It's Not All About the Code: What Makes a 10x Engineer Today

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The idea of the 10x engineer, the belief that one developer can be ten times more productive than another, has been around for nearly sixty years. It started with a 1968 study by Sackman, Erikson, and Grant, which found performance gaps as large as tenfold among experienced programmers. Fred Brooks made the idea famous in The Mythical Man-Month, where he suggested building a “surgical team” around one standout engineer. The term became industry shorthand and, over time, a bit of a joke on social media.

But do 10x engineers still exist? Today, the question itself has changed. AI coding assistants have made raw coding speed much less important. When a model can draft, test, and refactor code faster than any person, being able to “write code ten times faster” doesn’t mean as much. Now, what matters most is judgment: knowing what to build, spotting mistakes before they go live, and making architecture choices that pay off later. The industry has shifted from focusing on lone geniuses to valuing engineers who make the whole team better.

This is why we need to rethink what top engineering talent looks like today and how to measure it. In my experience, coding skills are just one part of the picture.

Four traits set apart elite engineers who create lasting value:

1. Technical and coding skills,
2. Understanding the engineering context,
3. Collaboration and communication,
4. Empathy.

Here’s how to assess each one, whether you’re looking at your current team or hiring new people.

Talent Trait #1: Technical and Coding Skills

I’ll admit it: you still need a basic level of technical skill. The good news is that this is one of the easiest things to check, even when interviewing remotely.

Coding exercises are easy to create and send out, and they work well as a first filter for basic skills. But in the age of AI, they aren’t as reliable. That’s why I rely more on live coding, pair programming, and using real-world problems. Solving a problem together reveals things you can’t see in a finished take-home project: how the candidate approaches the task, how they ask questions to clarify unclear requirements, and whether they naturally use logging, testing, mocking, and serialization. When anyone can generate decent code quickly, being able to explain your thinking out loud is what really stands out.

Talent Trait #2: Understanding the Engineering Context

Technical skill only gets you so far without context. You need to know whether a candidate understands how code flows from inputs through the pipeline to production. Do they know what a deployment environment looks like and how to organize code to deliver real value to the business and users? Writing code is just one part; building systems that turn it into working services takes more experience.

Testing for this takes more effort from the interviewer, but it helps spot weak candidates early. You can set up a web service and ask them to use it, provide an existing codebase to extend, or have them submit jobs via a build system. These tasks move the candidate out of isolation and closer to real work. Keep in mind, though, that this approach only works if the interview panel knows exactly what the role needs.

Talent Trait #3: Collaboration and Communication

Engineering is a team effort. With continuous delivery, engineers need to work together at every stage. Often, someone who collaborates well adds more value than a brilliant jerk who doesn’t. The lone “rockstar” genius who leaves behind unmaintainable code and frustrated teammates isn’t a 10x engineer. They’re a ticking time bomb with a great reputation.

At its core, development is about communication. It’s not just about passing designs from managers to developers, but also about debating solutions, building consensus on tough decisions, and ensuring everyone understands what’s needed. A good engineer understands the intent behind a project, not just the list of requirements.

To assess this, set up peer feedback loops for your current team. For candidates, create an exercise that requires collaboration, like asking them to update earlier code based on new input from a designer or product manager. Pay attention to how they handle feedback. Someone who takes feedback well is often more valuable than someone who does great on tests but gets defensive when challenged.

Talent Trait #4: Empathy

Empathy might not be the first thing you think of in engineering, but it’s a key to building strong teams and products. In software, empathy means understanding the real people your technology helps. Whether you’re building a reservation app or automating marketing, the team needs to consider everyone involved: the operations team checking logs, customer support helping users, product managers reviewing analytics, and QA engineers testing releases. An empathetic engineer doesn’t just ask if a feature adds value; they also look for ways to reduce friction for every downstream consumer of their work.

Empathy is also the hardest trait to measure, since you can’t test it with tools or checklists. The best way to spot it is through a conversation after the candidate has shown their technical, contextual, and communication skills. Are they interested in the wider organization, the people they’ll work with, and the customers they’ll serve? Do they feel responsible for the user experience, or do they stop caring once their code is done? Reference checks help too: did this engineer go beyond the basics and speak up for others, even when it wasn’t required?

Conclusion: Build a Team That Lasts

Think long-term. You’re not just hiring for today; you’re building a team you want to keep. That means hiring for growth potential as much as current skills. Communication, collaboration, and empathy show how much someone can grow over time, and technical skills can usually be taught to people who have these traits.

This brings us back to the main point. Raw coding speed no longer defines a 10x engineer, since technology now handles much of the speed for us. What’s rare now is the judgment to use these tools well and the ability to adapt as things change. An average engineer who communicates well, works well with others, and cares about the people who use their work has the greatest potential to grow in a supportive organization. In the age of AI, that kind of engineer, not the fastest coder, is the one most likely to deliver 10x value.