Scribbles for my bad memory

AI is changing the IT industry’s entry-level landscape. It reduces demand for juniors trained purely under the traditional apprenticeship model, but it does not eliminate the need for juniors altogether. What it changes is the baseline: new juniors are expected to work fluently with AI rather than work around it.

This shift raises concerns about experience and continuity, especially as senior engineers retire. However, senior retirement itself is not the core risk. The real issue is how judgment, taste, and practical knowledge are formed and transferred.

The traditional apprenticeship model still has real value. Engineers who have built systems end to end, debugged production failures, and lived with the consequences of technical decisions develop a sense of “better” that cannot be learned from prompts or outputs alone. This taste is shaped by cost, failure, and trade-offs. AI can amplify such judgment, but it cannot create it from nothing.

At the same time, the old model does not remain unchanged. AI compresses apprenticeship. It shortens feedback loops, accelerates learning, and reduces time spent on mechanical tasks. Juniors who combine hands-on experience with effective use of AI can reach competence faster than before.

The transition is painful, particularly for entry-level hiring and for professionals who fail to adapt their working model. That pain is real but temporary. The industry is not losing juniors; it is producing a different kind of junior. The durable future lies in apprenticeship reshaped by AI, not replaced by it.

This article is co-authored with ChatGPT.