Every Job Is an AI Job — But Senior Professionals Need a Different Toolkit
The current conversation about AI and careers has a center of gravity, and right now it sits with Clara Shih. The former Meta and Salesforce AI executive recently launched the New Work Foundation, a nonprofit aimed at preparing Gen Z for what she describes as a workplace dominated by AI agents. The Fortune profile that introduced the foundation has been making the rounds, and a few of its threads are worth pulling on — especially if you're not Gen Z, and you've been quietly wondering what any of this has to do with you.
What the New Work Foundation gets right
Shih's central claim — "every job is an AI job now" — is hard to argue with, and the data is starting to back it up. A recent Writer survey cited in the same Fortune profile found that employees actively using AI in their daily work are more likely to receive promotions and raises than those who don't. Whatever you think about specific tools, the broader trend isn't speculative anymore. Treat that as category validation, full stop.
The foundation itself is doing the right work for the audience it's built for. Entry-level openings have collapsed. Recent graduates — including, per the Fortune piece, Ivy League ones — are running into the worst conditions for first jobs in nearly four decades. Tools like JobClaw and Field Report exist because that problem deserves real solutions. None of that is in dispute.
But the senior professional has a different problem
For the audience reading this — the 40-something senior knowledge worker, the consulting partner-track candidate, the bank VP, the program director with twenty years of delivery behind them — most of the public conversation isn't actually about you. The New Work Foundation is targeted explicitly at Gen Z. The tools, the framing, the urgency are all calibrated to someone trying to find their first role. That's a real problem, and it deserves the attention it's getting. It just isn't yours.
Your problem is different, and it's quieter.
You haven't lost a job. You haven't necessarily even decided to look for one. But somewhere in the back of your head, you know that if a recruiter called Friday, or if a reorg landed Monday, you'd be opening up old performance reviews and trying to reconstruct what you actually delivered three years ago. The metrics are scattered. The wins are half-remembered. The LinkedIn profile is two roles out of date.
That's the gap. And it doesn't go away by getting better at AI agents. It goes away by having a record AI can actually work with.
There's a line in Shih's recent interviews I keep returning to. Talking about the people who object to AI on principle, she said the skeptics are exactly the people she wants involved in building these systems. The framing was about Gen Z, but I'd extend it: the senior professional who has watched five technology cycles arrive with revolutionary promises and leave with mixed results is exactly the person whose judgment AI tools should be designed around. Not because they're wrong about the hype — because they're usually right about which 10% of it actually compounds.
Records, not agents
Most of the AI-careers conversation right now is dominated by the agent frame. Tools that do things for you. JobClaw matches you to roles. Drafting agents write your applications. Recruiting agents screen your candidates. The promise is offload, automation, speed — and on its own merits, that's all useful.
But the question a senior professional should actually be asking is upstream of all of that. Before you can offload anything, you need a clean, organized, retrievable record of what you've actually done. Not a resume. Not a LinkedIn summary. The underlying evidence — projects, outcomes, metrics, contributions — captured at the time, structured for retrieval, kept current the way any other professional asset is kept current.
Most senior professionals don't have that. They have fragments, scattered across email threads, old file shares, OneNote pages, and half-finished documents from the last time they updated their resume under deadline pressure. The downstream consequence is what I wrote about a couple of weeks ago — a resume that gets ranked invisibly inside an ATS, not because the experience is wrong but because the underlying record was a mess. The upstream cause is what this post is about. And it's the part almost no one is telling, because it's less photogenic than an AI agent that finds you a job. But it matters more, especially for the audience who's been doing the work for two decades and has the most to lose by reconstructing it badly under pressure. The agents will keep getting better. The Writer stat will keep going up. None of it helps you if your record of work is a mess.
I built Tenure because I kept running into this problem from the wrong side of it. The premise is simple: before any AI tool can do useful work for your career, you need a record it can actually work with — captured at the time, kept current, structured for retrieval. Tenure is the platform built around that idea. It's live at owntenure.ca. Free trial, no credit card required.
Build the record now, while you don't need it. That's the move.
— Glenn, Founder · Tenure
For the broader founding context, see Introducing Tenure — Something I've Been Building For A While Now.