Vibe coding was funky, then it was clunky. The ability to describe a software application’s intended form and function in natural language and then use a variety of agentic AI services to formulate and construct its codebase fitted the narrative of the agentic age, seemingly in perfect rhythm.
But like all complex syncopation structures, it’s easy to miss a beat if you don’t know all the steps.
Why vibe potentially stumbles
Perhaps due to the transparency of its abstraction layers, possibly due to the spaghetti junctions of dependencies it can throw up, or perhaps due to a lack of foresight into the intricacies of bringing this type of application online in a debugged and stable state ready for scaling, vibe coding projects have been criticized for their constrained ability to go from a standing start zero to around 80% almost instantaneously, but no further.
“What if QA agents ran in parallel within these [vibe] tools? Dedicated agents checking workflows in the background, validating that established rules still hold after every iteration.” – Neha Vyas.
Software programmer and Stanford University Graduate School of Business graduate Neha Vyas tells The New Stack that the 80% problem in vibe coding is real. She’s seen environments that reach a working prototype almost instantly, and then the next 20% takes more time and effort than the first 80% combined. In her experience, every fix spawns three new edge cases, every prompt patch breaks something upstream – so it’s not a tooling failure; it’s an architectural one.
“What vibe coding is still missing is a quality mindset baked into the loop itself,” says Vyas. “When I was building with AI agents, I kept thinking: what if QA wasn’t a phase you hit at the end, but a parallel process running the entire time? Dedicated agents working in the background, validating that established rules still hold after every iteration — catching regressions before the developer even notices them. Not manual rechecking after every prompt, but continuous contract enforcement woven into the agentic workflow.”
Glowing honeymoon, early divorce
Given the early divorce from vibe coding after the initial glowing honeymoon period last year, it would take a brave approach to attempt to lay down a comprehensive vibe coding platform offering in 2026.
That harsh reality hasn’t put Quickbase off. The company introduced Pave on Tuesday, a technology toolset that is described as a full-stack AI application builder. The company says it can take software engineering teams from prototypes to production-ready apps that meet enterprise requirements.
Pave promises developers a set of built-in governance controls along with IT oversight controls (that term here meaning a single interface for DevOps professionals to assess total application state), as well as data services, governance, permissions, hosting, and deployment tools, all built in.
Marcus Torres, chief product officer at Quickbase, says that most vibe coding tools focus on getting teams from A to B, i.e., from prompt to prototype. But, he pledges, Pave is designed to take teams from A to Z.
“Other app builders often come with hidden runtime and infrastructure costs that make it hard to forecast pricing as usage scales,” said Torres. “With Pave, teams don’t need to juggle a stack of third-party tools, separate databases, cloud hosting setups, custom domains, or the operational overhead that comes with stitching it all together.”
Torres and team explain that Pave provides an interface that lets users enter plain-language descriptions of the problem they need to solve. Users then iterate using the tool’s no-code interface to create deployable apps, complete with the application’s structure, logic, permissions, and governance. The claim here is that the resultant apps are production-ready and usable in the real-world business environment – immediately.
Pave already includes the data management, cloud hosting, and deployment infrastructure needed to move apps into production. There’s no separate database to manage, no selection pack of third-party vendors to integrate, and no credit-based pricing that becomes harder to forecast as usage scales.
Developers, steady as you go
Founder & CTO of Contrast Security and also a founder of OWASP Jeff Williams tells The New Stack that Pave looks like “a much better model” for AI app generation because it puts vibe coding inside a governed enterprise environment.
“Identity, permissions, data, audit, deployment, and rollback all stay inside one controlled platform,” Williams says. “That is meaningfully safer than letting every business user spin up their own little cloud application with unknown code, unknown data, and unknown risk.”
But, he cautions, a safe environment does not automatically make a safe application – namely, because the hard part is still the application logic. Williams urges developers who are grasping tools at this level to steady themselves and step back to assess whether the AI created the right permissions, the right workflow, the right data boundaries, and so on.
“Coders will need to ensure that even this new breed of vibe coding assistants has avoided the same vulnerability classes that have plagued software for decades. Pave apps still need architecture, review, testing, and runtime security – and it’s wise to never assume that all those things are a given until they have been identified, quantified, and validated,” adds Williams.
Single interface oversight
With built-in cautionary checking mechanisms on board, Pave offers granular user permissions, SSO authentication, audit trails, and version rollback capabilities. Relationships, logic, notifications, and views can be customized to fit existing business processes and branding, instead of forcing teams into templates.
An unnamed Pave beta user who serves as a lead cybersecurity & risk partner at a Big Four consulting firm is on the record saying that their team has “a real comfort level” with keeping sensitive data within Quickbase. They state that the tool provides a fluid creation experience, along with the security guardrails that Quickbase already has in place for data and access control.
“The PocketOS outage was caused by agent goal hijack… tool misuse… and identity/privilege misuse… These are all covered in the OWASP Top 10 for Agentic AI.” – Neil Carpenter, Minimus.
Principal solutions architect at cloud containerization specialist Minimus, Neil Carpenter, tells The New Stack that the inclusion of enterprise IT security controls and governance will be an important enabler for security leaders who want to greenlight agentic AI development tools that align with the vibe coding groove.
However, he says, the guardrails offered by Pave appear to focus on “traditional security problems” such as access management and auditing; he says they omit to address the sorts of problems that lead to security incidents originating from vibe coding.
“For example, the PocketOS outage was caused by agent goal hijack (as the agent made a decision to delete a volume on its own to address an issue), tool misuse (used cURL to call an API to delete the volume), and identity/privilege misuse (used an API token that was created for a different purpose and had more privilege than desired). These are all covered in the OWASP Top 10 for Agentic AI,” Carpenter says.
Safety dance?
Whether or not we’re safer to vibe code now feels like a calculation riddled with incongruent moving parts that may not all align, depending on an organization’s security posture and possibly on which way the wind is blowing. While Quickbase’s Pave almost certainly gets us one step closer to the vibe coding dancefloor, the risk of a misplaced step is (arguably, if not certainly) still there.
As long as you keep caution, security, and governance on your dance card, for now at least, the vibe beats on.
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