I Have Some Questions…
I Have Some Questions...
Podcast Description
What if leadership wasn’t about having the answers—but about asking better questions?On "I Have Some Questions…", Erik Berglund – a founder, coach, and Speechcraft evangelist – dives into the conversations that high performers aren’t having enough. This isn’t your typical leadership podcast. It’s a tactical deep-dive into the soft skills that actually drive results: the hard-to-nail moments of accountability, the awkward feedback loops, and the language that turns good leaders into great ones.Each week, Erik explores a question that has shaped his own journey. Expect raw, unpolished curiosity. Expect conversations with bold thinkers, rising leaders, and practitioners who are tired of recycled advice and ready to talk about what really works. Expect episodes that get under the hood of how real change happens: through what we say, how we say it, and how often we practice it.This show is for driven managers, emerging execs, and anyone who knows that real growth comes from curiosity rather than charisma.Subscribe if you’re ready to stop winging it and start leading with intention.
Podcast Insights
Content Themes
The podcast focuses on critical leadership skills, self-awareness, and accountability, with episodes diving into topics like how to lead teams in an AI-enhanced environment and the significance of asking better questions for personal and organizational growth.
Most people know the headline of a leader’s story. Few know the path it took to get there. This podcast goes beyond titles, book launches and business wins, to explore the lived journey behind the thought leader.
Through deep, unhurried conversations, we uncover the moments that shaped them—the doubts, pivots, convictions, and quiet breakthroughs that built their body of work.
Each episode features authors, coaches, executives, and bold thinkers who have forged their own path. Instead of rehearsed talking points, they’re invited into a space where thoughtful questions unlock something more human. The result is a layered conversation that reveals not just what they preach, but how they became the kind of person who can teach it.
Because we believe the best stories aren’t always told—they’re revealed. And when brilliant people are given the right questions and the room to answer them fully, what emerges is insight you can feel, frameworks you can apply, and a deeper understanding of what it truly takes to lead, create, and contribute at a meaningful level.
Justin Coats breaks down the idea of “super apps” for AI and what that really means for corporate adoption, change management, security, and tokenomics.
🧭 Conversation Highlights
- Justin defines super apps as AI workspaces that combine model access, agents, and computer or browser use in one interface.
- Erik pushes on the human side of adoption and asks whether waiting for the tech to mature actually reduces the real cost.
- They discuss how change management needs education, executive buy-in, and AI champion teams that represent more than just IT.
- Justin explains context windows (AI attention span) and then tokenomics: tokens measure workload, credits measure billing, and measurement is still messy.
💡 Key Takeaways
- Super apps are less about a new tool and more about consolidating how work happens, which forces a new way to interact with your systems.
- Waiting for “fully baked” AI does not remove the human adoption problem. Humans are slower, so competitors build advantage while you stand by.
- Good adoption looks like: leadership using it, education for everyone, and an AI champion group embedded across functions.
- Tokenomics and context windows are becoming operational concerns. If you cannot measure and manage usage, costs and performance turn into guesswork.
❓ Questions That Mattered
- Will adopting super apps get easier from a change management standpoint, or will it keep demanding constant iteration from teams?
- How should companies think about their tech stack being partially commoditized and what pushback comes from the original tools?
- If a super app depends on a small number of operators, what happens when key people leave and the wiring breaks?
- What does it mean when an AI says the chat is too long, and how should teams manage context and summarize threads?
🗣️ Notable Quotes
- “Humans need their hand held until they don't.”
- “Context window is your AI's attention span.”
- “Tokens measure the underlying AI model's workload. Credits are the product's own usage and billing currency.”
🔗 Links & Resources
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