In Conversation: Marie Doce on Building Smart, Sustainable AI
In today’s fast-evolving AI landscape, innovation isn’t just about chasing trends, it’s about solving real problems with clarity, care, and purpose. Few embody this ethos as clearly as Marie Doce, co-founder of a boutique product and development agency, Hyperfocus AI. With a background in product leadership and a deep commitment to responsible innovation, Marie approaches complexity not by stacking tools or scaling recklessly, but by staying lean, intentional, and grounded in real user needs.
At a time when many startups race to launch at all costs, she offers a more sustainable model for building in tech, one rooted in long-term value, contextual design, and ethical thinking from day one. We sat down with her to unpack what sustainable innovation really looks like in practice, how small teams can build with big impact, and why clarity is the foundation of any future-ready tech stack.
What sparked the idea for Hyperfocus AI? Was there a moment when you knew, “This has to exist”?
Marie: The idea really came together during a conversation in late March. My co-founder and I had been bouncing around a lot of ideas, but this one felt different. We were talking about a gap we kept seeing: there are lots of big agencies and consultants on either end of the spectrum, but not much support for early-stage teams who need to build something without the overhead or costly fees that come from working with a large, outsourced team.
I’ve worked on AI products at the enterprise level and seen how much work it takes to get them from idea to launch. My co-founder is an engineer who’s built full-stack systems in fast-moving environments. Between the two of us, we realized we could offer something truly useful to founders trying to make progress without hiring a huge team. That was the moment we thought, yes, this could really fill a need in the current market.
AI copilots are everywhere. What made you confident that there was still space to innovate and serve founders differently?
Marie: Yes, the space is saturated, but there’s still room to build in industry-specific spaces with tools that are designed to handle the context they’re working in. That’s especially true in highly regulated industries like legal and healthcare, where the stakes are high and the workflows are complex.
Those are areas where AI can make a real difference not by replacing people, but by removing rote tasks and, in doing so, helping users spend more time on meaningful work.
In a fast-moving industry, how do you balance urgency with durability? What guides your decision-making beyond just shipping fast?
Marie: This is where product experience really matters. Early on, I learned that moving fast doesn’t mean saying yes to everything; it means being clear about priorities. That starts with deeply understanding the customer’s pain points and being honest about what really needs to be in an MVP.
In past roles, I spent a lot of time aligning stakeholders, managing scope, and setting expectations upfront. That skillset is crucial now, especially when we’re deciding what to ship first and what can wait. Being a small team helps, too. Fewer layers mean less overhead, fewer handoffs, and a much tighter feedback loop. It’s easier to stay focused when nothing gets lost in translation.
Hyperfocus works closely with early-stage founders. What’s been the hardest part about truly fitting into their daily workflow?
Marie: The hardest part is that no two founders or workflows are the same. To really fit in, you have to truly understand the mindset. That’s why in every early conversation, I ask, “What made you start this company? What problem are you solving for your users?”
When I understand the story behind the startup, it’s a lot easier to meet teams where they are. It’s not about dropping in with a generic solution; it’s about plugging into what they’re already doing and helping them move faster in the direction they already want to go.
Let’s talk gender and leadership. Is the conversation around women in AI shifting meaningfully or still mostly surface-level?
Marie: Only about one in five product or engineering leaders in AI are women, and it’s not because the talent isn’t there. Discrimination in tech is real, and it continues to push women and people of color to the margins of the industry, or sometimes out of it altogether.
I do think the conversation is shifting, but slowly. I’ve been inspired by many women in the field of ethical AI who continue to be prominent and impactful voices — Dr. Timnit Gebru and Dr. Joy Buolamwini, to name a couple. So yes, the important conversations around representation in AI are happening, but you have to know where to look for them.
As a founder, how do you navigate the tension between innovation and responsibility in AI? Where do you draw the line?
Marie: Very carefully, from the very beginning of a product build. I don’t think innovation and responsibility are inherently at odds, especially in AI. But you do have to build with intention. That means thinking about potential risks from day one, not later on.
In earlier SaaS products, QA was pretty linear. But, with generative AI, the unpredictability, hallucinations, edge cases, and harmful outputs make those earlier processes insufficient. One person testing a tool can’t possibly catch everything. That’s why we involve a broader, more diverse group in evaluation early on. To me, responsible AI shouldn’t be a blocker. If you bake it into your process upfront, you can move fast and build something you’re proud to put in front of real users.
Startups often feel the pressure to scale. How do you protect product clarity while chasing growth and market fit?
Marie: This is where my startup experience really matters. I’ve seen firsthand what happens when companies scale too early: teams grow too fast, and it often leads to culture clashes, broken processes, and eventually, layoffs. It’s a pattern I’ve learned to avoid.
