top of page
Search

The xEngineer: A New Blueprint for Software Engineering in the AI Era


The xEngineer - Wix Engineering
Aviran Mordo, Yaniv Event Haim, Asaf Yonay


For decades, the role of the software engineer seemed straightforward: identify a problem and solve it by writing code. But the rise of powerful AI models is beginning to reshape that definition. 


With systems like Claude Code, Codex, Cursor and other advanced coding assistants, something important has become clear across the industry: writing code itself is gradually becoming a commodity.


This does not mean software engineering is becoming less valuable. Quite the opposite. What is changing is where the real value lies. Engineers are moving from being primarily code producers - to becoming problem definers, system designers, and orchestrators of intelligent tools.


This shift is at the heart of a new concept emerging at Wix - the "xEngineer."


Last month, we hosted an open discussion on Twitter-X (@WixEng) with Wix’s leadership: Yaniv Even Haim (Wix’s CTO), Aviran Mordo (VP Engineering), and Asaf Yonay (GM - AI-Native Transformation & AI Platforms). Together, they explored this emerging engineering concept, answered questions from the audience, and shared their perspective on what it takes to be a great developer in the AI era. 


This blog post captures the key insights from that conversation.



Yaniv Even Haim
Yaniv Even Haim



The Rise of the xEngineer


The idea behind the xEngineer reflects a deeper transformation in how software is built in the AI era. Rather than focusing on a single specialty or technology stack, the modern engineer operates at a higher level of abstraction, working across systems and leveraging AI throughout the development process.


Three major principles define this shift:



  1. AI Across the Entire Engineering Lifecycle 


Much of the conversation about AI in engineering focuses on code generation. But the real transformation goes far beyond that. AI is increasingly being used across the entire engineering lifecycle: system design, architectural documentation, debugging, testing, and understanding large legacy systems. In many organizations, the biggest challenge isn’t writing new code - it’s managing and evolving massive existing codebases.


AI tools are becoming extremely effective at navigating these "brownfield" systems, helping engineers understand complex architectures and safely improve them. The result is a dramatic reduction in the cognitive load required to work in large, mature codebases.



  1. Smaller Teams With End-to-End Ownership


"We want to see more and more cases where people are able to contribute to other systems. The ability of one person to be able to complete tasks end-to-end, which is also a very big mindset shift." (Yaniv Even Haim)


Traditionally, product development involved many specialized teams: frontend, backend, mobile, infrastructure. Delivering even a modest feature often required coordination between multiple groups, along with meetings, handoffs, and dependency management.


AI is starting to change that dynamic. When engineers can rely on AI assistance to bridge knowledge gaps across technologies, a single engineer can increasingly take a task from concept to production. This doesn’t eliminate expertise, but it significantly reduces the friction between domains. 


The result is smaller teams that move faster, with engineers capable of owning problems end-to-end rather than within narrow technical boundaries.



  1. Building Products Around LLMs


AI is not only transforming how engineers work - it is also transforming what they build. Large language models introduce a fundamentally different paradigm in software development. Traditional software is deterministic: given the same input, it produces the same output. LLM-driven systems are probabilistic and context-dependent. This means engineers must learn new approaches to system design, evaluation, and reliability.


Instead of simply writing deterministic logic, they must design systems that manage uncertainty, guide model behavior, and integrate AI capabilities into real-world products.




The Mindset Shift


"The role begins to resemble that of an architect or director, guiding AI agents and development tools... we'll have those champions of a specific skill that can help us keep the quality." (Asaf Yonay)


Perhaps the biggest change is not technical - it’s psychological.


For many engineers, professional identity has long been tied to mastery of specific languages, frameworks, or platforms. But as AI tools become capable of handling syntax and implementation details, the differentiator shifts.


The most valuable engineers will be those who can:


  • Understand complex systems

  • Define problems clearly

  • Design robust architectures

  • And - orchestrate AI tools effectively


In many ways, the engineer’s role begins to resemble that of an architect or director, guiding AI agents and development tools rather than manually executing every step.



Aviran Mordo
Aviran Mordo


Breaking Down Traditional Boundaries


"The engineer's role starts to look like that of an architect or director, guiding AI agents and development tools rather than manually executing every step." (Aviran Mordo)


One of the organizational implications of this shift is the gradual erosion of strict domain boundaries. Historically, companies maintained separate guilds or departments for backend, frontend, and mobile engineering.


As AI tools make it easier to navigate different parts of the stack, these divisions become less rigid. Engineers are increasingly expected to move across domains when solving problems.


This doesn’t eliminate specialization. Deep expertise still matters - especially at scale. But the baseline expectation is changing: engineers should be capable of operating across the stack with the help of AI.


The emphasis moves away from protecting code territories toward reducing friction and accelerating delivery.



An Opportunity, Not a Threat


Some fear that AI will replace developers. But the bigger picture suggests something different.


As AI dramatically lowers the cost of producing code, engineers gain the ability to focus on what truly matters: creating value for users. Problems that once required months of development effort can now be solved in weeks - sometimes even days.


We are entering a new phase in the evolution of software engineering. A phase where engineers are no longer defined primarily by the code they write, but by the problems they solve and the systems they design.


And yes, the xEngineer may well become the blueprint for what that future looks like.



Asaf Yonay
Asaf Yonay


Summary: Engineering Beyond the Syntax 


The transition to the xEngineer model isn’t just about working faster, it’s about working at a higher level of abstraction. As the technical barriers between frontend, backend, and mobile continue to dissolve, the definition of "expertise" is being rewritten. 


As Aviran Mordo put it during the discussion: "The profession of a software developer is to solve problems. The way that we were taught how to solve a problem is by writing code. We understand now that the skill of writing code is a skill that is maybe less needed as AI becomes better." 


This evolution allows developers to reclaim their original purpose: being architects of solutions rather than just writers of syntax. Success in this new era will be defined by the ability to orchestrate complex systems and maintain a holistic view of the product. 


Yaniv Even Haim summarized the ultimate goal of this shift: "We want to see more and more cases where one person is able to complete a task end-to-end. This is a very big mindset shift, but it's also a productivity multiplier." 


The xEngineer is more than a title, it is the blueprint for the next generation of creators. By harnessing the synergy between human judgment and AI capabilities, we are finally breaking free from narrow technical boundaries-empowered to build the most ambitious, impactful software in the history of our craft.



If you want to learn more about the xEngineer - read:




More of Wix Engineering's updates and insights: 

bottom of page