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.
Timestamps
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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