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AI Won’t Replace Juniors, It Will Redefine How They Learn

AWS CEO Matt Garman says using AI to replace junior staff is: "One of the dumbest things I've ever heard." This 👆 Many seniors assume juniors will learn the same way they did: by relying on observing masters at work, picking up techniques over time, and slowly building their own skills. That’s projection bias: believing others must follow the same path you once took. But AI changes the dynamic. Juniors won’t have to rely on observing senior engineers. They’ll ask AI. They’ll break problems down, test solutions, and learn by doing, with a faster feedback loop than ever before. Seniors remain just as important, but less as artisans to be copied and more as coaches who help juniors ask better questions, think critically, and navigate complexity. Yes, there may be a gap while juniors adapt to this new way of learning and growth. But that gap isn’t unique to them, it’s the same challenge seniors face too. AI won’t make juniors obsolete, it will make them stronger.
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The Title Trap: How We Misjudge Skill at Work

  The title trap. A bias that creeps in at work, is judging skill by title. Looking up: “They’re a principal / manager / senior leader, so they must be doing what they’re doing, much better than I could ever do.” Looking down: “They’re junior, so I must be better at everything.” This bias isn’t constant. It spikes after a win, praise, or promotion. It dips after a mistake or criticism. Try to self-correct when you notice it: If your confidence is low, remember that manager or senior leader you once had who was clearly immature about certain things. If you’re feeling overly confident, remember that junior who kept surprising and humbling you. And a quick test: Notice one junior who’s better than you at something → tell them. Notice one senior you admire, who’s weaker than you in a certain skill → that’s a valuable benchmark for you. Titles are signals, not proof. Being able to see past titles is a meta-skill that improves every other aspect of self-awareness.
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AI Needs Pioneers, Settlers and Town Planners

Have you considered that in the heated AI adoption debate, sceptics and optimists might both be right, just playing different roles as pioneers, settlers and town planners? Pioneers: Maximum optimism, minimum scepticism. They test everything, break things, find what's possible. Settlers: Balanced scepticism. They watch pioneers fail, extract what works, create products. Town planners: Peak scepticism. They demand proven production-ready solutions, industrialise them, make AI bulletproof and scalable. Pioneers need optimism to explore. Settlers need doubt to productise. Town planners need scepticism to industrialise. We're so busy picking sides, shaming the "AI resistant" or mocking the "AI evangelists", that we miss the point: your organisation needs all three roles.
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AI Hype vs Panic: Losing the Middle Ground

Most views on AI these days fall into camps; either overly hyped or needlessly panicked. And honestly, I think algorithmic filter bubbles that the social media apps have, are fuelling this. They seem to feed on people’s fears; either pushing “it’s all hype, ignore it all” or “we’re falling behind, do something now or lose it all” narratives into our feeds. This polarisation makes us overcorrect and focus on convincing the other camp, rather than seeking the kinds of conversations that might lead to a more balanced perspective. We’re losing the middle ground, and with it, the chance to think clearly together.
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A Better Way to Give Interview Feedback

Quick tip on giving interview feedback (especially when rejecting): Don’t write like your interview process is perfect or your interviewers are all-knowing. They might be smart, but they’re also human, often context switching from their work under pressure and working with limited signals. Avoid making bold statements about someone’s strengths or weaknesses. Instead, add a context setting line like this: "Our feedback is based solely on the limited observation window provided by the interview process, which may not capture the candidate’s full capabilities. However, we have to make decisions based on the evidence available to us during that time." Those few sentences can make a big difference to the candidate’s experience.
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