- Feb 16
- 5 min read
Over the past three years, AI has steadily moved from experimentation to infrastructure, influencing everything from creative workflows to operational decision-making. To understand what this transformation truly looks like from the inside, we spoke with employees across disciplines at Wix. Rather than focusing on tools or predictions, we asked them a simple question: What is actually changing in your day-to-day work and what does that reveal about the future of expertise? The answers tell a more nuanced story than disruption alone. They point to a shift in judgment, imagination, and human responsibility, all unfolding as machines grow more capable.
When language becomes infrastructure
For writers, the rise of large language models has not diminished the importance of human craft, it has clarified it.
“LLMs rely on content, and on writers, to improve and produce quality at scale,” says Ayelet Kessel, AI Master in the UX Guild. “Evaluating output still requires people who understand what good content looks like.”
As automated systems generate more language, the role of writers evolves from execution to influence. Writers increasingly shape the systems themselves – deciding tone, intent, boundaries, and quality thresholds. Writers' skill sets also expand as a result; linguistic precision remains essential, but so does the ability to guide, critique, and refine machine-generated output.
“The question is not whether writers are still relevant,” Ayelet notes. “It’s where we choose to exert influence within these new content systems, and how we continue to grow alongside them.”
Scale ≠ More people
For years, launching a project meant assembling a full cross-functional cast in one room: a frontend engineer, a designer, a backend developer, a product manager, etc. – each person representing a different profession. Progress was largely a function of coordination in this case.
According to Yotam Tron, OD Partner in the People Guild, AI quietly rewrites that model. Today, many projects can move forward with just two or three people. There is usually a creator (it can be a product manager, designer, or UX professional), who defines intent and direction, a builder, typically a software engineer who turns that idea into something real, and sometimes a third person who acts as a mentor or technical expert.
The impact is not just smaller teams, but a fundamentally different pace of work. More projects can run in parallel. Iteration accelerates. As Yotam puts it, “managerial responsibility is no longer proportional to the number of people managed, it grows exponentially with the scale of what small teams can now deliver.”
This shift also exposes a long-standing organizational paradox. Adding people does not increase output linearly – it increases communication. Every new hire brings more coordination, more alignment, and more cognitive load. The intuitive response, adding headcount when teams feel overloaded, doesn’t always accelerate delivery at the pace teams expect
AI changes the equation. Unlike humans, AI agents do not add friction. They don’t require alignment meetings or status updates. Where adding people increases communication overhead, adding AI adds leverage. Capacity grows without complexity growing at the same rate.
Recruiting for skills that don’t yet have names
The impact of AI in the hiring process is extremely visible and pretty complex.
“My role today isn’t just about finding the best talent,” says Dor Noyman, Team Lead in Sourcing. “It’s about defining what the right skill set even looks like.”
As roles blur and technologies evolve, traditional job descriptions struggle to keep up. Candidates are increasingly hybrid: part specialist, part generalist – fluent across various systems and tools. This raises difficult questions organizations are still learning to answer:
How do you identify emerging skills before they have an official title?
How do you assess potential, not just past experience?
“For me, this is where modern recruiting creates real value,” Dor says. “Not just filling roles, but translating deep market shifts into human capability that actually moves the organization forward.”
Design, amplified
For designers, AI represents neither an existential threat nor a radical departure from past technological shifts.
“AI shouldn’t be treated as something designers need to fear,” says Eden Platoni, Graphic Designer on the Design Dev Team. “It’s just another tool in the toolkit, no different in principle from the design software, like Photoshop for example, that came before it.”
Used thoughtfully, AI accelerates exploration. It allows designers to test more directions faster and reach high-quality outcomes with less friction. The real change, Eden argues, is not in what designers do, but where they spend their time.
“AI handles parts of execution. Designers can focus more on judgment, concept, and impact,” she explains. “It doesn’t replace design skills, it amplifies them.”
In this model, taste, decision-making, and clarity of intent become the true differentiators. Speed increases, but responsibility remains human.
Imagination as a core skill
Some of the clearest signals about the future of work come from unexpected places, like in the classroom.
Elinor Sason, Designer in the Wix Tomorrow Team, works closely with children through educational initiatives. What she sees is a fundamental shift in what really matters.
“First and foremost: imagination comes to life,” she explains. “We’re entering a moment where children can not only imagine, but build instantly”
She describes the rise of vibe coding in the classroom as the bridge between creativity and technology, where children can turn ideas into tangible outcomes using natural language.
Shay Levy, Wix Tomorrow Team Lead, sees the same pattern from a broader perspective.
“As the distance between idea and execution collapses,” she explains, “the real differentiator becomes articulation: being able to shape a vague thought into something concrete.”
“That skill,” she adds, “is what turns imagination into impact. Those who can clearly describe what they envision, whether working with AI or people, are the ones who truly move things forward.”
From manual control to smart operations orchestration
AI has also clarified the nature of the operations role. As Rusnė Rimkutė, Site Operations Manager at Wix Vilnius, sees it, the need for operations teams hasn’t disappeared, it has become more visible.
Someone still has to define the process, ask the right questions, and navigate real-world constraints. AI doesn’t make those decisions, it just executes them. The work hasn’t vanished, it has shifted. Instead of heavier manual effort, ops teams focus on designing direction, while AI handles execution. Impact, not effort, becomes the measure of the role.
A human shift Across disciplines, a common pattern emerges. AI accelerates execution while elevating the importance of human judgment. It lowers barriers for creation, while raising the bar for clarity, and responsibility. The real transformation is not technological – it’s human. And us as humans are learning how to build, decide, and imagine, alongside these new intelligent machines.
And if you made it this far, it’s probably worth mentioning: we’re always looking for great people.
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