Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new.
This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.
Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new.
This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.
This episode of "Techsplainers" introduces listeners to the concept of agentic architecture, a framework used for structuring AI agents to automate complex tasks. The podcast explains that agentic architecture is crucial for creating AI agents capable of autonomous decision-making and adapting to dynamic environments. It delves into the four core factors of agency: intentionality (planning), forethought, self-reactiveness, and self-reflectiveness. These four factors underpin AI agents' autonomy. The discussion also contrasts agentic and non-agentic architectures, highlighting the advantages of agentic architectures in supporting agentic behavior in AI agents. The podcast further breaks down different types of agentic architectures – single-agent, multi-agent, and hybrid – detailing their structures, strengths, weaknesses, and best use cases. Finally, it covers three types of agentic frameworks—reactive, deliberative, and cognitive—concluding with a detailed explanation of BDI architectures, a model for rational decision-making in intelligent agents.
Find more information at https://www.ibm.com/think/podcasts/techsplainers
Narrated by Alice Gomstyn