Will AI kill No-Code?
A few years ago, no-code was all the rage. On my LinkedIn feed, I kept seeing posts warning that I'd soon lose my job as a developer… it was a "revolution": build an app, a website, or automate a task without writing a single line of code. But now, generative AI has arrived—capable of coding for you. So… is it game over for no-code? Not so fast, my friend.
No-Code: A revolution already underway
No-code (and especially low-code) opened a huge door: allowing non-developers to create functional tools through visual interfaces (e.g., Webflow, Glide, Airtable, Make…).
It became a superpower for freelancers, marketers, solopreneurs, and small businesses.
One of my sales colleagues managed to build a graphical interface connected to a few REST API calls—in just two days, he had a pretty decent and functional prototype, despite his very limited technical knowledge. (And as a developer, I was glad I didn’t have to take on the project and waste time on such a prototype—long live no-code!).
Generative AI: The new, unpredictable player
With generative AI (like ChatGPT, Copilot, or Gemini), you just ask:
“Build me a task management app with a SQLite database, a React frontend, and a Flask API,”
…and boom — there’s the code.
No need to learn a no-code tool or, for more customization, a low-code tool. Just prompt the AI. And that, potentially, is a game-changer.
No-Code vs AI: A false duel?
In reality, these two approaches aren’t really at odds:
- No-code remains the simplest way to build quickly without worrying about technical details.
- Generative AI is powerful, but still requires at least some understanding of code and core concepts (debugging, logic, architecture).
For many users, no-code feels more safe and predictable than an AI prompt that might be misunderstood.
A fusion on the horizon?
We’re seeing a natural convergence:
- No-code tools integrating AI (e.g., Notion AI, Glide with GPT, Softr + AI).
- AI assistants helping users build inside no-code platforms (like ChatGPT helping you build a Zap in Zapier).
The logic isn’t AI versus no-code—it’s AI within no-code/low-code.
What about Python?
Python, with its accessible syntax and powerful libraries, remains the ideal bridge between traditional development and no-code/low-code tools. More and more platforms now allow users to insert custom Python code to handle specific needs.
Here are a few examples of tools where Python can be integrated: Zapier (via "Code by Zapier", for writing small Python scripts within automations), Make (also offers a "Python" module to run code inside your workflows), Retool (a low-code platform where you can add backend Python scripts to manipulate data or call APIs), … and many more!
Thanks to these integrations, knowing a bit of Python becomes a true superpower in a no-code or AI-driven environment: you can unlock complex use cases, add business logic, or connect systems that would otherwise be unreachable through visual interfaces.
What about the future?
- Simple tasks will go to AI (scripts, web pages, automations).
- No-code tools will become control panels, enhanced by AI blocks.
- Developers will still be essential for complex or critical use cases.
In short: no-code/low-code isn’t going to die. It will evolve. The winning platforms (like Engine) will be the ones that smartly integrate AI. AI isn’t killing no-code—it’s pushing it to reinvent itself.
Conclusion
So, should we bury no-code and low-code? Absolutely not. On the contrary, these tools are about to gain a lot more power and flexibility. They’ll go far beyond their current limits. They still won’t replace developers entirely—but for more and more use cases, they’ll be more than good enough. In some cases, they may even be better suited than hiring a dev.
cyrilou
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