Even LinkedIn Admits It Can’t Find You a Job

Reactive essay. Source: “The career ladder is fading as AI reshapes work, LinkedIn exec says” — Thibault Spirlet, Business Insider, April 1, 2026.

By Venki Padmanabhan • The Long Game • April 1, 2026

LinkedIn’s chief economic opportunity officer, Aneesh Raman, says the career ladder is dead. What’s replacing it is a climbing wall — careers that move sideways, diagonally, unpredictably. His new book with LinkedIn CEO Ryan Roslansky is called Open to Work: How to Get Ahead in the Age of AI. His advice to workers: figure out what AI can do for you, adapt in real time, and don’t plan ten years ahead.

It’s a good metaphor. Better than he realizes. Because a climbing wall is not a rock face. It’s an engineered environment. Every hold is deliberately placed. Someone designed the routes. Someone bolted the holds to the rock.

And that changes everything about who’s responsible.

Raman’s advice puts the burden entirely on the worker: “No one is going to come knock on your door and say, ‘We’ve figured out what your job is in the AI era.’” He means this as empowerment. I hear it as abandonment. Because here’s the asymmetry his metaphor hides — the worker didn’t choose to automate their tasks. The company did. The capital allocation committee signed off on the vision system that replaced the manual inspection. The VP of operations approved the AI that took over the first draft, the research summary, the financial model. And now someone with a title and a budget needs to answer a question that LinkedIn’s climbing wall conveniently sidesteps: what are you going to do with the human being whose tasks you just automated?

This isn’t just a blue-collar question. AI is consuming the entire junior tier of white-collar work — the tasks that used to be how young professionals learned the craft. The junior analyst didn’t build the DCF model because it was efficient. She built it because building it taught her how to think. When AI takes over the apprenticeship tasks, the climbing wall loses its bottom holds — for every collar.

So who builds the wall? The employer. And why don’t they? Because our accounting systems cannot see the asset they’re being asked to invest in. I call this HVAC — not the system that controls the air in your plant, but the one that measures the people. Hiring Value, Vocational Value, Accreditation Value, Contribution Value. Until you can put Capability Capital on the books, formation will always lose the budget fight to the next piece of automation. The wall won’t get built because the accountants can’t see the climbers.

That’s the argument. Now let me show you what it looks like on the ground.

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I say all of this with genuine respect for Raman. In 2007, my family was living in Stuttgart — I was working for Mercedes-Benz — and CNN was about the only English-language channel we could get. My oldest son, nine years old, watched Raman reporting from the Middle East and announced he wanted to be Aneesh Raman when he grew up. (He became a hematology-oncology fellow instead — its own kind of nonlinear career, made possible by twelve years of structured medical formation. The climbing wall had holds.)

Raman’s own path — CNN war correspondent to unpaid intern on Obama’s 2008 campaign to LinkedIn executive — is proof that nonlinear careers are possible. It is not proof they’re available to everyone. That path required education, network, and the financial cushion to take an unpaid internship during a presidential campaign. His book is called Open to Work. That phrase tells you everything about who the advice is for: people who have profiles, networks, credentials. It is not for the sixty people on my production floor, most of whom have never posted on LinkedIn and never will.

* * *

Picture the advice landing differently.

You are a pipe extrusion operator in Wooster, Ohio. AI hasn’t taken your job — not yet — but it has restructured the control systems you interact with. The HMI panels are smarter. The quality sensors generate data you weren’t trained to read. The preventive maintenance system now flags anomalies using pattern recognition that used to live in your supervisor’s head.

“Figure out what AI can do for you” is not helpful here. It floats above the shop floor like a motivational poster in a break room nobody uses.

And here’s the deeper irony: LinkedIn itself is structurally useless for this worker. A pipe extrusion operator doesn’t have a profile. A welder doesn’t list “can hear a die going bad before any sensor catches it” as a skill endorsement. The entire architecture of “open to work” assumes you live in the knowledge economy. So when LinkedIn’s chief opportunity officer says the climbing wall gives workers “more control over their careers,” you have to ask: which workers?

The formation path I’ve built at my plant looks like this: an operator who used to visually inspect pipe joints learns to interpret the data stream from the vision system that replaced them. They learn to calibrate it, recognize when its algorithms are drifting, troubleshoot the edge cases that confuse the AI. They become the person who makes the automation work — not the person the automation replaced. From executing tasks to understanding systems. From running the machine to reading the data it generates. From labor as a depreciating asset to labor as an appreciating one.

That’s the climbing wall. That’s what building it actually looks like. And it doesn’t happen because someone told the operator to figure it out.

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The same logic applies in white-collar work, and this is where Raman’s framework fails most dangerously. AI isn’t nibbling at the edges of knowledge jobs — it’s consuming the entire junior tier. The first draft. The research summary. The slide deck. The legal brief. These weren’t grunt work. They were the curriculum.

A law fi