We’re choosing to stay lean on purpose. We want to prove market fit first, then scale in step with what we learn. Especially in AI, things shift fast, and what seems like a smart move today might look very different six months from now. Roles are evolving, tools are evolving, and our understanding of what’s actually useful is still taking shape.
That’s why we’re prioritizing focus and flexibility over headcount. Growth will come, but we want to grow around the right product, not the other way around.
What’s surprised you the most since launching Hyperfocus AI? Anything that changed how you think about this space?
Marie: One of the biggest surprises has been realizing just how early this space still is. When you’re a new founder, especially from a group that’s underrepresented in tech, it’s easy to look around and think, “Everyone else already has it figured out.” I definitely felt that pressure when I was trying to define what Hyperfocus AI could be.
But the truth is, even companies that seem further along are still figuring things out. The field is moving fast, but it’s also wide open. That’s been the most exciting realization: there’s still so much room to build, explore, and shape what comes next. You don’t have to wait for permission to start — the areas of innovation are limitless, and I truly believe there are many more applications for AI that haven’t been uncovered yet.
Many AI tools still focus on flashy demos. How important is “invisible UX” in your product philosophy?
Marie: Invisible UX is core to how we think about building. A lot of people are intimidated by AI, and it’s our responsibility as builders to make it less so. If we want these tools to be useful outside of tech circles, they need to feel intuitive, not overly technical.
The goal is to make AI work in the background so users can get things done. That’s especially important if we’re trying to bring AI into industries where people aren’t used to working with complex software. A seamless experience isn’t just good design, it’s what makes adoption possible.
You’ve led product at multiple startups. How has that experience shaped how you lead and build at Hyperfocus AI?
Marie: My startup experience has shaped how I lead in a meaningful way. As a product leader and now a co-founder, I focus on leading with empathy, clarity, and decisiveness. Over the years, I’ve worked closely with engineering and customer-facing teams, and I’ve learned how important it is to communicate clearly across both.
One thing I’ve consistently heard in past roles is that my strong communication and documentation skills made things easier for everyone involved. That’s something I’ve carried into Hyperfocus AI. Founders are juggling so much, so part of my job is helping them work through the chaos, stay focused, and keep momentum without getting overwhelmed.
When you think about building a ‘sustainable tech stack,’ what does that mean in your context, as a founder and a builder? And how do you choose tools or infrastructure that won’t create friction or technical debt down the road?
Marie: To me, a sustainable tech stack is one that supports learning early and scales gracefully later. It’s easy to fall into the trap of trying to future-proof everything from day one, but in reality, the priority early on is product–market fit.
That means choosing tools that let us move fast, experiment, and actually get something into users’ hands. If we run into scaling issues later because too many people are using the product, that’s a great problem to have. At that point, we’ll have real data to guide more choices on tooling and infrastructure.
Sustainability in this context means avoiding premature complexity and choosing tools that can evolve as the product does, without slowing us down now.
A lot of teams equate scale with success. But your approach seems more focused on staying small and sharp. How does that mindset impact the way you build your tech stack?
Marie: I do think a lot of teams equate scale with success, which can be risky. To me, scale should be earned, not assumed. When you grow too fast without a strong foundation, you open the door to layoffs, burnout, and financial instability.
At Hyperfocus AI, we’re taking a different approach. We’re focused on staying small, sharp, and aligned with what’s actually working. That mindset shows up in how we build our stack: we use tools that are lightweight, flexible, and easy to evolve.
It’s not about building for some hypothetical future, it’s about solving real problems well, right now. If we get that right, scale will follow.
Everyone talks about responsible AI, but what does that look like in practice, inside your team and products?
Marie: For us, responsible AI means building with intention from day one. It starts in the ideation phase when we think through potential risks before a single line of code is written. It also means asking better questions during customer feedback sessions: not just “Is this useful?” but “Could this do harm?” or “Where might this go wrong?”
That kind of upfront thinking helps us spot risks early, when they’re still easy to address. The goal isn’t just to avoid bad outcomes, it’s to build tools that genuinely help people.
As you build out the Hyperfocus team, what kind of culture are you intentionally trying to foster?
We’re building a culture rooted in intentionality, clarity, and speed. That starts with asking the right questions: What are we building, why, and who does it serve?
We want everyone on the team to feel a sense of ownership over those answers. Openness and transparency, both internally and with our partners, are core to how we work. When you’re clear from the beginning and aligned on purpose, speed follows naturally.
It’s not about rushing, it’s about removing friction so we can move fast without losing focus.
And finally, what’s next for Hyperfocus AI, and what are you most excited about in the coming months?
Marie: Right now, we’re loving the work we’re doing with early-stage partners, but we’re also heads-down building our own product. It’s in a space that’s both context- and compliance-heavy, where we’ve seen real unmet need, and where we bring a lot of firsthand experience.
We’ll have more to share soon, and I’m excited for what’s coming. It feels like the right time to build something that’s both deeply useful and built to last.
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