There’s an old saying in the tech world: when Elon Musk was asked about the secret to success, he replied, 'The first 90% of the work takes 10% of the time, and the last 10% of the work takes 90% of the time.' In the age of artificial intelligence, this joke takes on a frightening accuracy.
When the future arrives too quickly
Imagine yourself as the founder of a startup with an excellent idea — an application for personalized educational courses that selects learning materials based on user progress and interests. Previously, creating a prototype required a team of developers and $100,000. And today? You type in a few prompts in a neural network, wait 30 seconds, and there appears an application that seems ready for launch.
Technological tools powered by artificial intelligence have turned what was once the domain of technical experts into a playground for anyone with an idea. As a startup founder with a clear vision of the future product but no programming skills, you gain unexpected freedom of action. No more issues with technical limitations. No more need to search for the perfect developer who can understand your vision. The barrier that prevented countless ideas from ever seeing the light of day is not just lowered — it has vanished.
The truth hidden behind the demonstration
But behind every technological revolution lies an uncomfortable truth. For #AI tools in application development — this is the '80/20' problem. What appears to be a finished product is actually just the beginning of the journey.
At the beginning of your work, you watch in amazement as artificial intelligence works wonders. But soon the magic fades. You begin to realize that you are spending hours refining queries with increasingly specific phrasings, yet the results still do not meet expectations. The illusion of 'programming through dialogue' shatters when you understand that the only way to fix the problem is to dive into code that resembles hieroglyphs.
The first impressive demonstration creates the illusion that 80% of the work is already done, but in reality, AI has only completed 20% of what is required to turn the application into a viable business. The remaining part — creating real value for the user and ensuring stable product performance — is still ahead:
A user interface that aligns with your concept and adapts to user feedback
Logic that goes beyond basic functionality — for example, authentication systems or approval processes
Data management for real volumes, not just test cases
Reliable protection ensuring the safety of users and the business
It's not just about adding features and changing colors. We are talking about the transition from an application that beautifully showcases capabilities to an application that works in the real world.
Alarm signals: you are stuck at 80%
The euphoria of the first demonstration often masks upcoming challenges. You may not realize that you have encountered an 80% problem until you spend significant time trying to overcome it.
You will realize you are stuck when you see that your application still looks like a typical AI-generated product or seems correct but does not perform all the necessary functions. You spend an entire day trying to add a simple dropdown menu that should have taken minutes. You frantically switch between different AI tools hoping that one of them will finally understand your request.
The increase in the number of users becomes a source of anxiety rather than joy, as you are unsure whether your application can handle the real load. User data protection? Nobody cared about that. And those $20 for the neural network tokens that you started with? You've already spent another $500 and still can't get the payment processing function to work properly. When something breaks, the only way out is to hire a developer, meaning you end up doing exactly what you were trying to avoid.
In short: you are hitting the ceiling of the platform's capabilities, while your business demands much more.
The real price of the 80% problem
The 80% problem is not just a technical complexity. It can doom your business even before it takes off.
When progress stops, you lose the most valuable resources of a developer: time and development momentum. What started as a 'free start' turns into an 'expensive finish' when you realize that overcoming the platform's limitations requires hiring specialists.
The saddest part is that you miss the opportunity to realize the original idea. Speed without control leads to compromises that leave only a pale shadow of your vision.
A rethink of the development approach with AI
The solution is not to abandon development with artificial intelligence — far from it. The solution is to understand that impressive demonstrations are the beginning of the journey, not its end.
The remaining 80% of the work may vary for each project, but typically include:
Complex interaction scenarios: not just basic forms, but multi-step processes with conditional logic
Integration with necessary services: connecting precisely those systems that your business needs
Flexible data models: capable of evolving along with business requirements
Performance optimization: ensuring fast application performance as the number of users grows
Compliance: implementing GDPR, SOC 2, and other standards
It is clear that artificial intelligence should enhance your capabilities, not limit them. The future belongs to tools that view AI as a partner, not as a black box or a magic lamp with a genie. Environments where people interact with the results of AI's work, rather than simply accepting whatever it outputs.
The way out is to choose a solution that will support your vision and business in the long term. Tools like Bubble, OutSystems, Retool, or FlutterFlow combine AI generation capabilities with professional refinement tools, bridging the gap between an impressive prototype and a full-fledged product. This combination of artificial intelligence and visual development is the true future, allowing not only for a quick start but also for a confident finish.
It is interesting to observe how the classic Pareto principle loses its relevance here. Italian economist Vilfredo Pareto formulated the regularity at the beginning of the 20th century: 20% of efforts yield 80% of results. In traditional development, this rule worked flawlessly — the preliminary version showcased the key functions of the final solution.
But in the world of AI development, the Pareto principle doesn't apply: 20% of efforts yield a fair 20% of results (impressive but limited prototype). And to achieve the remaining 80% of the results, you need to invest 80% of the efforts.
Artificial intelligence did not solve the development problem; it merely shifted the pain points. It replaced one bottleneck with another. Instead of asking 'how to start creating an application?', the main question became 'how to finish it?'
In an era where technology evolves at the speed of thought, it is paradoxical that the most important part of the work still requires a human touch. And there is beauty in this — AI has made the beginning of the journey accessible to everyone, but only professionals can cross the finish line.
