How do you move beyond AI hype and actually build systems that deliver real business impact?

In this episode of the Orlando Insights Podcast, we sit down with Lena Hall, Founder & CEO of Droid AI, to explore Context Engineering — the missing layer between large language models and real-world enterprise systems.

Lena is an expert in practical AI adoption, data engineering, cloud, and pragmatic architecture. With 15+ years of deeply technical experience, she has led large-scale data, analytics, machine learning, and cloud initiatives across global organizations.

Before founding Droid AI, Lena served as:

• Head of Developer Experience, North America at Amazon Web Services

• Lead of Big Data Developer Relations at Microsoft

Today, through Droid AI, she helps businesses get real results from AI — defining Data + AI strategies, integrating LLMs into complex enterprise systems, connecting AI solutions with business tools, and optimizing outcomes through proven architecture.

In this conversation, we cover:
✔️ What Context Engineering actually means
✔️ Why most AI implementations fail
✔️ How to integrate LLMs with enterprise data systems
✔️ Designing AI architectures that scale
✔️ Practical lessons from AWS and Microsoft
✔️ Building AI that works in production — not just demos

If you're a data engineer, AI architect, CTO, or business leader looking to move from experimentation to production-grade AI, this episode is for you.

In this episode of the Orlando Insights Podcast, I sit down with Natalia Kuklova, a senior data science and AI leader with over a decade of experience building enterprise analytics, machine learning, and decision systems inside highly regulated industries.

Natalia has led large-scale initiatives across risk, product analytics, experimentation, and enterprise AI strategy. She works directly with executive teams to move organizations beyond dashboards and models — and toward measurable, durable business outcomes.

We explore:

• What Decision Intelligence actually means in practice
• Why most AI strategies stall at the “model” stage
• How leaders can connect data science to real business decisions
• The practical framework of Automate, Augment, Inform
• What regulated enterprises must consider when scaling AI
• How governance and innovation can coexist

Natalia is also a contributor to the Forbes Technology Council, where she writes about AI strategy, decision intelligence, and the future of work.

If you’re a data leader, executive, AI strategist, or builder looking to connect analytics to real decisions — this episode is for you.

AI is no longer a future concept—it’s embedded in how people work every day. Ivonne Kinser breaks down what leaders must understand to navigate AI’s real impact on teams, decisions, and culture.