Mastering Agentic AI: Agents vs. Workflows Explained

In this thrilling episode of Real Terms with AI Season 2 by Google Cloud Tech, we dive headfirst into the fascinating world of AI, leaving no byte unturned. Last season, we explored the very building blocks of generative AI, data protection, and the intricate dance of function calling. But hold onto your hats, this season is all about agentic concepts, with a twist of different video formats to keep you on the edge of your seat. The team sets the stage by unraveling the enigma of agents and agentic behaviors, shedding light on the crucial role of non-determinism in tasks.

As the discussion unfolds, we learn that agentic behaviors are the secret sauce that blends tasks seamlessly to achieve specific outcomes, a stark departure from the more predictable nature of deterministic workflows. AI agents take center stage, showcasing their ability to autonomously make decisions to reach predefined goals, while workflows play it safe with a more calculated approach. From processing invoices to creating websites, examples abound to illustrate the power of agentic workflows and AI agents in action.

The team delves deeper into the essence of agentic behavior, drawing parallels to human interactions and decision-making processes. The million-dollar question arises: when should one opt for an agentic workflow over creating a full-fledged AI agent? The answer lies in the complexity of the task at hand and the level of autonomy desired. By weighing the risks and rewards, one can navigate the fine line between harnessing the power of AI agents and sticking to tried-and-true workflows. With a promise to share practical code snippets and architectural examples on GitHub, viewers are invited to embark on a thrilling journey of exploration into the realm of agents and agentic workflows.

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