Bryan Helmig on building Zapier

Bryan Helmig on building Zapier

AI lets us build automations which we could never have built through traditional programming. Because AI is able to process unstructured information in a common sense way, a whole new class of tasks can now be automated for the first time. AI is also empowering; because the main interface to AI is natural language, anyone can build automations without any programming experience.   Bryan Helmig, co-founder and CTO of Zapier, joins Anton to discuss how Zapier is using AI to automate workflows for businesses. Bryan shares how Zapier is making AI accessible to non-technical users and how they are building tools to help users iterate on their AI models. They also discuss the challenges of building AI tools for non-technical users and how to collect and evaluate feedback on AI models.   Released June 10, 2024, Recorded May 20, 2024

Rahul Sonwalkar on building Julius

Large language models are capable of capturing user intent in a common-sense way, and translating it into code. This new approach to software empowers many users who don't have the time or knowledge to write code themselves, allowing them to instead focus on the task at hand. Making sure that the translation is accurate is a challenge, requiring all-new tooling and techniques.   Rahul Sonwalkar, founder and CEO of Julius - the AI data scientist, joins Anton to discuss how they use large language models to write code, integrate LLM tool use, detect and mitigate errors, and how to quickly get started and rapidly iterate on an AI product. They also discuss how thinking about products in terms of 'GPT wrappers' kills creativity, and what kinds of experiments AI developers should be trying today.

Flo Crivello on building Lindy.AI

AI Agents are a new category of software, built on top of large language models (LLMs). While the potential applications are extremely varied, best practices for building practical, robust AI agents are still being worked out.   Florian Crivello, founder and CEO of Lindy.ai joins Anton to discuss the practical challenges, strategies, and tools Lindy are ussing to build AI agents for. Flo shares insights on how to get LLMs to do what you want, how to detect and correct errors, and how to build trust with users. They also discuss the importance of experimentation, the future of AI agents, and the potential of AI in its most valuable and exciting domain: business process automation.   Released June 10, 2024, Recorded May 20, 2024