AI Dependency in Junior Developers: Risks and Strategies for Responsible Use

The integration of artificial intelligence (AI) tools such as GitHub Copilot, Claude, and others has transformed the workflow of junior developers, accelerating code production. However, this growing dependency raises concerns about technical training and the sustainability of the sector.

Increasingly, junior developers are using these tools as substitutes for deep learning, which generates several adverse effects:

• Lack of structural understanding: the code works, but many cannot explain its internal logic or adapt it to complex scenarios.
• Deterioration of critical skills: deep knowledge is replaced by quick solutions, limiting the ability to solve problems without assistance.
• Increased operational risks: AI-generated code often contains errors or vulnerabilities, forcing more time to be spent on fixing rather than creating.

Given this scenario, a key question arises: what strategies can be implemented to ensure responsible and educational use of AI?

• Active learning, not passive: use AI to generate examples, analyze them line by line, and then rewrite them manually.
• Master fundamentals first: prioritize the study of algorithms, data structures, and design patterns before delegating to AI.
• Debugging exercises: solve errors without automatic tools to strengthen logical thinking.

• Guided code reviews: require explanations of AI-generated code during reviews and encourage pair programming sessions where seniors model best practices.
• Comprehensive evaluation: measure not only delivery speed, but also the ability to optimize existing code and document technical decisions.
• Structured training: promote a culture that values deep knowledge. Include modules on “AI applied to development” in onboarding programs, with emphasis on limitations and best practices.
• Technical challenges: create exercise banks that require modifying and contextualizing solutions proposed by AI.
• Strategic mentorship: designate “learning architects” who guide juniors in the responsible use of these tools, aligning educational objectives with productivity.

AI is not a threat in itself, but its improper use can hinder the professional evolution of a generation of developers. It should be assumed as an assistant, not as a substitute for learning. The real challenge for junior developers will be integrating AI without sacrificing the path toward seniority.

Open question: Should companies implement specific policies to regulate AI use in junior teams?