In this podcast, Noz and Amir Faizpour talk about how businesses can effectively implement AI beyond basic tools like ChatGPT.
Amir, who runs Aggregate Intellect, explains why companies might need more sophisticated AI solutions that integrate with their existing business systems rather than using standalone AI tools.
The conversation focuses on “AI agents” – systems that can independently use tools and execute complex tasks – and the importance of separating language models from actual business data to ensure accuracy and reliability.
A key takeaway is that instead of relying on one large AI model for everything, businesses might benefit more from using multiple specialised models for different tasks, much like how human workflows operate.
 
What you’ll learn


Understanding why businesses might need solutions beyond standard AI tools like ChatGPT and Microsoft Copilot
The importance of integrating AI with existing business systems rather than using siloed solutions
How “agentic” AI systems work and their three key components: tool usage, memory, and planning capabilities
The value of separating language models from actual business data and knowledge
Why smaller, specialized AI models can sometimes be more effective than larger, general-purpose ones
The role of human oversight and knowledge in AI systems
How to evaluate and verify AI-generated content for accuracy and specificity.


 

“I have these nine commandments that I usually talk about when it comes to generative AI and one of them, which I think is the most important one, is the separating the knowledge, the data and the linguistic interface.”
“One of my biggest design principles is that the architecture of, or the anatomy, as you’re saying of the system, you’re building has to replicate the human workflow.” – Amir Feizpour

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