A few months ago, I published my thoughts on what we've learnt form hiring juniors in the world of AI: sherifmansour.medium.com/on-… Last week, Anthropic published a piece on “How employment is changing at Anthropic”: anthropic.com/research/emplo… Firstly, thank you again to the folks at Anthropic for continuing to share what they’re learning with the rest of the world. I found their post incredibly thought provoking and made me challenge some of my assumptions. I felt like one question folks could have from Anthropic’s findings is what does a junior add once the team is already AI native? My answer is that the learning curve keeps resetting. Each new wave of tools and techniques can ask experienced people to unlearn something; newcomers get to start there. In my time spent working in tech (old man here 🤣), unlearning has been one of the hardest things I’ve seen a workforce have to do - especially when the old ways made people successful. As an example, an experienced developer might ask how AI fits their workflow. Someone learning today might ask what workflow makes sense now that AI can write code. I’m not suggesting that means younger people always adapt better (although, I think that could be generally true). But their contribution doesn’t disappear once everyone has adopted today’s tools. Tomorrow’s approaches can create that opportunity again - I think of it more as a never-ending cycle. I think the challenge that will always exist is that newcomers help the team discover different ways of working, while experienced colleagues help them develop judgment and independence. That takes deliberate investment. So I’d still resist a blanket decision to stop hiring juniors. Instead, look at what the situation you’re in. Today, the vast majority of the world is unlearning how they used to work, the argument that once we’re all AI native you won’t need juniors doesn’t check for me - because tomorrow’s approaches for what “AI native” means will continually reset that assumption.