AI is entering a new phase.
In 2026, the conversation is no longer about basic automation or copilots - it’s about agentic AI: autonomous systems that reason, decide, and execute work across functions.

In this episode, I break down six defining AI trends for 2026, drawing from multiple industry reports and real-world adoption patterns. We explore why AI agents promise massive productivity gains - and why trust, data quality, and governance remain the biggest blockers to scale.

You’ll learn why context engineering matters more than prompt engineering, how successful teams combine AI autonomy with human oversight, and what practical strategies actually reduce legal, ethical, and operational risk.

If you’re building, leading, or investing in AI systems - this episode is about what works in practice, not what sounds good in demos.

This episode is for product leaders, engineers, and executives navigating real-world AI adoption in 2026.

How can AI remember without losing clarity or consistency?
In this episode, we explore Hindsight, a structured memory architecture that enables AI agents to retain facts, track experiences, reflect over time, and maintain a stable persona. We break down how it outperforms traditional retrieval methods and why structured, evidence-aware memory is key to building truly long-term AI agents.

How are AI agents actually being used in the real world?

In this episode of Intelligent Insights, we break down insights from Measuring Agents in Production (MAP) — a large study of how teams are deploying AI agents across industries like finance, healthcare, and science.

Instead of complex autonomy, most teams succeed with simple, controlled systems focused on productivity and reliability. We explore why human oversight still matters, why many teams build their own agents in-house, and what practical patterns are emerging in production today.

If you’re building or thinking about AI agents, this episode focuses on what works — not hype.