Seniors Learned in a Pre-AI World That No Longer Exists. Be Careful With Their Advice.
Experience used to be far more portable. A senior could reach back into their own learning curve and hand something useful forward. Not just the tools they'd used, but the shape of how they'd grown. Learn the domain. Build something real. Let your failures teach you. Do your own research. The specific stack was almost beside the point. The sequence was what mattered, and the sequence held.
That portability is what's quietly breaking right now.
The advice being handed down to post-AI beginners often carries the confidence of hard-won wisdom, but it's being applied to a context it wasn't built for. And the mismatch isn't always obvious; which is what makes it slippery. It's not that the old lessons were wrong. It's that they were shaped by a particular kind of friction, and that friction has changed.
Learning used to require pushing through the resistance of not understanding. Syntax, error messages, the slow accumulation of mental models; that struggle wasn't incidental, it was the mechanism. Shortcutting it produces something that looks like progress but isn't.
What we haven't figured out yet is what replaces it.
What does a genuine learning path look like when so much of the surface can be generated instantly? Which fundamentals matter more now, and which ones mattered mostly because the tools were hard? Nobody knows. Not really.
The most honest thing experience can offer right now isn't a roadmap. It's the clarity to say: the path I took no longer exists in quite the same form, and I'm not sure what the new one looks like yet.