Episode 62: Practical AI at Work: How Execs and Developers Can Actually Use LLMs

Many leaders are trapped between chasing ambitious, ill-defined AI projects and the paralysis of not knowing where to start. Dr. Randall Olson argues that the real opportunity isn't in moonshots, but in the "trillions of dollars of business value" available right now. As co-founder of Wyrd Studios, he bridges the gap between data science, AI engineering, and executive strategy to deliver a practical framework for execution.

In this episode, Randy and Hugo lay out how to find and solve what might be considered "boring but valuable" problems, like an EdTech company automating 20% of its support tickets with a simple retrieval bot instead of a complex AI tutor. They discuss how to move incrementally along the "agentic spectrum" and why treating AI evaluation with the same rigor as software engineering is non-negotiable for building a disciplined, high-impact AI strategy.

They talk through:

• How a non-technical leader can prototype a complex insurance claim classifier using just photos and a ChatGPT subscription.
• The agentic spectrum: Why you should start by automating meeting summaries before attempting to build fully autonomous agents.
• The practical first step for any executive: Building a personal knowledge base with meeting transcripts and strategy docs to get tailored AI advice.
• Why treating AI evaluation with the same rigor as unit testing is essential for shipping reliable products.
• The organizational shift required to unlock long-term AI gains, even if it means a short-term productivity dip.

LINKS

• Randy on LinkedIn
• Wyrd Studios
• Stop Building AI Agents
• Upcoming Events on Luma
• Watch the podcast video on YouTube

🎓 Learn more:

• In Hugo's course: Building AI Applications for Data Scientists and Software Engineers — https://maven.com/hugo-stefan/building-llm-apps-ds-and-swe-from-first-principles?promoCode=AI20

Next cohort starts November 3: come build with us!