Autonomy is where things start to feel different. It’s also where things start to feel real. Because autonomy is what elevates AI from being reactive — waiting for instructions, following your every click — into something that can operate on its own, on your behalf, within reason. In agentic systems, autonomy means the ability to take initiative. The agent decides what to do next. It understands goals, prioritizes actions, allocates resources, and handles exceptions — all without waiting for a nudge. That doesn’t mean it’s unbounded. It operates within defined limits, like organizational rules, user preferences, or legal guardrails. But within those lines, it has freedom to move. This isn’t about removing humans. It’s about removing bottlenecks. Think of autonomous systems in supply chain management. An AI agent could monitor global…

🧠 M – Memory: The Context That Makes AI Human-like Memory isn't just remembering the last message in a chat—it’s about continuity, personalization, and the ability to evolve. Short-term memory (aka context window) is what lets AI keep up with you in real time. Models like Gemini have taken this far, holding millions of tokens at once. It’s like having a photographic memory for the current moment. Helpful? Yes. Sufficient? Not even close. Long-term memory is where the magic of agentic AI begins. It allows an agent to remember you, your goals, your tone, your history—and to adapt accordingly. It can draw on past conversations, stored knowledge, and personal preferences. That’s what makes it more than a chatbot. That’s what makes it a partner. Effective long-term memory involves more than just…

The ongoing evolution of Artificial Intelligence presents both significant opportunities and new complexities for the business world. We've moved beyond AI systems limited to narrow tasks and are now encountering the more sophisticated potential of Agentic AI – systems designed to understand broader goals, operate with a degree of independence, learn from interactions, and execute tasks on our behalf. As these advanced AI capabilities become more prevalent, the challenge for curious businesspeople is to look past the often-inflated rhetoric and gain a clear, practical understanding of what these systems can genuinely offer. How can we effectively evaluate their potential, differentiate true innovation from transient trends, and ultimately determine how Agentic AI can bring tangible value to our operations and strategies? To address this need for clarity, my book, Generative AI for…

Synthesis is more than summarization. It’s the AI equivalent of a detective assembling clues across scattered scenes. It means pulling threads from wildly different sources, weaving them into something coherent, insightful, and even novel. A truly synthetic AI doesn’t just know stuff — it knows how to combine things in ways that matter. This capability enables an agent to integrate information across domains, formats, and timelines — something humans often struggle with at scale. It connects concepts that might appear unrelated on the surface, linking technical documentation with market trends or financial reports with behavioral cues. From these fragmented inputs, synthesis allows agents to build coherent narratives that help people make sense of complex realities. It also gives rise to useful explanations — not just lists of facts, but interpretations. Synthesizing…