How AI is rewriting the rules of work for the specialist

The process of building technology, for the past few decades, was defined by rigid assembly lines. A product manager wrote the specs. A designer created the visuals. A front-end engineer built the interface. And a back-end developer handled the data. Everyone was focused on their task or function within the larger organisation, sticking to their lanes. Erran Berger, the Vice President of Product Engineering at LinkedIn, thinks that type of division of labour is rapidly disappearing, a prediction that could unsettle traditionalists in the software world.

Sitting on the executive team of the world’s largest professional network, Mr. Berger is observing a fundamental shift in how work gets done, not just within LinkedIn’s own walls, but across the 1.3 billion members that make up the platform’s “Economic Graph.” His central thesis is that the future belongs not to the hyper-specialist, but to the individual who can take an idea from concept to launch entirely on their own, aided by a suite of artificial intelligence tools — he calls this breed the “Full Stack Builder.”

When Mr. Berger joined the platform in 2009, it was essentially a digital rolodex for resumes. Now, those behind the platform are performing multi-speciality tasks. Product managers are writing code. Engineers are generating design concepts. As a result, the gap between having an idea and shipping a product is closing fast.

This creates a paradox that Mr. Berger is keen to navigate: if AI can generate code and design interfaces, what happens to the craft? He insists that the “maestro” is still essential. Just because a machine can generate code doesn’t mean it is secure, maintainable, or efficient enough to load quickly in low-bandwidth markets like India. The role of the human shifts from labourer to editor, from creator to curator. The domain expertise remains vital, but the capacity to execute expands dramatically.

This philosophy extends beyond engineering and into the very heart of LinkedIn’s business model: recruiting.

For years, the recruitment industry has been bogged down by what Mr. Berger calls “toil.” Recruiters spend vast majority of their days staring at search bars, filtering lists, and sending generic outreach messages. It is repetitive, low-value work that burns people out. Mr. Berger’s strategy is to hand this entire stack of drudgery over to AI.

His team has rolled out tools that assist recruiters with automated hiring support. Disputing the idea that such automation removes the human element from recruiting, Mr. Berger argues it makes the hiring process more human. By removing the search process, recruiters are freed to showcase their company’s vision, assess cultural fit, and build relationships with potential hires.

In Mr. Berger’s view, judgment and creativity will be the last bastions of human exclusivity. An algorithm can match keywords to a resume, but it cannot determine if a candidate has the grit to survive a pivot or the empathy to lead a team. This exclusivity, if it pans out as Mr. Berger predicts, will transition a recruiter into a talent agent and a brand ambassador.

For this ecosystem to work, the workforce itself must adapt. Mr. Berger noted that the anxiety in the market is palpable. Professionals are confused about which skills matter when the ground is shifting beneath them. The old static profile of a list of universities attended and job titles held is fast becoming insufficient or incomplete.

LinkedIn’s own data suggests that the skills required for jobs are changing by double-digit percentage points annually. In response, the platform is evolving from a resume repository into a dynamic verification system. It is no longer enough to claim you can code; you link to your GitHub repository. It is no longer enough to say you are a designer; you link your portfolio. The platform is betting that in an age of AI-generated noise, proven capability will command a premium.

When asked how a professional survives in this volatile environment, Mr. Berger’s advice is strikingly analog: curiosity. He draws a parallel to the engineers who have survived the industry’s previous seismic shifts when the platform shifted from desktop to web and from on-premise servers to the cloud. The survivors were never the ones who clung to the old ways, but the ones who jumped headfirst into the new paradigm.

Mr. Berger sees the current AI revolution as a tool kit to be mastered, and not a wave to be ridden on. This revolution is specialisation agnostic so whether you are an accountant or a software engineer, it will dynamically change the way work gets done in any organisation.

Published – March 19, 2026 08:01 am IST