Senior devs often tell me they’re worried juniors won’t learn what good looks like. Juniors tell me they’re learning much faster with AI helping them stumble along the way.
Both are right. The question is which effect dominates.
Learning rate as competitive advantage
Greg Ceccarelli nailed it: the most dangerous person in any room isn’t the expert with twenty years of experience — it’s the person with solid experience and the ability to master new domains at an accelerated rate. He calls it “intellectual metabolism” — the speed at which you absorb new patterns and abandon outdated assumptions.
Fast learners ship working solutions while experienced people explain why it can’t be done. Experience without deliberate practice and feedback produces minimal improvement.
From CI/CD to Continuous Learning
We’ve had Continuous Integration and Continuous Delivery for years. The next shift is Continuous Learning — for both individuals and organizations. When AI accelerates the doing, the differentiator becomes how fast you learn from what you’ve done.
Knowledge management becomes critical as automation increases. If the AI does the coding, what you know about why and when matters more than how.
The junior/senior tension
Some perspectives from the conversation:
- Juniors need basic coding skills plus senior-level systems thinking — AI lets them skip 3-4 years of syntax mastery and get to the interesting problems faster
- “Hard == learning” isn’t necessarily true — Terrence Tao used ChatGPT to learn Lean programming. Easy learning is still learning, it just requires pedagogical awareness
- Experience matters most when it’s been actively refined through feedback, not just accumulated through repetition
The pattern: AI doesn’t eliminate the need for experience. It compresses the time to get there — if you’re intentional about it.
Originally posted on LinkedIn