You thought the generalist was dead — in the 'vibe work' era, they're more important than ever

Not long ago, the idea of being a “generalist” in the workplace had a mixed reputation. The stereotype was the “jack of all trades” who could dabble in many disciplines but was a “master of none.” And for years, that was more or less true. Most people simply didn’t have access to the expertise required to do highly cross-functional work. If you needed a new graphic, you waited for a designer. If you needed to change a contract, you waited for legal. In smaller organizations and startups, this waiting game was typically replaced with inaction or improvization — often with questionable results. AI is changing this faster than any technology shift I’ve seen. It’s allowing people to succeed at tasks beyond their normal area of expertise. Anthropic found that AI is “enabling engineers to become more full-stack in their work,” meaning they’re able to make competent decisions across a much wider range of interconnected technologies. A direct consequence of this is tasks that would have been left aside due to lack of time or expertise are now being accomplished (27% of AI-assisted work per Anthropic's study). This shift is closely mirroring the effects of past revolutionary technologies. The invention of the automobile or the computer did not bring us a wealth of leisure time — it mainly led us to start doing work that could not be done before. With AI as a guide, anyone can now expand their skillsets and augment their expertise to accomplish more. This fundamentally changes what people can do, who can do it, how teams operate, and what leaders should expect. Well, not so fast. The AI advances have been incredible, and if 2025 may not have fully delivered its promise of bringing AI agents to the workforce, there’s no reason to doubt it’s well on its way. But for now, it’s not perfect. If to err is human, to trust AI not to err is foolish. One of the biggest challenges of working with AI is identifying hallucinations. The term was coined, I assume, not as a cute way to refer to factual errors, but as quite an apt way of describing the conviction that AI exhibits in its erroneous answers. We humans have a clear bias toward confident people, which probably explains the number of smart people getting burned after taking ChatGPT at face value. And if experts can get fooled by an overconfident AI, how can generalists hope to harness the power of AI without making the same mistake? Citizen guardrails give way to vibe freedom It’s tempting to compare today’s AI vibe coding wave to the rise of low- and no-code tools. No-code tools gave users freedom to build custom software tailored to their needs. However, the comparison doesn’t quite hold. The so-called “citizen developers” could only operate inside the boundaries the tool allowed. These tight constraints were limiting, but they had the benefit of saving the users from themselves — preventing anything catastrophic. AI removes those boundaries almost entirely, and with great freedom comes responsibilities that most people aren’t quite prepared for. The first stage of 'vibe freedom' is one of unbridled optimism encouraged by a sycophantic AI. “You’re absolutely correct!” The dreaded report that would have taken all night looks better than anything you could have done yourself and only took a few minutes. The next stage comes almost by surprise — there’s something that’s not quite right. You start doubting the accuracy of the work — you review and then wonder if it wouldn’t have been quicker to just do it yourself in the first place. Then comes bargaining and acceptance. You argue with the AI, you’re led down confusing paths, but slowly you start developing an understanding — a mental model of the AI mind. You learn to recognize the confidently incorrect, you learn to push back and cross-check, you learn to trust and verify. The generalist becomes the trust layer This is a skill that can be learned, and it can only be learned on the job, through regular practice. This doesn’t require deep specialization, but it does require awareness. Curiosity becomes essential. So does the willingness to learn quickly, think critically, spot inconsistencies, and to rely on judgment rather than treating AI as infallible. That’s the new job of the generalist: Not to be an expert in everything, but to understand the AI mind enough to catch when something is off, and to defer to a true specialist when the stakes are high. The generalist becomes the human trust layer sitting between the AI’s output and the organization’s standards. They decide what passes and what gets a second opinion. That said, this only works if the generalist clears a minimum bar of fluency. There’s a big difference between “broadly informed” and “confidently unaware.” AI makes that gap easier to miss. Impact on teams and hiring Clearly, specialists will not be replaced by AI anytime soon. Their work remains critical. It will evolve to become more strategic. What AI changes is everything around the edges. Roles that felt important but were hard to fill, tasks that sat in limbo because no expert was available, backlogs created by waiting for highly skilled people to review simple work. Now, a generalist can get much farther on their own, and specialists can focus on the hardest problems. We’re already starting to see an impact in the hiring landscape. Companies are looking to bring on individuals who are comfortable navigating AI. People who embrace it and use it to take on projects outside of their comfort zone. Performance expectations will shift too. Many leaders are already looking less at productivity alone, and more at how effectively someone uses AI. We see token usage not as a measure of cost, but as an indicator of AI adoption, and perhaps optimistically, as a proxy for productivity. Making vibe work viable Use AI to enhance work, not to wing it: You will get burned letting AI loose. It requires guidance and oversight. Learn when to trust and when to verify: Build an understanding of the AI mind so you can exercise good judgement on the work produced. When in doubt or when the stakes are high, defer to specialists. Set clear organizational standards: AI thrives on context and humans, too. Invest in documentation of processes, procedures, and best practices. Keep humans in the loop: AI shouldn’t remove oversight. It should make oversight easier. Without these factors, AI work stays in the “vibe” stage. With them, it becomes something the business can actually rely on. Return of the generalist The emerging, AI-empowered generalist is defined by curiosity, adaptability, and the ability to evaluate the work AI produces. They can span multiple functions, not because they’re experts in each one, but because AI gives them access to specialist-level expertise. Most importantly, this new generation of generalists knows when and how to apply their human judgment and critical thinking. That’s the real determining factor for turning vibes into something reliable, sustainable, and viable in the long run.