
Lucas Greenwell
\# Lucas Greenwell
Lucas Greenwell is a software engineer and product leader with experience building technology across the health, education, and defense sectors. He is known for helping organizations understand how AI can be applied in practical, high-impact ways, translating fast-moving technological advancements into clear strategies and actionable solutions.
Having followed the evolution of artificial intelligence for years, Lucas has developed a strong understanding of both the technical foundations of AI systems and the realities of deploying them within industry environments. His work spans software engineering, product management, and emerging technology strategy, giving him a well-rounded perspective on how businesses can successfully adopt and integrate AI tools.
Lucas works closely with teams and decision-makers to evaluate what is realistically possible with today's AI capabilities, identify high-value use cases, and navigate the rapidly changing landscape of AI products and platforms. He is particularly focused on helping people move beyond hype and confusion to make informed decisions about implementation, workflow improvements, and future opportunities.
Known for his approachable communication style and practical mindset, Lucas helps bridge the gap between technical innovation and real-world business needs. Whether advising on AI adoption, product direction, or emerging trends, he brings a balanced perspective grounded in hands-on industry experience and a deep curiosity about where the technology is headed next.
- Session rate
- $750 per 1-hour session
Expert profile
Software engineer and PM bridging AI to health, ed-tech, and defense
What this session is built for
Bring a concrete AI workflow, decision, or implementation challenge. This session is designed for focused diagnosis, practical options, and next steps you can use immediately.
Book sessionSign in to bookExample questions you might ask
- How do we avoid building AI workflows that break when models change?
- What is the right way to handle AI-driven decisions in regulated or high-stakes contexts?
- How do we evaluate AI vendors when our requirements are still emerging?
- Where should we start with a 90-day AI pilot in a core business function?