​Four Smart Ways To Implement An Agentic AI Framework

Innovation​Four Smart Ways To Implement An Agentic AI FrameworkByJay Bhatty,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 01, 2026, 10:45am EDTJay Bhatty is the CEO and founder of NatGasHub.com. gettyJust a few years ago, it would have seemed like sci-fi to imagine people using AI regularly at work. But here we are. ​LLM and GenAI are now commonly understood terms. A February 2026 Gallup survey found that "half of employed American adults say they use AI in their role at least a few times a year," and 28% say "they use it a few times a week or more," a jump from 46% and 26%, respectively, in Q4 2025. ​After its Next 2026 conference, Google Cloud published a piece saying, “the most significant trend is the transition from AI as a passive assistant to AI as an active part of the team, where specialized agents can orchestrate entire workflows.” ​This is the trend I’m seeing unfold in the energy sector. It’s clear to me that agentic AI is the future of work. My company started developing agentic AI software for clients in the oil and natural gas industry less than two years ago. Our goal is to build up to 10,000 AI agents for clients working across different natural gas pipelines in the next 12 months. From LLMs To AI Agents To Agentic AI FrameworksLLMs are quickly evolving into commodities, like any other type of technology. You may have loyalty to one brand over another, but each one deals with the same limitation: Its training data has a cutoff date.​If you ask an LLM, "What is tomorrow's weather looking like?" or "What are the average airline ticket prices to Boston next week?" it doesn't have that information. An LLM comes out of the box like a laptop, calibrated with an operating system trained on data with a certain release date.​You can take an LLM to the next l...