Mendix's Real Approach to AI: Why Checkpoints Beat Black Boxes

There's no shortage of tools promising to build your entire application from a single prompt.

Type a sentence. Get an app. Ship it tomorrow.

It sounds incredible. And for quick prototypes or landing pages, some of these tools deliver exactly that. But here's what nobody talks about: What happens on day two? Day thirty? Day three hundred?

At VeilSun, we're huge believers in AI. 

We use it every day. It saves us time, catches errors we'd miss, and accelerates work that used to take weeks. 

But we've also watched companies bet on "magic prompt" platforms – and we've seen the cleanup that follows.

That's why Mendix's approach to AI caught our attention. It's not flashier than the alternatives. It's more thoughtful. And in enterprise software, thoughtful wins.

The Problem with One-Prompt Promises

Let's be honest about what tools like Lovable, Cursor, and Windsurf actually do well. 

They're excellent at generating what we'd call "vanity foundations.” 

These are the front-end scaffolding of an application. Pages render. Buttons appear. It looks like software.

But what if you take a closer look?

Those buttons don't always connect to anything. The database structure may not reflect your actual business logic. 

And the workflow you needed? It's either missing or hardcoded in a way that'll take longer to untangle than it would have taken to build correctly in the first place.

We've talked with tech leaders who are genuinely excited about AI – and simultaneously terrified. 

Not because AI doesn't work, but because they can already picture the scenario: citizen developers across their organization spinning up disconnected applications, each one a black box, none of them talking to each other, all of them impossible to maintain.

That's not digital transformation. That's technical debt at scale.

Mendix Built AI for the Entire Lifecycle

So, what’s the better solution?

We like to point our clients to what platforms like Mendix are doing. What makes Mendix different isn't that they've added AI to their platform. Everyone's done that. 

What's different is where they've added it – and more importantly, where they've kept humans in the loop.

Mendix calls their AI assistant Maia, and it's woven throughout the entire software development lifecycle. 

Not just the "generate an app" moment, but every stage: requirements gathering, data modeling, workflow design, UI development, testing, deployment, and ongoing optimization.

Here's what that actually looks like in practice.

Say you're starting a new project and your point of contact sends you a PDF with bullet points about what they need. 

It's messy. Half requirements, half wish list. In a traditional process, someone spends hours translating that into user stories.

With Mendix, you upload that PDF. Maia converts those bullet points into structured user stories – and then shows them to you. You can edit them. Add context. Assign roles. Remove the ones that don't make sense. 

The AI did the heavy lifting, but you made the decisions.

Only then do you click to generate. And even at that stage, you're not getting a finished product you can't touch. You're getting a foundation you can inspect, adjust, and refine.

That's the difference between AI as a collaborator and AI as a black box.

Checkpoints, Not Magic

Every other AI tool we've evaluated follows the same pattern: prompt goes in, app comes out, good luck figuring out what happened in between. 

Mendix flips that model. Each phase of development has a clear handoff point where a human reviews, adjusts, and approves before the next phase begins.

Think about it from a technology leader's perspective. When something breaks (and something always breaks) you need to know where to look. 

You need developers who understand what was built and why. You need documentation that reflects reality, not a prompt someone typed six months ago.

Mendix's Maia actively checks your application against established standards and flags issues before they ship. Their Logic Recommender suggests next steps as you build, drawing from patterns across millions of applications. The Workflow Recommender helps you connect the pieces without reinventing solutions that already exist.

Image source: Mendix. “Software Development Life Cycle,” Mendix Evaluation Guide. Mendix.com. https://www.mendix.com/evaluation-guide/app-lifecycle/

AI App Development: Two Approaches

Not all AI-powered development is created equal. Here's how the "type a prompt, get an app" approach stacks up against Mendix's lifecycle-wide, human-in-the-loop model:

The bottom line? One-prompt tools can get you started fast. 

But if you're building software your business will actually run on—software that needs to scale, integrate, and evolve over time—you need more than a magic trick. 

You need a process built for the long haul.

AI Development Generators – A WebMD Problem

Here's an analogy that resonates with us: AI app generators work kind of like WebMD.

You stub your toe, you search your symptoms, and WebMD gives you enough information to decide whether you need ice or an emergency room. That's useful, and it’s a genuine service.

But you wouldn't bet your health on WebMD. You wouldn't skip the doctor because a website said you're probably fine. 

And sometimes, what you get from WebMD can send you down a terrified rabbit hole of horrible symptoms and outcomes. 

The same logic applies here. 

AI can give you a starting point. It can accelerate early-stage work. It can help you think through possibilities faster than you would on your own. 

But enterprise software – the systems your business actually runs on – requires more than a starting point.

It requires people who understand your workflows. People who can ask the right questions about edge cases. People who will still be around in six months when requirements change or integrations break.

Where Mendix (and VeilSun) Fit

We're not here to tell you AI is overhyped. It's not. The productivity gains are real, and they're only accelerating. We think that this has completely changed how developers will approach their work.

What we are here to say is that there's a right way and a wrong way to adopt AI in enterprise software development.

The wrong way treats AI as a replacement for expertise. The right way treats AI as a force multiplier for the people who already know what they're doing.

Mendix built their platform for developers. Maia doesn't replace that expertise. It actually has the potential to amplify it. 

The result is software that gets built faster and remains supportable for years to come.

That's the approach we take at VeilSun. We've spent 17+ years building custom applications across industries, and we've learned that speed without sustainability is a trap. 

The fastest project isn't the one that launches first. It's the one that's still working two years later without constant emergency fixes.

AI can save you millions. It can also cost you a fortune. The difference is whether you're using tools that keep humans in the loop – or tools that promise to replace them entirely.

We know which side of that bet we're taking.

Ready to Get AI Right? Let’s Chat

Whether you're just starting to explore what AI can do for your operations – or you've already experimented with vibe coding tools and hit the limits of what a single prompt can deliver – we'd love to talk.

At VeilSun, we help companies figure out where AI makes sense, where it doesn't, and how to build software that actually scales with your business. 

No pressure, no pitch. Just a conversation about what you're trying to solve.