe coding practices because of the undeniable benefits. A whopping 92% of developers claim to use AI tools daily, and 74% of those developers report increased productivity.

Vibe coding has become so ubiquitous that the practice is being decried as the killer of SaaS as a whole. If customers can deploy AI capabilities and build form-fitting software themselves, updating it over time with further vibe coding sessions, the argument is that they won't require the help of a software vendor at all after that initial AI implementation. The customer need not even have developers on staff to put together a functional piece of software, affording more power to the uninitiated.

The truth about vibe coding exists somewhere between an egalitarian empowerment mechanism and the slayer of an entire industry. When used properly, the prevalence of vibe coding helps SaaS vendors align with customer expectations and increase speed-to-solution production, positioning them to support customers in the long term.

Bad vibes

It's important to recognize that the metrics around vibe coding don't tell the whole story.

On the surface, it seems like vibe coding can save companies money. They no longer need to hire developers or employ a SaaS vendor to compete with bigger players in terms of software. Code can be changed on-the-fly, adding new features that might have taken a SaaS vendor a fair amount of time and resources to implement. The practice also guarantees that customers only get what they want to pay for, rather than having to choose a plan offered by a SaaS vendor that includes software they might never use.

What's missing from these points are all the downstream costs that aren't accounted for in these arguments. The software needs to be reliable, and considerable effort has to be put into ensuring that whatever's produced by vibe coding can stand the test of at least a modest amount of time.

Developing a piece of software in a vacuum doesn't offer enough of a boost to sustain an enterprise organization. Many of these companies run on legacy software, as the cost of changing vendors is prohibitive. A new piece of software built via vibe coding will have to be integrated into what already exists in a way that automates processes that weren't previously economic, rather than attempt to replace pieces of mission-critical SaaS. This requires lots of manpower or, at the very least, a close watch over any AI that might be handling this task. There will likely be multiple vibe coding iterations occurring, turning a streamlined piece of software into the exact sort of Franken-program the company was trying to avoid in the first place.

It's worth considering the costs associated with everything that happens after the software is completed. Privacy legislation changes over time and varies by region. The proliferation of data centers pulls into focus issues surrounding data sovereignty, or who owns which pieces of data and by whose laws should it be governed. And, if vibe-coded software can't perfectly integrate with existing software, the entire system leaves itself vulnerable to bad actors, increasing the chances for a security breach to occur — requiring much damage control after-the-fact.

Companies that vibe code also need to worry about shadow IT, a term applied to the practice of business teams leaning on makeshift technology solutions when the IT team's company-sanctioned software fails. This can take the form of multiple spreadsheets of different versions, barrages of emails, or working with an unproven third-party vendor when employees get tired of waiting. Developers understand the difference between software for software's sake and a solution built to last — since vibe coding is a practice usually taken up by non-developers, there's real danger in their software output never quite living up to potential.

Good vibe

When vibe coding is considered part of the software development process, and not the entirety of the process itself, it serves as a strong accelerator and communication tool that enhances the final product.

For starters, vibe coding does wonders for the prototyping phase. Under normal circumstances, producing a working software prototype takes a significant amount of time, and the result is merely a building block or proof-of-concept that requires much more work to complete. With the help of vibe coding, teams can create testing environments and hand off prototypes in a fraction of the time, allowing for the feedback portion of development to kick off sooner, shortening the length of the development process substantially. Non-developers can also build a vibe-coded prototype off merely an idea they'd like to share, with AI serving as a translator, of sorts, to communicate with developers.

There's also the new maxim that vibe coding, and AI in general, can handle repetitive tasks, freeing up folks to focus on bigger picture concerns or mission critical projects. This premise is mostly true, but carries a few caveats. A recent Harvard Business Review piece warned of "AI Brain Fry," which occurs when users have more than three AI tools running simultaneously and are tasked with overseeing them all. Despite the amount of work being saved, these users reported feeling more overwhelmed with oversight than they did performing the tasks to begin with. This caused them to experience decision fatigue, burnout, and suboptimal decision-making, all of which can cost companies money.

Vibe coding can also be effective when teams are aware of what the final product looks like. A company replacing its legacy ERP solution requires a lot of fine tuning to ensure business can operate as usual during the transition and that the ultimate result is one that won't cause frustration among employees. Vibe coding can aid with this process by simplifying coding software updates, allowing for a more robust testing phase. The practice of vibe coding works well if given specific parameters, and there can be nothing more rigid than an enterprise's outmoded software suite.

The importance of guardrails

Enterprise software becomes difficult to use when it doesn't fit within strict guardrails surrounding privacy, security, governance, and data sovereignty — those downstream costs we mentioned earlier. These protections will remain constant for years to come, far outlasting the hype surrounding the latest, greatest AI tool. Vibe coding without these key pieces in place will ultimately waste time. And it's highly unlikely that non-developers taking up vibe coding will have the experience to understand how to take guardrails into account.

This is an area where SaaS vendors can shine. They can build guardrails around their tech stack to protect existing software, and allow vibe coders to work only within a predefined space where those guardrails can remain firmly in place. Anything produced will more easily integrate into the current system if it's designed upon the same bedrock.

The practice of installing guardrails also opens avenues for communication with customers. A vibe coder could create a piece of software that isn't quite finished, then hand it off to the SaaS vendor, who can complete the work and ensure it runs within the same ecosystem and within the same limitations as everything else. This means that vibe coded software is more likely to integrate, customers are more likely to see their ideas in practice, vendors can serve as direct partners, and the risk of a data breach or governance issue remains low.

When to vibe

Vibe coding holds massive potential, but should still be used sparingly and at the proper phase of the process.

Consider a recent study pre-published by Cornell University, titled “Your Brain on ChatGPT — Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task.” The researchers studied the difference in cognitive activity between writing an essay aided by an LLM, writing one using a search engine, and writing one with only the participant's brain. The results demonstrated that total reliance on LLMs is a dangerous proposition. LLM-users were less engaged with the process, felt less of a sense of ownership over the final product, and even had trouble quoting from their essays mere minutes after it was complete.

The trick, then, is to utilize vibe coding not as a starting point but as a way to refine ideas that may already exist. Even when using vibe coding for rote tasks, it's important that the user understand what's being streamlined so they can better articulate the ultimate results. This means that even non-developers should consider learning a few foundational software development principles before embarking on their vibe coding journey, lest they find themselves holding lines of code with no idea how they can be practically useful.

Despite its name, vibe coding is more than an of-the-moment craze. It represents the next step in the democratization of technology away from traditional gatekeepers. SaaS providers that embrace smart, strategic use of vibe coding, seeing it as a way to empower customers, are positioned to thrive in this next chapter.