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Join me, Nik (https://x.com/CoFoundersNik), as I interview Liz (https://x.com/leveragedupside) about the blistering pace of AI development and what it means for business owners right now.
We dive into the difference between traditional LLMs and the new reasoning models from OpenAI and Google, exploring how they go beyond just predicting the next word to actually thinking through problems using methods like chain of thought. Liz shares exciting updates like OpenAI's beefed-up API with a massive 1 million token context window and how this enables tackling complex business tasks, like analyzing thousands of contracts, which used to cost a fortune.
Plus, Liz gives us a look at Lindy, an automation tool designed for small businesses that makes building these powerful workflows much simpler than older tools like Zapier or Make.com, even demonstrating how it can automate lead enrichment.
Questions This Episode Answers:
What's the difference between traditional LLMs and the new AI reasoning models?
How are expanded context windows and AI memory changing what businesses can do with AI?
What does 'agentic AI' mean and how is it impacting automation?
How can businesses manage or QA outputs to deal with AI hallucinations?
What is Lindy and how can it help small businesses automate tasks more easily?
Enjoy the conversation!
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This week we covered:
00:00 Transforming Contract Review with AI
03:02 Understanding AI Models: Traditional vs. Reasoning
05:48 The Evolution of AI: From Analysis to Action
09:08 Agentic Behavior in AI: The Future of Decision Making
12:02 Memory and Context in AI: Enhancing User Experience
15:07 Practical Applications: Cost Savings and Efficiency
17:55 Ensuring Data Accuracy: Quality Assurance in AI Outputs
24:23 Exploring QA Systems with AI Models
27:41 Innovations in Automation: Introducing Lindy
30:35 Lead Enrichment: Automating Research for Business
35:59 Agentic Behavior vs. Automation: Understanding the Difference
40:33 Cost Considerations: Balancing Automation and Human Labor
