JumpCloud Innovation & Technology Culture

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?
JumpCloud’s unique AI story starts with the reality that we work in a complex, multifaceted domain — managing identities, devices, access, LDAP, RADIUS, SaaS tools and more. AI became a key tool not for doing the same work with fewer people, but for enabling the same team to do ten times more without being overwhelmed. It helps us make sense of large, interconnected systems quickly, contribute to unfamiliar projects and turn ideas into working solutions faster. A fitting title might be “Amplifying Impact: Using AI to Thrive in Complexity at JumpCloud.”

What was a monumental moment for your team when it comes to your work with AI?
One monumental moment was when we started using AI primarily for code editing. It immediately made mundane tasks like formatting, refactoring and writing boilerplate code faster, easier and more reliable — freeing us up to focus on the harder problems. Another key moment was during new hire intakes: AI’s ability to parse and analyze thousands of lines of code helped new engineers onboard more efficiently. And since documentation can quickly become outdated, using AI to generate up-to-date diagrams and flow visuals, then reviewing and signing off as a team, became a game changer. These use cases showed real, practical value — AI combined with human judgment made us significantly faster and more effective.

What challenges did your team overcome in AI adoption? 

Initially, integrating AI felt overwhelming — many on the team, especially senior engineers, were skeptical about its real-world value. Others, often juniors, expected it to do everything from debugging to writing entire modules. We focused on tools like GitHub Copilot to bridge the gap and demonstrate how AI can assist, not replace. Prompting became a core skill — figuring out how to ask the right questions to get meaningful, usable help. Over time, this built trust and practical understanding.

A big part of this shift came from having a general #gen-ai Slack channel. People shared everything — from Studio Ghibli-style AI photos to real stories of how AI made their work easier or more efficient. It sparked creativity and inspired others to try new workflows. Now, AI adoption is companywide, and we’re even hosting AI-focused hackathons across teams.

What new technologies or frameworks are helping your teams move faster and build smarter?

As with most organizations we’re heavily leveraging AI and improved processes to dramatically speed things up. While AI is certainly helpful, we’ve found that you get the most impact out of it when you rethink how a product is built from the ground up. We overhauled our product design lifecycle to pull left a lot of the work that was otherwise being done later in the process. PMs for example, do a lot of iteration of a new design on their own using a toolset that we’ve developed in-house to get fully functioning PoCs in the hands of others in the company and even customers before any engineer starts work. This way we can remove a lot of the iterations that would otherwise be required as the product and engineering teams refine the feature set of what they are working on.

How do you balance experimentation with reliability in your development process?

This is a great question and something that we’ve been constantly tweaking as we’ve been iterating on this process. Even with all the new tooling that’s available, the same basic precepts hold true, they just may be in a different order. We let our product and UX teams go bananas on the prototypes and proof of concepts. They can explore pretty much any ideas that they want and we’ve given them a safe sandbox that they can do this in all hosted in the cloud so it’s easy to share with others. However, once the product and UX ideation is over, none of that code goes to the engineering teams. The engineering process starts with a detailed product requirements document, a pixel perfect UX design and the technical documentation already written. The developers then have everything they need to quickly work on the project without having to wait on questions being answered by the product team. This keeps the actual development process strictly within the confines of our software development lifecycle and lets us follow a lot of well traveled paths.

What role does collaboration play in turning innovative ideas into products? 

As a fully remote and global company, we spend a lot of time ensuring that good collaboration can happen at the right time. Part of the changes we’ve made to our product design lifecycle has been to allow smaller teams to work asynchronously without having to wait on others. That’s not to say we don’t value collaboration, but more that we want to make sure that teams aren’t blocked. Our product is becoming increasingly matrixed and work on a particular feature may span a number of teams to ensure the integration that we’re looking for, but now that we can easily pass around fully functional proof of concepts, each team can be clear on what the product is supposed to do and what they need to build.