As a professional volleyball player in Brazil, Rose Hecksher Schamberger saw that success depends on synchronized teams rather than individual heroics. It’s a lesson she now applies when explaining how to shorten software development timelines to clients. That lesson has become a cornerstone of her leadership philosophy, shaping how she thinks about collaboration and execution. “When you play your position well but still connect seamlessly with teammates, the overall performance improves. I try to build engineering teams with that same spirit,” she says, pointing to the parallels to the dynamics of team sports where success comes from aligning diverse skill sets toward one objective and executing with precision.
Today, as a seasoned CTO with two decades of experience leading modernization and growth, she applies that playbook to engineering organizations. Her core principle is to optimize how work flows so value reaches customers sooner, without burning out teams or wasting resources.
Shorter Cycles, Stronger Businesses
Lengthy release plans erode momentum and confidence. Schamberger has seen otherwise strong initiatives stall under the weight of twelve-month roadmaps that are vulnerable to shifting priorities and funding pressure. “The longer it takes you to get value from your development, the harder it is to keep going,” she says. Her counter is to break ambition into increments that prove value early, not six months from now. “Take the big thing and find something small and valuable from the user perspective that you can produce,” she adds. Early increments generate revenue, feedback, and internal excitement, which protects investment and surfaces course-corrections before sunk costs compound. The discipline also improves morale. Teams stop “hiding in the lab” and start delivering visible outcomes that validate strategy every quarter.
Introducing Agile That Actually Works
Agile is a family of lightweight, iterative practices—Scrum, Kanban, XP—that replaces long, sequential projects with short, outcome-focused cycles. Work is sliced into small increments, each designed to deliver user-visible value, with planning, building, testing, and learning happening continuously. The point is not speed for its own sake; it is faster feedback that de‑risks investment and keeps teams aligned on what customers actually need.
Schamberger prefers to see Agile as a framework. “Do not pick and choose in the recipe,” she says. “Use the recipe as written, and adjust to your flavors. Less salt, more pepper, but do not remove the salt and pepper altogether.” In practice that means stable, cross-functional teams with a shared definition of value, product backlogs groomed against clear outcomes, and increments that can be put in front of customers even if they are not yet fancy. “Agile is not cutting corners,” she says. “It helps you break things into deliverables you can validate with the market.” The goal is to prove the product’s core promise quickly, then iterate with real-world input rather than slide-deck assumptions.
Automation That Sticks
Automation is the second flywheel in Schamberger’s approach. She favors end-to-end consistency over isolated tooling, because repeatability enables trustworthy comparisons across builds, sprints, and environments. “Anything you can make more efficient and repeatable helps,” she explains. That includes CI and CD pipelines, test automation that executes the same checks today and tomorrow, and telemetry that links code changes to user outcomes.
When teams automate the path to production and the feedback loops around it, they remove busywork and reduce variance, which shortens cycle time without sacrificing quality. The compounding effect is significant in early stage companies as well as at scale, because a consistent delivery system lets small teams punch above their weight while large organizations keep many squads aligned on the same definition of done.
What AI Changes and What It Does Not
AI is accelerating the front end of software creation. Schamberger is careful to place it inside a human-in-the-loop model. “AI is not replacing software developers,” she says. “Leverage AI to produce first phases faster and to clean up routine work, but keep engineering judgment in place.” For net-new initiatives, AI can help teams draft scaffolding, generate tests, and explore design alternatives in hours rather than days. For mature products rich in domain logic, she advises starting slower so systems can absorb context. The objective is cycle-time compression with accountability. “If you go with AI only to save a couple bucks, you will not use it to the best extent,” she adds. When AI is woven into a sound Agile cadence and a reliable automation backbone, it amplifies both, turning a static process into a learning system that accelerates with each iteration.
The Scoreboard That Matters
For Schamberger, success is measured by tangible business outcomes, such as customer impact, revenue growth, and team resilience, rather than by process rituals or surface‑level metrics. Faster cycles de-risk investment and let leaders pivot with evidence. Automation safeguards quality while removing toil. AI speeds discovery without diluting accountability. The philosophy is pragmatic and team-centric, shaped by years of building collaborative cultures that perform under pressure. “There are multiple ways to solve a problem,” she says. “A well-tuned machine finds those ways better and faster than a traditional group that follows predetermined steps.” That is how development cycles shrink by 40 percent while margins expand and customers feel the difference.
Connect with Rose Hecksher Schamberger on LinkedIn for more insights.
