It actually is. A year of experience is not equal at different companies.
You could spend years writing very little code and have “years of experience” in a language, and you can also output intense volumes of work and still be within a year.
Of those two people, the one who spent less real time but produced more work, can have the equivalent experience of the person who spent years.
The key is to figure out how much work a person using Claude Code would have been expected to produce in 10 years, then find a way to do that much in a single year. Boom, you just solved the years of experience problem.
You've never seen project managers basically propose the equivalent of getting a baby delivered in 1 month instead of 9 months by adding more people to the project?
But yeah, if the recruiters start asking for "10 years experience with Claude Code", then I guess a tongue-in-cheek answer would be "sure, I did 10 projects in parallel in one year".
Adding more people to a project doesn’t improve throughout - past a certain point. Communication and coordination overhead (between humans) is the limiting factor. This has been well known in the industry for decades.
Additionally, i’d much rather hire someone that worked on a a handful of projects, but actually _wrote_ a lot of the code, maintained the project after shipping it for a couple years, and has stories about what worked and didn’t, and why. Especially a candidate that worked on a “legacy” project. That type of candidate will be much more knowledgeable and able to more effectively steer an AI agent in the best direction. Taking various trade offs into account. It’s all too easy to just ship something and move on in our industry.
Brownie points if they made key architecture decisions and if they worked on a large scale system.
Claude building something for you isn’t “learning” in my opinion. That’s like saying I can study for a math exam by watching a movie about someone solving math problems. Experience doesn’t work like that. You can definitely learn with AI but it’s a slow process, much like learning the old fashioned way.