Not long ago, the idea of being a “generalist” in the workplace had a mixed reputation. The stereotype was that of the “jack of all trades” who could dabble in many disciplines but was not a “master of any.” And for years, that was more or less true.
Most people simply did not have access to the expertise needed to do a highly cross-functional job. If you needed a new graphic, you waited for a designer. If you needed to change a contract, you expected what was legal. In smaller organizations and startups, this waiting game was usually replaced by inaction or improvisation, often with questionable results.
AI is changing this faster than any technological change I’ve seen. It enables people to succeed at tasks beyond their usual area of expertise.
found anthropic that AI is “enabling engineers to be more well-rounded in their work,” meaning they can make competent decisions across a much broader range of interconnected technologies. A direct consequence of this is that tasks are now being carried out that would have been left aside due to lack of time or experience (27% of work assisted by AI according to the Anthropic study). This change closely reflects the effects of the past. revolutionary technologies. The invention of the automobile or the computer did not give us a great deal of free time; mainly it led us to start doing jobs that we couldn’t do before.
With AI as a guide, now anyone can expand their skills and increase their experience to achieve 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 advances in AI have been incredible, and if the year 2025 has not fully fulfilled its promise of bringing AI Agents for the WorkforceThere is no reason to doubt that he is on the right track. But for now, it’s not perfect. If making mistakes is human, trusting AI not to make mistakes is foolish.
One of the biggest challenges of working with AI is identifying hallucinations. I suppose the term was coined not as a cute way to refer to factual errors, but as a fairly apt way to describe the conviction that the AI exhibits in its erroneous answers. We humans have a clear bias toward confident people, which probably explains the number of smart people burned after taking ChatGPT at face value.
And if experts can be fooled by overconfident AI, how can generalists hope to harness the power of AI without making the same mistake?
Citizen railings give way to environmental freedom
It is tempting to compare the current situation. AI vibration coding wave to the emergence of low-code or no-code tools. No-code tools gave users the freedom to create custom software tailored to their needs. However, the comparison is not entirely true. The so-called “citizen developers” could only operate within the limits allowed by the tool. These strict restrictions were limiting, but they had the benefit of saving the users from themselves, preventing anything catastrophic.
AI removes those limits almost completely, and with great freedom comes responsibilities that most people are not prepared for.
The first stage of “vibrational freedom” is one of unbridled optimism encouraged by sycophantic AI. “You are absolutely right!” 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: something is not quite right. You start to doubt the accuracy of the work: you look over it and then wonder if it wouldn’t have been faster to do it yourself in the first place.
Then comes negotiation and acceptance. You argue with the AI, they take you down confusing paths, but little by little you begin to develop an understanding: a mental model of the AI’s mind. You learn to confidently recognize wrong, you learn to reject and verify, you learn to trust and verify.
The generalist becomes the layer of trust.
This is a skill that can be learned and can only be learned on the job, through regular practice. This does not require deep specialization, but it does require awareness. Curiosity becomes essential. The same goes for the willingness to learn quickly, think critically, spot inconsistencies, and rely on judgment instead. Treat 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 detect when something is wrong and defer to a true specialist when the stakes are high.
The generalist becomes the layer of human trust placed between the AI output and the organization’s standards. They decide what happens and what gets a second opinion.
That said, this only works if the generalist passes a minimum level of fluency. There is a big difference between “broadly informed” and “confidently unaware.” AI makes that gap easier to overlook.
Impact on teams and hiring
It is clear that specialists will not be replaced by AI anytime soon. Your work remains essential. It will evolve to become more strategic.
What AI changes is everything around the edges. Roles that seemed important but were difficult to fill, tasks that remained in limbo because no experts were available, delays created by waiting for highly qualified people to review simple jobs. Now, a generalist can go much further on his or her own, and specialists can focus on the most difficult problems.
We are already starting to see an impact on the hiring landscape. Companies are looking to hire people who are comfortable navigating AI. People who adopt it and use it to undertake projects outside their comfort zone.
Performance expectations will also change. Many leaders are already looking less at productivity alone and more at how effectively someone is using AI. We see the use of tokens not as a measure of cost, but as an indicator of AI adoption and, perhaps optimistically, as an indicator of productivity.
Make work vibe viable
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Use AI to improve work, not improvise it: You’ll burn yourself out letting the AI loose. Requires guidance and supervision.
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Learn when to trust and when to verify: Develop an understanding of the AI mind so you can exercise good judgment on the work produced. When in doubt or when the stakes are high, turn to the specialists.
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Set cClear organizational standards: AI thrives on context and also on humans. Invest in documenting processes, procedures and best practices.
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Keep humans informed: AI should not eliminate oversight. It should make supervision easier.
Without these factors, AI work remains in the “environment” stage. With them, it becomes something the company can truly rely on.
The return of the generalist
The emerging AI-powered generalist is defined by curiosity, adaptability, and the ability to evaluate the work that AI produces. They can span multiple roles, not because they are experts in each, but because AI gives them access to specialized-level expertise. Most importantly, this new generation of generalists knows when and how to apply their human judgment and critical thinking. That is the real determining factor in turning vibes into something reliable, sustainable and viable in the long term.
Cedric Savarese is founder and CEO of FormAssembly.
