Explore how AI could transform businesses without needing the latest models. The hosts argue existing technology is powerful enough to drive big changes today. They compare AI’s potential to farming mechanization, showing how tasks can be broken down into manageable parts. The discussion challenges common misconceptions about automation, advocating for immediate action instead of waiting for advanced AGI. They also touch on the shift to e-commerce and the essential adaptation businesses must embrace to thrive.
01:15:55
forum Ask episode
web_stories AI Snips
view_agenda Chapters
auto_awesome Transcript
info_circle Episode notes
question_answer ANECDOTE
Agriculture Mechanization Anecdote
Mechanization shifted farming in the U.S. from 10 workers per person to 1 farmer feeding 100+.
Jeremy Clarkson's farming show highlights how technology democratizes labor efficiency.
insights INSIGHT
Augmentation vs Agentic Insight
AI augmentation helps humans do existing jobs faster but is limited.
Rewiring businesses on AI-native processes unlocks exponential productivity improvements.
insights INSIGHT
Task Decomposition Insight
Breaking jobs into subatomic tasks enables many simple AI agents to excel.
It’s easier to automate many tiny tasks than one complex role.
Get the Snipd Podcast app to discover more snips from this episode
The Good Stuff, with Pete and Andy - Episode 5: Billy Big Models
Hosts: Pete and Andy (recording at City Beach, Perth)
Episode Overview: Pete and Andy challenge the belief that more advanced AI models are needed for business transformation, arguing existing models are already sufficient to achieve dramatic cost reductions. They explore frameworks for AI implementation and why businesses should act now rather than waiting for future developments.
Agriculture Mechanization as an AI Parallel (03:40-06:42)
Before mechanization: 10 farm workers needed to feed 1 person; after: 1 farmer feeds 100+
Similar dramatic workforce changes could occur in knowledge sectors with AI
The "Billy Big Models" Concept (11:06-15:10)
Central question: Do we need more advanced AI models for business transformation?
Pete argues we don't need models better than what existed 9-12 months ago
Challenging the industry narrative focused on larger models and AGI
Augmentation vs. Agentic Approaches (18:12-22:00)
Augmentation: Using AI tools to enhance existing human jobs (current focus)
Agentic: Completely rewiring business processes on an "AI native" standard
The distinction between "assist" vs. "automate" approaches
Task Decomposition as the Key (23:22-25:55)
Breaking down jobs into "subatomic" tasks is crucial
Each agent only needs to do one small task well, not an entire job
100 simple agents is exponentially easier than creating one complex agent
Recent key advancements weren't bigger models but new techniques:
Multi-agent architectures mirroring how teams of people approach problems.
Notable Quotes:
"If you're sat around waiting for AGI and AGI takes 10 years, and right now I can take 80% of the cost out of a business line, I will crush you in the market."
"What would this process look like if I now had unlimited access to intelligence?"
"Agency is going to be the new IQ. That's the standard for harvesting opportunity."