A lot of people starting out right now are anxious that AI will erase the bottom rung of the ladder — the entry-level jobs where you used to learn by doing the small, repetitive work. I understand the worry, but I think it misreads the change. My name is Howard Davner, I’ve spent 25 years in finance and capital markets and now build companies, and the more I watch AI move through real organizations, the more convinced I am that it doesn’t remove the first rung so much as move it.
The grunt work is going, the judgment is staying
For decades, a first job meant absorbing a lot of mechanical tasks: formatting the deck, pulling the numbers, drafting the first pass. AI now does much of that faster than any junior person can. What it cannot do is decide which analysis matters, notice when an output is subtly wrong, or take responsibility for a recommendation. That work — judgment, taste, ownership — used to be reserved for people with a few years of experience. AI is pushing it down to day one. That’s harder, but it’s also more interesting, and it rewards people who think rather than people who merely execute.
You now have to show the work
When the routine output is commoditized, the way you stand out is by demonstrating that you can direct the tools and check them. That means having real projects you can point to — things you actually built, with an honest account of the choices you made and the mistakes you fixed. This is exactly why I founded Provieo: to help people build genuine, job-tailored projects so they can prove their ability instead of just claiming it. In an AI world, a portfolio of real work is worth far more than a list of tasks you were assigned.
Curiosity compounds faster than credentials
The people I’d bet on early in their careers today are the ones who treat AI as a way to learn faster, not a way to avoid learning. They use it to try things they couldn’t have attempted alone — a working prototype, a financial model, a piece of analysis outside their formal training — and they come out the other side understanding more, not less. The trap is using these tools to skip the understanding entirely. If you let the model do the thinking, you never build the judgment that makes you valuable when the answer isn’t obvious.
My advice, plainly
If you’re early in your career, don’t compete with AI on speed or volume — you’ll lose. Compete on judgment, reliability, and the ability to own an outcome end to end. Build things. Keep the evidence. Get comfortable being the person who says “this output looks right, but here’s where it’s wrong.” The workers who thrive in the next decade won’t be the ones who resisted these tools or the ones who hid behind them. They’ll be the ones who used them to become more capable, and who can show it. That’s the future I’m building toward at Provieo, and it’s a genuinely optimistic one.
Learn more: provieo.com
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