What AI Means for Our Clients
Faster Timelines, Fewer Bottlenecks, Better Software
When projects start to slow down—missed timelines, unexpected rework, communication gaps—it’s easy to assume the problem is technical.
Many times, it’s not. It’s day-to-day friction and subsequent bottlenecks: handoffs between teams, back-and-forth discussions on requirements and the time it takes to review, test, and validate ideas that can slow things down.
These issues have always existed because humans are collaborative. Amongst cohesive teams, there will always be a back-and-forth volley of ideas and discussion about the best way to innovate.
This is where AI starts to make a real impact, though—not by replacing developers, but by reducing the friction that gets in the way of good work and true collaboration.
There’s a lot of noise around AI right now, and most of it focuses on speed. But speed alone doesn’t solve the underlying problem. Moving faster without structure just creates more rework later. So our focus isn’t on simply faster, but better.
As our Head of Software Development, Brody Robertson, explained in a recent interview:
“We’re focused on how we leverage AI for small wins initially… integrating efficiency into our process. And it’s not just efficiency—it’s increasing the quality of the software we build.”
The major shift is that AI isn’t just accelerating output; it’s helping improve how the entire process works.
Where AI Reduces Friction
Software development is rarely slowed down by one big issue. It’s a series of small inefficiencies that add up, including but not limited to: unclear requirements, missed edge cases, delayed feedback loops.
AI helps address those gaps directly.
“There are opportunities to introduce efficiency by making the entire workflow more efficient… from the business analysis, definition of scope, backlog… to development and code review.”
One of the clearest impacts we’ve seen is in testing. Testing has always been essential, but it’s also where time constraints tend to show up. There’s only so much coverage a team can realistically achieve. But utilizing AI doesn’t mean more or less work. What matters is making sure the work holds up. Through thorough testing and easier validation, clients end up with less surprises downstream.
Every development process has natural slow points—reviews, approvals, clarifications. Traditionally, the only way to move faster was to add more people or cut corners. AI creates a third option for developers.
“We can increase the amount of automated testing… we can make [the workflow] more efficient and catch more issues… because we have agents doing code review.”
Why Better Processes Deliver Better Outcomes
In the end, the combination of speed and rigor becomes the true selling point of AI for both the clients and the developer team. When used correctly with experienced developers, we can see optimized outcomes: projects moving predictably along a timeline, more efficient collaboration amongst teams, and products strengthened. Not only that, it allows us to operate more efficiently as a team.
For our clients, that means better software delivered with fewer obstacles, less rework, and more confidence at every stage. Because AI isn’t replacing expertise. It’s sharpening it, strengthening the systems around it, and making strong teams even better.