Join Nolan Fortman and Logan Kilpatrick for a deep dive into the story of Bolt.new (Stackblitz) with founder and CEO Eric Simons. We talk about Bolt.new as the overnight success 7 years in the making, why vibe coding is here to stay, scaling from $0 to $20M to now $40M ARR, the the future of software creation.

Get started vibe coding: https://bolt.new/

Find Eric and Logan on X / Twitter: https://x.com/EricSimons + https://x.com/OfficialLoganK

Learn more about Around the Prompt: https://www.aroundtheprompt.com/

Join Nolan Fortman and Logan Kilpatrick for a conversation about the future of home robotics with Matic CEO Mehul Nariyawala. We dive deep into the challenges of on-device AI, scaling robot production in America, where humanoids are going, and more!

Join Nolan Fortman and Logan Kilpatrick for a deep conversation with Dwarkesh Patel, host of the Dwarkesh podcast, and one of the 2024 TIME most influential people in AI. We chat about how the world is going to change with AI in the next 2 years, infinite AI dimensionality, creating content for the AI world, human authenticity in the age of AI, and learning with AI!

Join Nolan Fortman and Logan Kilpatrick for a deep dive on the world of coding with GitHub CEO Thomas Dohmke. We chat about: - Personal software creation using AI - Open source in the age of AI - AI enabling coding changing how developers work and much more! Thomas is leading the charge for one of the world's most important developer companies. I hope you enjoy the conversation as much as we did!

Listen to a conversation with Alex Atallah, the CEO of OpenRouter, along with Nolan Fortman and Logan Kilpatrick. The conversation covers:

• The start of OpenRouter
• Open vs Closed models
• Why AI usage is the ultimate metric for us
• How to compare different models in production
• How to rank models

And much more!

Join Nolan Fortman and Logan Kilpatrick as they dive into an unfiltered conversation with Chamath Palihapitiya, covering: open source AI, the massive compute buildout, where the AI value creation is, how to build for the age of AI, Deepseek, and much more!

In this conversation, Simon Willison discusses the intersection of AI, Open Source, and journalism, emphasizing the importance of tools like Dataset in enhancing data journalism. He reflects on his journey from developing Django to his current work with AI, highlighting the role of open source in software development. Willison shares insights on how AI can augment human capabilities rather than replace them, and he expresses concerns about the future of AI, particularly regarding AGI. The discussion also touches on the evolving landscape of programming and the need for better onboarding processes for new developers.

Join Logan Kilpatrick and Nolan Fortman for a discussion with Shreya Rajpal that covers the inception and evolution of Guardrails, a tool designed to enhance reliability in AI applications. She emphasizes the importance of AI validation, the challenges of moving from proof of concept to production, and the organizational buy-in required for implementing such tools. The discussion also touches on the role of open source in AI development, the competitive advantages it provides, and the parallels between self-driving technology and AI systems. Shreya shares insights on real-world use cases, the introduction of Guardrail Server, and the future of AI regulation, highlighting the need for benchmarks and the importance of understanding the risks associated with generative AI. A few of our favorite

Sound Bites: "Guardrails started as a form of building reliability." "AI development is very much like traditional software development." "The long tail is brutal in machine learning."

Join Logan and Nolan in a deep dive into the world of AI coding with Quinn Slack, the CEO of Sourcegraph. Sourcegraph was founded in 2013 with the goal of solving the problem of code search. The founders, who had experience working with massive code bases, wanted to create a code search tool similar to Google for code. They started by building code search as their first product and made mistakes along the way, but ultimately built a product that many developers love. Over time, Sourcegraph expanded to include intelligent automation and AI capabilities. They believe that the future of code search and AI in coding is a unified platform that combines search, chat, and AI capabilities. The conversation explores the potential impact of AI on coding and software development. Quinn Slack discusses how AI can empower non-technical individuals to code and create software solutions. He emphasizes the importance of making AI tools work manually before introducing automation. The conversation also touches on the challenges of building AI interfaces and the need for context integration from various tools. Quinn expresses his hope for the continued development of local models and competition in the AI space.

Highlights: "We wanted to have some kind of code search like Google for code." "Search and AI chat really blur together. From the user's perspective, what they want is a box that they can type shit into and it solves their problems." "GitHub has the world's code. Why would we want to compete against GitHub? And I think now they're actually seeing a bunch of sort of co-pilot level competitors." "I think you're going to see that increase... we could have everyone coding or at least conjuring up code." "You got to make it work manually first before you introduce any kind of magic." "It is very likely that we'll end up with like many... one person billion dollar companies."

Andrew Mayne shares his non-traditional journey into AI, from being a magician and illusionist to becoming a science communicator at OpenAI. He discusses his early experiences with AI as a child, his interest in robotics and AI, and his fascination with chatbots. Andrew also talks about his experience using AI to deceive great white sharks and how it led him to explore the capabilities of text models like GPT-2 and GPT-3. He emphasizes the importance of prompt engineering and the need to carefully craft prompts to get desired outputs from the models. Andrew Mayne emphasizes the importance of having a clear idea of the desired output and breaking down complex tasks into manageable steps. He shares his experience in teaching magic tricks and how it helped him in prompt engineering. Mayne discusses the evolution of prompt engineering and the challenges and hype surrounding it. He also talks about his personal tech stack and the tools he uses for writing, coding, and research. Mayne expresses his excitement about the accessibility of AI models and the potential impact of AI in education. He also discusses his concerns about deep fakes and the need for trust and authentication in communication.