Everyone's slapping 'agentic' on their AI products, but what does that even mean? Anne Jenkins, Vice President of Solution Architecture at Teneo, helps us separate substance from buzzwords.

In this episode, Anne shares her expertise on agentic AI and the evolution of conversational AI technologies. We explore what truly makes an AI ‘agentic’ versus the marketing hype all over your LinkedIn feed and beyond. Anne explains why Teneo's hybrid approach, combining traditional NLU capabilities with large language models, creates more reliable, cost-effective, and latency-friendly solutions than pure LLM implementations.

We also discuss the challenges organisations face when adopting AI solutions, including the misconception that LLMs alone can solve all problems without proper conversation design or business rule integration. Anne shares valuable insights on how companies can prepare for AI adoption through education, competitive pilots, and architectural considerations.

We touch on many best practices when it comes to implementation, with Anne emphasising the importance of proper context engineering, state management, and dynamic prompting.

Chapters

00:00 - Meet Anne Jenkins

05:01 - AI is now a boardroom conversation

06:48 – OpenAI’s agentic AI platform

08:48 – What is an AI agent?

21:38 – The hybrid AI model or end-to-end LLMs

26:49 – AI in debt collection

34:55 – How Teneo helps implement agentic AI

42:39 – Context engineering

47:19 – State management and LLMs

55:40 – How Teneo designs AI experiences

01:00:32 – Demo – teaching Teneo something new

01:10:26 – How businesses should adopt AI

01:16:44 – What sets Teneo apart

Show notes

Check out Teneo

Follow Anne Jenkins on LinkedIn

Read Kane’s article - What agentic AI actually is: a deeply researched and definitive explanation

Follow Kane Simms on LinkedIn

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