We always hear such phrases as «We do not need developers anymore» or «AI will make you a website overnight» with the growth of generative AI tools. Even though AI is a powerful assistant, we cannot ensure it is effective on its own. Here is why.
Useful AI
AI undoubtedly helps with code generation, bug detection, auto-correction, code completion, and code testing. There are a bunch of tools. Therefore, people believe in their productivity.
Real Case :
Amazon AI assistant for a recruitment team. The HR department receives enormous assistance. AI sorts out candidates who fit the Amazon team based on the 10-year database.
Why myth?
It was trained using information from 10 years ago. The candidates were males. Thus, female candidates were rejected. Because AI declined resumes that included the context «women’s» or anything referencing it. Developers have to babysit AI tools. AI programming still lacks context, intuition and domain expertise.
AI – a replacement tool
AI is a universal technology. It might be a good replacement for programmers. Companies implement AI throughout different industries. There are real-world examples from IT.
Real Case :
1) A pre-product AI engineering called “Devin” by Cognition Labs. It can plan, debug and test autonomously.
2) Another example is Morgan Stanley’s DevGen AI, which modernizes COBOL code. It has already reviewed 9 million lines of code and saved 280,000 developer hours. It replaces routine coding and understands functions.
3) Also, one regular case. The software developer lost his job due to the AI implemented by his employer.
Why myth?
1) Devin is limited to controlled tasks. It has high computing costs. It needs supervision and also lacks security.
2) Dev Gen AI fails to understand business logic at full capacity behind these lines of code. The senior engineer has to review the output. Besides, it replaces jobs for those who did code clean-up before it.
3) We can see that big companies need optimization. It is more reasonable to replace 10 developers with a single AI tool. That leads to negative results. It lowers the value of traditional coding. AI puts down hundreds of developers.
AI assistant
It is an excellent idea. AI is like a junior pair. It never gets tired. It offers basic solutions and autocomplete functions. It offers alternative approaches and boosts repetitive tasks when guided by an experienced developer. Overall, the idea of cyborgs sounds real and achievable.
Real Case:
GitHub Copilot is an AI pair programmer that helps developers. It auto-suggests lines of code and functions. As well as full files based on the context. Big companies like Airbnb and Spotify use GitHub Copilot internally for their teams.
Why myth?
AI cannot determine the optimal scalability concerns of a business. AI often approves insecure practices that responsible developers don’t approve. AI often introduces bugs and errors. In essence, AI assistants cannot think about what to build. It cannot implement critical thinking and architectural decision-making.
AI – an entry tool in IT
AI has lowered the barrier to entry for beginners. It helps to overcome difficulties for those who just started. Beginners do not require deep code knowledge. It plays a role in learning this industry.
Real Case :
10-17-year-old learners use Open AI Codex to solve Python problems. For example, AI single prompt or AI hybrid programming. Replit’s agent lowers the barrier for non-programmers or beginners. And helps them to learn new. It turns natural language into apps and websites.
Why myth?
While AI is good for prototyping and learning, it can be dangerous in production. Beginners might create applications that “work”. But they are fragile, insecure, and unscalable. Without understanding fundamentals like data structures. They risk building systems that collapse under real-world use.
Conclusion:
If you believe that AI outdates developers, you can end up paying in the long-run. For example, repairs, security breaches or complete rewrites. Smart clients hire smart developers.
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