What is agentic AI? Inside Teneo’s real-world automation approach with Anne Jenkins

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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