T.A. McCann, managing director at Seattle-based Pioneer Square Labs, talks with Boaz Ashkenazy on the Shift AI Podcast.

“I think any pitch that doesn’t have AI in it is just not going to get a look unless the team is incredible… but it’d be unlikely that an incredible team wouldn’t be at least thinking about leveraging the newest, coolest technology. It’s just that important.”

That’s one of the observations from T.A. McCann, managing director at Seattle-based Pioneer Square Labs, on this episode of Shift AI, a show that explores what it takes to thrive and adapt to the changing workplace in the digital age of remote work and AI. We discuss TA’s background and experience building fast-growing venture backed startups, and learn important lessons on ways to bring AI-first products to market.

Listen below, and continue reading for highlights from his comments, edited for context and clarity. Subscribe to Shift AI and hear more episodes at ShiftAIPodcast.com.

Family and Upbringing: From my father, I gleaned the importance of sales and a broader understanding of the world. He was a phenomenal storyteller, a skill that has proven invaluable in my entrepreneurial endeavors. The art of storytelling is essential whether one is communicating with oneself, customers, or investors. His teachings have helped shape my business acumen and worldview.

My mother, a sailing instructor, taught my brother and me the value of trying new things. Her encouragement led us to venture into diverse activities, from sports to building websites. This attitude of “just try it” has been instrumental in my life, fostering both self-reliance and resilience. My home was a breeding ground for these virtues, shaping how I approach challenges and opportunities today.

Sailing & Startups: Growing up near Lake Michigan, I was captivated by sailing from a young age and eventually joined the America’s Cup team as a technical expert, winning the Cup in 1992. This experience paved the way for my transition into the technology sector, where I started building websites for the marine industry. I often draw parallels between the worlds of sailing and startups, emphasizing the value of the lessons I’ve learned on the water in my talks.

Three key takeaways from winning the America’s Cup that apply to running a successful startup include: 

  • Investing in the right engineers and resources creates a technological edge; 
  • Budgeting and innovation go hand-in-hand, and understanding how to allocate resources is crucial; and 
  • Leadership dynamics and effective team integration are vital for success. 

Both in sailing and startups, the capacity to endure and stay motivated often correlates with greater progress.

Lessons from Entrepreneurial Experience: From my entrepreneurial experience, I’ve identified three pillars for success: team, execution speed, and customer focus. 

  • Working with a trustworthy team, such as co-founding companies with my brother, provides a foundation of trust and effective division of tasks. 
  • Speed in execution is crucial; the mantra “just ship” underscores the importance of putting products into customers’ hands. 
  • Asking the right financial questions — like what customers are willing to pay for — helps in aligning the business model with market demands.

To streamline these aspects, I utilize a funnel that helps in answering critical questions like “Who are we selling to?” “How do we guide people through the sales funnel?” and “How do we continuously add value for our early adopters?” 

By focusing on these areas, startups can achieve higher velocity, greater volume, and more consistent results.

3 ways to differentiate AI companies (Design, Data, & Distribution): In the realm of AI product development, three critical factors come to the forefront: design, data, and distribution. Design focuses on the user experience, asking key questions like whether the product employs a chat interface or another type of interaction to facilitate communication with the AI. On the data front, the question isn’t just about starting with a unique data asset but also how the AI manages, leverages, and even creates new data, thereby adding value to the system.  

Lastly, distribution looks at how this particular AI can uniquely engage and expand its customer base, exploring innovative ways to reach and resonate with the target demographic. Each of these elements plays a pivotal role in the success and scalability of AI-driven solutions.

Team Building For Better Remote Work: When thinking about how team building has shifted, post-pandemic, I’ve participated in work-from-home since 2009 starting with Gist. We used to run a two week-long sprint schedule and every other Wednesday we would spend our time talking about the metrics of the business, what’s working and what’s not. And then the opposite Wednesday was sprint planning. So the first Thursday I got my brain around my sprint and committed to getting it done. 

The sprint process I just described provides scaffolding for remote work. When you think about communication styles and the tooling, written culture versus verbal culture, everyone knows there’s a document and there’s a sprint plan. Everyone can read it and edit at the same time or they can do it asynchronously. That is scaffolding for better remote work.

The Future of Work: We are all at this point in time and technology where we’re all having to experience a whole new way of thinking about building companies. We are all going to have to be very open to learning a lot of new things in a way that sometimes makes us uncomfortable with good learning often does.

Diverse overlaps into learning because there’s going to be a whole set of skills that we didn’t think about combining, that’s going to become very important in the near future. Maybe we have to think about the fact that everyone around the world is building products in different ways for global audiences. Therefore diversity in background, understanding and appreciation is very important. 

AI Projects at Pioneer Square Labs

  • An AI copilot for hardware product development that handles requirements, prioritization, and supplier decisions. By describing the desired product, it automatically generates and evolves specifications while optimizing for factors like cost and battery life.
  • A licensing assistant that detects unauthorized use of copyrighted material like music or videos, then notifies the owner. This protects intellectual property as AI synthesis of media becomes more advanced.
  • A self-learning AI that identifies and writes skills it needs to complete tasks described in plain English. It builds its capabilities over time, allowing it to take on more complex assignments. Initial applications are focused on sales productivity tools.
  • An AI software developer that can write code, tests, and documentation like an intern, while integrating with systems like GitHub. It takes direction to complete programming tasks efficiently.

Listen to the full episode of Shift AI with T.A. McCann here.

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