From Iteration to Curation and Why AI is Changing the Way Leaders Build Products
Written by Laura McCann, Founder & CEO of Auratherapy
Laura McCann is the Founder and Chief Executive Officer (CEO) of Auratherapy. A 30-year Consumer Packaged Goods (CPG) and tech founder, she’s building a modern movement at the intersection of scent, energy, and self-mastery, turning daily rituals into transformation.
When I built software fifteen years ago, I accepted a simple truth: you couldn't possibly know everything at the beginning of a project. That was the philosophy behind Agile. You started with a vision, gathered enough requirements to begin, and trusted that the product would evolve as the team learned. Each sprint brought new discoveries, new questions, and, inevitably, new changes. It wasn't considered inefficient; it was simply the reality of building software.
This year, I found myself leading another software project after more than a decade away from product development. I expected the technology to have changed. I expected better tools, faster development cycles, and more sophisticated platforms. What I didn't expect was that my own role as the CEO and subject matter expert would be transformed.
I'm currently building ATOS, a software platform for Auratherapy that brings together our Aura Reading Method, practitioner training, client experiences, and personalized wellness journeys. I am not the engineer on the project, nor am I writing production code. My responsibility is to define the vision, articulate the business requirements, and ensure that the software reflects the experience we want to create for both practitioners and clients.
Somewhere in the middle of that process, I realized I wasn't working the way I had before, and neither was AI.
What began as a tool for organizing ideas quickly became something much more powerful. Instead of helping me document requirements, AI began helping me think.
As a designer by training, I have always approached problems visually. My instinct is to explore possibilities, sketch concepts, connect patterns, and imagine the experience long before I think about implementation. As a CEO, however, I've learned to balance that creative instinct with operational realities: budgets, resources, timelines, staffing, and execution. My career has always lived somewhere between those two worlds. I move comfortably between strategy and creativity, between vision and operations, between what is possible and what is practical.
For the first time, AI felt like it was operating comfortably in both worlds with me.
What surprised me wasn't how quickly it could generate content. It was how dramatically it expanded my ability to explore ideas before asking anyone else to build them.
Within a single afternoon, I could model customer journeys, test alternative workflows, organize complex business rules, identify edge cases, draft functional requirements, simulate user interactions, create interface concepts, and pressure-test assumptions that previously would have surfaced weeks or months into development. Instead of arriving at a sprint planning session with a handful of loosely defined user stories, I was arriving with an increasingly refined vision of where the product could go. That shift forced me to ask an uncomfortable question.
If AI allows leaders to think this far ahead, are we still organizing product development around the right constraints?
For decades, software development was limited by engineering capacity. Building features was expensive. Prototypes required significant effort. Every change consumed time, money, and resources, so organizations learned to manage uncertainty by discovering the product incrementally. Agile became the framework that allowed teams to learn while they built.
Today, many of those assumptions are changing. The cost of exploration has dropped dramatically. It no longer takes weeks to evaluate a new concept or visualize an alternative workflow. As a result, ideas are no longer the scarce resource. Judgment is.
The challenge is no longer generating possibilities; it is deciding which possibilities deserve to become part of the product. That realization has changed the conversations I have with my own development team.
Our engineers still work within structured Agile sprints, and they should. Building reliable software requires discipline, planning, and predictable execution. My work, however, no longer happens only during sprint planning sessions. Between those meetings, I am continuously exploring the product with AI. I refine business processes, rethink user experiences, reorganize requirements, validate assumptions, and often uncover opportunities that simply weren't visible a few days earlier.
From the outside, it might appear that the requirements are changing more quickly than they used to. From my perspective, they are becoming more complete before development begins. That distinction matters.
What I am discovering is that AI hasn't accelerated Agile nearly as much as it has accelerated product discovery. The sprint is still the place where software gets built. Increasingly, however, it is no longer the place where the product is first imagined. That work is moving upstream.
As I reflected on this process, I realized that another change was taking place, one that has less to do with technology and more to do with people.
For years, software organizations depended on translation. Subject matter experts explained the business. Business analysts translated those ideas into requirements. Product managers organized priorities. Designers translated concepts into interfaces, and engineers translated those designs into working applications. Each role served an important purpose because information had to move carefully from one discipline to the next.
AI has not eliminated those roles, but it has fundamentally changed what each of them contributes.
Today, subject matter experts can explore ideas independently at a level of depth that previously required an entire team. Business analysts can model processes in minutes instead of days. Product managers can evaluate multiple approaches before prioritizing a backlog. Designers can prototype variations almost instantly. Engineers can automate portions of implementation that once consumed weeks.
Every discipline has become more capable. Ironically, that creates a new challenge. When everyone can generate more ideas, more versions, more documentation, and more possibilities, the organization needs someone whose primary responsibility is not creation but synthesis.
Someone has to connect the dots. Someone has to recognize patterns across hundreds of iterations, preserve the strongest concepts, eliminate redundancy, and translate an evolving body of knowledge into work that can actually be executed.
I don't believe we have fully defined that role yet, but I believe we soon will. Whether that person is called a product leader, a business architect, or something entirely new, I suspect one of the most valuable capabilities inside modern organizations will be the ability to curate intelligence rather than simply create it. That is a different kind of leadership.
It also has implications for how we think about budgets and resources. For years, organizations primarily invested in implementation. We estimated engineering hours, design hours, quality assurance, and project management because those were the activities that determined cost and schedule. Strategic exploration happened, but it was constrained by time and budget.
AI changes that equation. Exploration has become inexpensive. What now consumes time is reviewing, synthesizing, validating, and making thoughtful decisions from an abundance of possibilities. In many organizations, the bottleneck is shifting away from producing ideas and toward curating them into a coherent product strategy.
That may ultimately prove to be one of AI's greatest contributions, not that it helps us build software more quickly, but that it helps us make better decisions before software is built at all.
I don't believe this represents the end of Agile. Quite the opposite. Agile remains one of the most effective frameworks for delivering complex software. What I believe is changing is where Agile begins.
In the past, we expected discovery to happen throughout development because there was no practical way to explore every possibility beforehand.
Today, AI allows us to arrive at development with a far richer understanding of the product than was ever possible before. Agile becomes the execution engine, while AI expands the strategic thinking that feeds it. We're still writing software. We're simply thinking differently before we do.
As a founder, I find that both humbling and energizing. Every week I discover a new way that AI changes how I communicate ideas, structure information, or evaluate decisions. I also discover that the people around me are adapting just as quickly. None of us has a playbook for this yet, and perhaps that's what makes this moment so exciting.
Looking back, I thought I was building a software platform. Instead, I found myself participating in the redesign of how product leadership itself may evolve.
The companies that thrive over the next decade won't necessarily be the ones that generate the most ideas. AI will make that increasingly accessible to everyone.
The advantage will belong to those who learn how to curate, synthesize, and translate those ideas into products that solve real problems for real people.
That feels less like the next version of Agile and more like the next evolution of leadership itself.
Read more from Laura McCann
Laura McCann, Founder & CEO of Auratherapy
Laura McCann, a former child star, France-raised creative, NY fashion alum, and tech entrepreneur, now leads Auratherapy as Founder & CEO. With 30 years as a founder across CPG and tech, she’s bringing luxury and innovation to functional fragrance through breathable, essential oil-based Aroma Perfumes and water-based aura sprays. Auratherapy pairs this with data-driven aura and chakra diagnostics that translate energy into personalized rituals. Her mission is to help people reclaim their breath, remember they are vibrational beings, and transform through the practice of adoring yourself.
