Volaris Group’s learning events and programs, including the AI Accelerator, are helping the business move faster when learning new tools and skill sets
Volaris Group is introducing the AI Accelerator in 2026, a program designed to upskill developers, product teams, and business leaders and help companies advance their AI maturity and fluency. We are profiling some of the businesses that have participated in the program and are moving from AI experimentation to adoption and beyond.
Sansio, a company that joined Volaris Group’s healthcare portfolio after being acquired in 2021, is no stranger to reinvention.
The business has been developing software for emergency responders and healthcare providers since its founding in 1999. In its nearly 30 years of serving customers, Sansio has ridden several waves of technological change. The current AI moment is just the latest in a series of pivots that the company has had to navigate. Luckily, after being acquired by Volaris and gaining access to a wealth of resources to upskill their teams, they are well along their way in accelerating their adoption of the latest tools.
Several members of the Sansio team attended the Volaris AI Accelerator in 2026 and have set their intentions toward translating the learnings into tangible returns for the business.
Embracing the benefits of using AI for software development
One of the areas where Sansio is exploring improvements in speed and productivity is in using AI to code.
“The big buzzword is spec-driven development, where you spend most of your time talking with AI about the overall concept, the constraints, and the reasoning, and then set the AI into motion to produce the code that will do everything you just said,” she describes of the process of using AI as a coding partner.
This new way of creating code is changing the way teams work, with developers and product leaders having to develop their “T-shaped” skill sets—broader skills that go beyond their traditional areas of expertise.
“Memorizing syntax is not important anymore in the same way that it used to be,” Kuno says. Instead, she sees the new skillset as being systems-level thinking—being able to think cross-functionally and think through business acumen, user-facing concepts, and reasoning about the software architecture.
Overcoming the new challenges of spec-driven development
As can be the case when creating a workflow, the team is working through issues that are unique to adapting spec-driven development to their existing way of working.
For example, code review presents a challenge for the development team. Although AI-enabled software development enables faster initial coding, it is still necessary for human eyes to ensure that the AI has generated a solution that the business needs and identify any hallucinations or security risks.
One concept that can help with spec-driven development is the Architecture Decision Record, or ADR. The Sansio development team was introduced to this concept through the AI Accelerator. The idea behind it is to generate a document that accompanies the AI-generated code that captures the logic behind the code—not just what decision was made, but why, and which alternatives were ruled out along the way.
The ADR documentation serves double duty by providing developers with context to revisit past choices and giving AI the same context so it isn’t retreading ground that has already been covered. Sansio sees this as an important component to add to their workflow going forward.
Overcoming legacy infrastructure challenges
Another challenge encountered has been the company’s legacy code base. With older code bases, there are “rules you have to play by that are already in place,” as Kuno explains it.
To overcome this challenge, Kuno and Sansio’s lead developer, Melissa Zamzow, have been building a new platform that gives the team freedom to try spec-driven development in a new environment. The new platform lets developers avoid having to retrofit AI into an existing and complex code infrastructure, sidestepping legacy platform issues that would keep them away from innovation.
How AI can help teams bridge the collaboration gap
An advantage that AI can bring to teams is encouraging stronger communication skills and bringing team members closer together for cross-functional collaboration.
A moment that stood out for Sansio at the AI Accelerator was one that brought together the R&D and product sides of the business. Kris Ruhl, Director of Product Management at Sansio, had built a prototype as part of his participation in the AI Accelerator’s product track.
After sharing his prototype with the team, they discovered that the idea behind the prototype was a similar concept to something that his colleague, Taylor Kuno on the development team, had been trying to articulate to him before. They realized that the two of them had been thinking in parallel, separated by a communication gap. Their conclusion? That AI can enable an environment where team members can build toward a shared vision without talking past each other.
For product team members like Ruhl, AI enables them to prototype in their natural language so that they can bring something to developers that is concrete and grounded in code, rather than a purely abstract, high-level idea, which can be challenging to implement.
“We’re at a round table with our development team, and we’re all writing code together and merging it,” he said of the collaborative environment fostered by the new AI tools and the support of the AI Accelerator event. “We’re about to start the QA (quality assurance) process together.”
Beyond learning to vibe code prototypes, the AI Accelerator also challenged product teams to conduct rapid market research and conduct interviews with customers. In particular, the rapid market research activity left a strong impression on Ruhl.
“Using the tools that were provided this week, we’ve opened doors and found ways of doing market research that really we never would have thought were possible,” he shared.
Some of the things we’ve actually produced in four hours during the event this week, it would have taken us four weeks to do prior to that.
-Kris Ruhl, Director of Product Management, Sansio
Lessons to take back to the business after the AI Accelerator
The team came away from the AI Accelerator refreshed with new ideas, big goals, and lessons from the week.
“The new skill set is communication, or at least one of the really big ones, in my perspective,” Kuno says, observing that articulating instructions clearly to AI becomes increasingly important in spec-driven development. But it becomes even more important as the new AI work environment brings different parts of the business closer together.
The new skill set is communication… ‘Garbage in, garbage out’ is the phrase. Are you are you covering all your bases and communicating that to your team members and to AI in a way that pushes things forward? Can you describe what’s in your mind as a developer, as a product person, as a business leader? Can you describe that in a way that resonates with your team?
-Taylor Kuno, Developer, Sansio
Reflecting on the team’s ambitions after returning from the Volaris AI Accelerator, the Sansio team in attendance say they are already discussing how to recreate a version of the learning event within their company—possibly an “AI challenge week” designed to bring in colleagues who couldn’t attend to show them what’s possible with AI.
“Seeing is believing,” said Ruhl of his supercharged experience at the AI Accelerator.
