The Job Market
As of August 2025, over 132,000 tech workers have been laid off so far this year according to data from TrueUp. For junior developers, the situation is especially challenging. According to data sourced from Indeed, software developer job openings in the U.S. have decreased by 35% since the pre-covid level (Jan 2020), more than any other industry. Global trends for software devs show a fall across most regions. However, Australia stands out as the only country with an increase in demand for developers compared to 2020.
Software Development Job Postings on Indeed by Country
In this tough job market, many junior developers resort to "vibe coding". This is a false shortcut of building applications using AI without actually learning to code, and the AI solution is making the problem worse. It's creating a generation of "prompt-engineers" who lack the basic understanding and skills needed to survive in an increasingly competitive industry.
A False Promise
In practice, vibe coding means using AI models to build your entire application without writing a single line of code yourself. When something breaks, you don't debug it. You ask the AI to fix it for you.
The appeal is obvious, especially for newcomers facing a brutal job market. Why spend years learning to program when you can just describe what you want in plain English? AI coding sounds amazing: no technical knowledge required, just explain your vision and watch it built. The possibilities are endless, or so they promise.
An Illusion of Productivity
Recent research reveals a shocking truth when it comes to AI programming productivity. A study conducted in 2025 tracked 16 experienced developers from major open-source projects as they completed 246 real-world coding tasks. The results were shocking: developers using AI tools experienced a 19% decrease in productivity compared to working without AI assistance.
Even more concerning, the developers themselves were completely unaware of this slowdown. They estimated that AI had increased their productivity by 20%, while the actual data showed the opposite. The study found that developers spent substantial time reviewing AI-generated code, with only 39% of AI code generations being accepted. Much of the "time savings" from AI was offset by the need to prompt, wait for responses, review output, and often discard flawed code.
This research challenges the belief that AI tools are boosting developer productivity. While helpful with certain types of tasks, the study suggests that for experienced developers working on mature, complex codebases, these tools may actually be counterproductive. This creates a fundamental problem: to use AI effectively for programming, you need to understand the domain well enough to make precise requests and evaluate the output. But if you already have that level of understanding, you might not need the AI in the first place.
Skills Degradation in Junior Devs
For junior developers, vibe coding is a career death trap. Industry experts consistently warn that it's "the worst thing you can do for your career right now". The approach creates a false sense of productivity and learning, and prevents the development of crucial skills.
The fundamental problem is that vibe coding creates what experts call "pseudo-developers". These are people who can generate code but can't understand, debug, or maintain it. When AI-generated code breaks, these developers are helpless. As one notes: "The first to get replaced will be the vibe coders. The ones who thrive will be those who know how to guide the tools, not just follow them."
The skills degradation happens across multiple dimensions:
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No Debugging Abilities: When AI-generated code fails, vibe coders can't identify or fix the problems. They become dependent on AI for every technical challenge, never developing the problem-solving skills that separate real developers from code generators.
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No Architecture Understanding: They can't make informed technical decisions about system design, performance optimization, or scalability because they don't understand the underlying principles.
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No Code Review Skills: They can't assess code quality, security vulnerabilities, or maintainability because they've never learned to read code properly.
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No Fundamental Knowledge: They miss the foundation that allows developers to adapt to new technologies, understand trade-offs, and make architectural decisions.
The Technical Debt Problem
Even when vibe-coded applications work initially, they create massive technical debt that becomes unmanageable over time. AI-generated code lacks structure, maintainability, and efficiency. Debugging turns into a time sink, where you spend more time fixing than you saved.
Experienced engineers report reviewing significantly more code than in previous years, but struggling to maintain quality standards when so much of it is AI-generated. The problems compound because:
- Poor Code Quality: AI generates poorly structured code that's difficult to maintain
- Missing Edge Cases: AI often ignores error handling and unusual scenarios
- Performance Issues: Generated code frequently has bottlenecks and inefficiencies
- No Documentation: AI-generated code typically lacks proper documentation
- Security Vulnerabilities: AI doesn't think adversarially like human attackers
The Fundamental Paradox
Professional developers have identified a cruel irony: vibe coding works best for those who don't need it. Experienced developers can guide AI tools effectively and catch their mistakes because they already understand the domain deeply. This creates a devastating catch for junior developers:
- They need experience to use AI tools effectively
- But vibe coding prevents them from gaining that experience
- They end up trapped in a cycle of dependency without real skills
The most effective AI users are those who could solve the problems manually but use AI to work faster. The least effective users are those who rely on AI because they don't know how to solve the problems themselves.
AI as a Tool, Not a Crutch
This doesn't mean AI has no place in software development. Developers can successfully use AI as a productivity tool by:
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Treating AI as a Co-pilot, Not Autopilot: Understanding that AI assists but doesn't replace human judgment. "Treat it like a co-pilot, not an autopilot. For example, if you understand CSS, you can describe the design and see how it implements it, then look at the code and say 'Yeah, it makes sense.'"
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Maintaining Code Understanding: Reading and reviewing all AI-generated code before using it in production. Never shipping code you can't explain or debug.
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Building Fundamental Skills: Using AI to enhance existing knowledge rather than replace the need to learn programming concepts.
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Practicing Without AI: Regularly coding without AI assistance to maintain and develop core skills. Set aside time for "AI-free" development sessions.
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Explaining Generated Code: For every piece of AI-generated code, write comments explaining what it does and why. If you can't explain it, you don't understand it well enough to use it.
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Learning from AI: Study how AI solves problems to understand different approaches, but always verify the logic and learn the underlying principles.
The tech industry is undergoing a fundamental shift. The industry is becoming more selective and prioritizing developers who can actually solve problems, not just generate code. Recent layoffs have disproportionately affected junior positions and support roles, and in this environment, vibe coding makes you less valuable, not more.
Final Thoughts
Using AI involves trading knowledge for speed. Sometimes this trade-off makes sense, but it's important to remember that even elite athletes continue practicing basic fundamentals. You can't skip the foundation and expect to build a sustainable career.
The vibe coding trend may be popular, but it can't give you a strong career. In a field where security, reliability, and maintainability matter more than ever, there are no shortcuts to understanding the code you deploy to production.
For junior developers serious about their future, the path forward is clear: learn the fundamentals, use AI as a tool to enhance your skills, and build the deep understanding that separates real developers from code generators. The market is already harsh enough. Don't make it worse by sabotaging your own skill development.
The future belongs to developers who can work effectively with AI while maintaining their own competence. These are developers who can debug AI-generated code, explain why certain solutions work, and adapt when AI models change or fail. The industry demands developers who can think critically, debug confidently, and solve real-world problems.