Why Low-Code and No-Code Are Already Losing to Agentic AI

Low-code and no-code platforms have been presented as the future of software development for years. 'Everyone can build now!' was the promise. But in 2025, we're witnessing a fundamental shift. Agentic AI is taking over the advantages of these platforms while eliminating their biggest drawbacks.

The Original Promise of Low-Code

Platforms like OutSystems, Mendix, and Microsoft Power Apps promised a lot:

Faster development through visual interfaces
Less dependency on scarce developers
Lower costs through increased productivity
Accessibility for 'citizen developers'

In theory, this sounds fantastic. In practice, reality proves more stubborn.

The Hard Reality: Hidden Complexity

The Learning Curve Isn't As Low As Promised

Take OutSystems as an example. Despite the 'low-code' positioning, the platform requires a significant investment in time and training. You need to learn their specific abstractions, understand their proprietary logic, and master their development environment. This isn't an intuitive experience. It's learning a new language.

On average, it takes three to six months before a developer becomes productive on a platform like OutSystems. And that knowledge isn't transferable. Moving to Mendix or another platform? You start from scratch.

Vendor Lock-in: The Golden Cage

The most underestimated risk of low-code is the total dependency on the vendor. Your application doesn't run on standard infrastructure, it runs on their platform. This has far-reaching consequences:

Price increases: You have no negotiating position when your application can't migrate.
Platform discontinuation: What if the vendor stops or gets acquired?
Limited integrations: You're dependent on what the platform supports.
Export restrictions: Exporting code is often impossible or produces unreadable output.

Legacy Before You Know It

Here's the fundamental problem: low-code applications become legacy quickly. You're bound to the platform's update cycle. New frameworks, better libraries, more efficient architectures: you can't access them. You're stuck in the ecosystem you chose five years ago.

Traditional codebases with modular architecture can be modernized component by component. A React component can be replaced, an API can be rewritten, a database can be migrated. With low-code platforms, this is fundamentally impossible.

The Rise of Agentic AI

In 2024 and 2025, a paradigm shift is underway. AI assistants like GitHub Copilot, Cursor, Claude, and Google Antigravity are transforming how software is built. But the real breakthrough lies in agentic AI: autonomous systems that independently execute complete tasks.

What Makes Agentic AI Different

Unlike traditional code-completion tools, agentic AI systems can:

Break down complex tasks into subtasks
Independently write, test, and debug code
Make architectural decisions within given constraints
Generate and maintain documentation
Perform refactoring across multiple files

This means the barrier to building software drops dramatically, but with real, transferable code.

Why AI Beats Low-Code

1. Lower Learning Curve

The learning curve for agentic AI is surprisingly low. You don't need to learn proprietary systems. You communicate in natural language and the AI generates standard code in common languages and frameworks. A developer with basic knowledge of Git and an IDE can be immediately productive.

Compare this to OutSystems, where you first need to complete their certification track before you can build anything substantial.

2. No Vendor Lock-in

Code generated by AI is your code. It runs on your infrastructure, in your repository, with your deployment pipeline. You can switch AI tools without any migration effort. Claude today, GPT tomorrow, an open-source model next week. The code stays the same.

3. Financial Freedom

This is where it gets interesting. Low-code licenses often cost thousands of euros per user per year. OutSystems' enterprise licenses can run up to €50,000+ per year. Mendix and similar platforms use comparable pricing models.

AI tools, on the other hand, operate at a completely different cost level:

GitHub Copilot: ~€19/month
Claude Pro: ~€20/month
Cursor Pro: ~€20/month
Google Antigravity: Free

For the price of one OutSystems license, you can equip an entire team with AI tools.

4. Modular Modernization

Code in a Git repository is inherently modular. You can:

Upgrade individual components to newer versions
Replace frameworks without rewriting the entire application
Split off microservices when scalability demands it
Adopt new technologies when they mature

This is the antithesis of low-code, where you're stuck with what the platform offers.

5. AI Gets Better, Platforms Don't

AI models improve exponentially. What costs an hour today will cost ten minutes next year. The quality of generated code rises, context windows grow larger, integrations go deeper.

Low-code platforms evolve incrementally. They add features, but the fundamental limitations remain. You can't escape their architecture.

The Downside of Low-Code in Practice

OutSystems: A Case Study

OutSystems positions itself as an enterprise-ready low-code platform. And for specific use cases like internal tools and simple CRUD applications, it can be effective. But the reality for more complex projects is less rosy:

Limited customization: As soon as you want something outside the standard components, you hit a wall.
Performance issues: The generated code isn't optimized for your specific case.
Debugging is a nightmare: You're not debugging your own code, but abstraction layers you don't understand.
Talent is scarce: OutSystems developers are more expensive than standard developers because the market is smaller.

The Migration Illusion

You often hear: 'We can always migrate later.' This is a dangerous assumption. After years of development on a low-code platform, you're stuck with:

Thousands of hours of platform-specific logic
No exportable codebase
No documentation usable outside the platform
A team that only knows this platform

Migration in practice means: rebuilding from scratch.

The Practical Benefits of Repository-First Development

When you manage code in a Git repository, it opens doors that low-code keeps permanently closed:

AI Agent Freedom

With a codebase in a repository, you can deploy any AI agent. Want Claude for architecture and Copilot for implementation? No problem. Want a locally running open-source model for sensitive code? Fine. You're not bound to one ecosystem.

Continuous Integration & Deployment

Modern CI/CD pipelines are built around Git. Automated tests, code reviews, staged deployments: this is standard practice for code repositories. Low-code platforms try to imitate this, but it's never equivalent.

Open Source Ecosystem

The JavaScript, Python, and other ecosystems contain millions of packages. Every library, every framework, every tool is at your disposal. With low-code platforms, you're limited to their marketplace and approved integrations.

When Low-Code Still Works

To be fair: low-code still has legitimate use cases:

Internal tools: Simple admin panels or dashboards where longevity isn't critical.
Rapid prototyping: Concept validation before investing in real development.
Non-technical teams: Departments wanting to automate simple workflows without IT involvement.

But for production applications with an expected lifespan of more than two years? The risks don't outweigh the supposed benefits.

The Future: AI-Augmented Development

The future of software development doesn't lie in simplifying code into visual blocks. It lies in empowering developers with intelligent assistants that abstract away complexity without sacrificing flexibility.

This means:

Standard codebases that anyone can understand
AI agents that do the heavy lifting
Full control over infrastructure and deployment
No vendor lock-in, no surprises

Conclusion: Make the Strategic Choice

The question is no longer 'low-code or traditional development'. The question is: 'Low-code or AI-augmented development?'

And the answer is becoming increasingly clear. Agentic AI offers the same promise of speed and accessibility that low-code once made, but with real code, full ownership, and the freedom to evolve.

For organizations facing this choice now: choose the future. Choose code that belongs to you. Choose flexibility. The initial investment in good architecture pays for itself many times over when you're not stuck in a platform that can't keep up.

Considering a new project or want to migrate existing low-code applications to a modern, AI-supported architecture? Get in touch for a no-obligation conversation about the possibilities.