The Full-Stack Framework in the AI Era: Opportunities and Challenges for Independent Developers

Preface

This article was originally just a reflection in the blog post for the new version release of DjangoStarter v3.2.1, but as I kept writing, it grew longer and longer, so I decided to break it out into a standalone article. 😄

---

The term "full-stack" has been overused, but in the AI era, its meaning is changing.

This article does not discuss full-stack from the "big company recruitment" perspective, but rather from the perspective of an independent developer to reflect on the value of full-stack frameworks.

Full-stack = Full-responsibility, but with lower costs

Full-stack = Full-responsibility

Essentially, it's about reducing costs.

In my view, full-stack development (全栈) has two core advantages: reducing development costs and improving product coherence.

• No need to switch contexts or toggle between different tools, which means lower development costs.
• A better understanding of the entire product stack, leading to better product design and implementation.

In the past, developing a SaaS product individually required mastering an entire Java + React + deployment stack. Today, it might only take Next.js + AI to get started.

With the constant emergence of various open-source frameworks and technologies, it’s often joked that programmers are always revolutionizing themselves. 😄

However, looking at it from another perspective, this is actually the perfect era for indie developers. The continuous reduction in development costs means individuals can accomplish more and create their own products at a relatively low cost. It's both a challenge and an opportunity.

Conflicts and Transitions in the AI Era

When I first started working on DjangoStarter, the concept of "full-stack (全栈)" wasn't very prevalent at the time.

The traditional full-stack approach involved one person handling both frontend and backend development. While it still typically involved a separation of frontend and backend, one person would be doing the work of two. The essence was still a "layered + division of labor" mindset.

Now, in the AI era, the competition isn't about technical superiority or how many languages one has mastered. Whoever can better leverage AI will achieve higher efficiency.

Therefore, in the current full-stack approach, integration (一体性) is more crucial. It reduces layers, making it easier for AI's limited context length to understand the code, and also, to some extent, eases the developer's own understanding. This is why full-stack frameworks like Next.js are becoming increasingly popular, and the experience of using AI with such frameworks is excellent.

Full-Stack in the AI Era: Integration is more important because:

1. AI's context is limited, and an integrated framework helps AI better "understand" the code.
2. Developers themselves experience less cognitive load (心智负担), reducing the cost of switching between "the frontend toolchain" and "the backend ORM."

PS: Caveat: foundational knowledge is still very important. AI provides far greater enhancement to experts than to beginners. If beginners haven't mastered the basics, they won't even understand the code generated by AI, let alone be able to build a qualified product.

Route Dispute

DjangoStarter previously didn't follow the full-stack framework approach; it was actually more backend-focused. However, recently, I've been using it directly for full-stack development in many projects. It has a complete user system, and with Tailwind CSS + Alpine.js + HTMX + Django template rendering, the pages can look quite polished. Plus, it avoids heavy dependencies like node_modules and webpack.

I've actually discussed this before, and you can check out these related articles: Back to Basics! Developing Interactive Web Applications with Alpine.js, Abandon node_modules and webpack!

That said, this approach isn't without its drawbacks.

The biggest issue is the ecosystem. Using Alpine.js for simple interactions is fine.

But once things get a bit more complex—for example, I once needed a tree component—it becomes difficult. There aren't ready-made solutions, and you have to write it yourself. For reference: Video Middleware Solution: Organizational Tree Component + Multi-Stream Video Live Interface Development.

Fortunately, with AI now, this shortcoming is greatly compensated for. You can have AI write any missing components, though stability and quality can't be guaranteed.

For simple pages, it's still no problem. This is actually why I've turned to Next.js (the ecosystem is more complete, and combined with AI, complex pages can be built in a short time).

PS: Of course, that's for later. I'll write articles about Next.js full-stack development in the future.

Opportunities and Challenges

Opportunities:

• Individuals can now accomplish more than ever before;
• AI has reduced complexity and the learning curve, enabling independent developers to quickly experiment and iterate.

Challenges:

• Ecosystem fragmentation: Django? Next.js? Remix? SvelteKit? Or Bun/Edge?
• AI dependency for code stability and long-term maintenance: Today, AI writes you a tree component, but will you still recognize it three months later?
• The trap of mental cost: The eternal struggle between choosing lightweight frameworks vs. large ecosystem frameworks.

Summary

In the AI era, the key phrases for independent developers using full-stack frameworks are "cohesion + AI-friendly".

I will write a follow-up article titled "Next.js Full-Stack Development: My Frontend Tech Stack Panorama (2025 Edition)" as an extension of this piece.