Nexthink Innovation & Technology Culture

What types of products or services does your engineering team work on/create? What problem are you solving for customers?

I’m the tech lead on Nexthink Assist, an AI capability inside Nexthink Infinity, our digital employee experience platform. Infinity gives IT teams deep visibility and remediation across devices, apps and networks so they can diagnose and fix digital workplace issues quickly. Assist is the simple entry point: It turns natural-language questions into the right data retrieval, analysis and actions so users get to answers faster. In short, it drastically lowers the barrier to entry by allowing anyone to get value from Nexthink much quicker, and ultimately reduces the time from “What’s going on?” to “Fixed.”

Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?

In my daily work as a developer, AI has become an essential teammate. I use tools like Windsurf and Claude Code at almost every stage of the development workflow, designing, coding, debugging, reviewing and even writing specifications. When I start a new project or dive into an unfamiliar codebase, AI helps me quickly understand the architecture, explain technologies and highlight how different pieces connect. During implementation, I guide the model to generate code that fits our patterns, and my role has shifted from writing code line by line to intensively checking, reviewing and validating what AI produces. It’s a bit like pair-programming: I provide direction and context, and AI does the heavy lifting. 

I also use it to draft clear specifications for my teammates, so they have precise guidance before starting their work. That said, I’m always very deliberate about staying in control of what the AI does; I never just accept its output blindly. Overall, it has made me significantly faster and more effective, allowing me to focus on higher-level design and problem-solving rather than boilerplate tasks.

What would that project have looked like if you didn't have AI as a tool to use? How has AI changed the way you work, in general?

Without AI tools, we’d spend more time on boilerplate, digging through docs and manually stitching test scaffolds and refactors, especially when touching unfamiliar areas of the codebase. Work that now takes days would likely take weeks, and we’d ship fewer iterations. AI has fundamentally changed my workflow. It drafts most of my code, allowing me to focus on framing the problem, setting constraints and reviewing the output. It also shortens the onboarding process for unfamiliar projects because it can explain the technology and guide you to the right resources quickly. And when the AI goes in a direction I don’t like, I simply redirect it and correct its trajectory; I’m still fully in control of the implementation. Overall, AI enables me to work faster and smarter while maintaining control over quality and intent.

What is the unique story that you feel your company has with AI? If you were writing about it, what would the title of your blog be?

Nexthink’s journey with AI began two decades ago, when we set out to build a security solution that could detect anomalies, long before AI became the buzzword it is today. While our mission has evolved and we’ve become a leader in Digital Employee Experience, AI in our DNA and data-driven innovation remain at the heart of everything we do.

What was a monumental moment for your team when it comes to your work with AI? 

We see conversational interfaces as the most natural and effective way to access DEX insights. As AI agents evolve, we’re more excited than ever about their potential to deliver personalized, proactive support at scale, reshaping the way our customers experience IT.

AI is a constantly evolving field. Very few people coming into these roles have years of experience to pull from. Explain what continuous learning looks like on your team. How do you learn from one another and collaborate?

We’re all learning as we go, and that’s part of what makes working with AI exciting. No one has all the answers, so we test ideas, share what works (and what doesn’t), and build on each other’s progress. Prototyping is a big part of our process: try fast, learn fast, improve fast. We remain curious and move forward as one team.