𝗔𝗜 𝗜𝘀 𝗕𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗧𝗲𝗰𝗵 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽
AI is changing how we work. It is also destroying the way we train new developers.
In the past, mentorship followed a simple pattern. Juniors did repetitive tasks. Seniors guided them. Juniors broke things. Seniors fixed them. Both parties learned through this cycle.
AI has broken this cycle.
The Problem
AI tools like GitHub Copilot now handle the tasks meant for juniors. This includes debugging and writing boilerplate code.
When a junior uses AI, they skip the most important step of learning: explaining a problem to a human. They get an instant answer without understanding the logic. This creates several risks:
- Juniors lack foundational debugging skills.
- Juniors view seniors as optional rather than essential.
- Seniors face burnout because they manage both their own work and AI-assisted junior work.
- The industry faces a leadership crisis. Seniors lose people management skills, and juniors rise with weak technical foundations.
The Risk of Over-reliance
AI can fail. It often misinterprets old code or complex dependencies. If a junior relies solely on AI, they will panic when the tool fails. They lack the skills to fix the mess.
How to Fix the Mentorship Loop
You must force human interaction back into the workflow. Here are three ways to do it:
Structured Pair Programming: Force juniors to explain their thought process to a senior before they touch AI. This is the most effective way to rebuild the learning loop.
Task Segmentation: Designate high-level decisions, like architecture, as human-only tasks. This ensures juniors see the value of human expertise.
Reverse Mentorship: Have juniors document when AI fails. They should present these failures to seniors. This teaches juniors to spot AI errors and builds trust in human judgment.
If you do not fix this pipeline, the tech industry will become brittle. Innovation will stall because no one understands how the code actually works.
Fix the loop before the system breaks.
Optional learning community: https://t.me/GyaanSetuAi