StoryTime: Generate Children's Stories with AI | Mike Cavaliere
Published:
Mike Cavaliere discusses building an AI-powered children's story generator app called StoryTime, exploring prompt engineering techniques and AI development challenges.
Episode Summary
In this episode, Anthony Campolo interviews Mike Cavaliere about his AI-powered children’s story generator app called StoryTime. Mike explains how he built the app using OpenAI’s GPT model for text generation and Stable Diffusion for image creation. They discuss prompt engineering techniques, the challenges of working with different AI models, and potential future features for the app. The conversation covers various AI tools and frameworks, including custom GPTs and prompt optimization strategies. Mike shares insights into the development process, pricing considerations for AI-powered apps, and the growing importance of AI skills in the tech industry. The episode provides a practical look at building AI applications and the current state of AI development tools.
Chapters
00:00 - Introduction and Background
This chapter introduces Mike Cavaliere and provides context for the discussion. Mike talks about his 20-year career as a software engineer, mentioning his book on full-stack Jamstack development. The conversation touches on the evolution of web development frameworks, drawing parallels between modern JavaScript frameworks and Ruby on Rails. This sets the stage for discussing Mike’s current project, a storybook app powered by AI.
02:56 - Exploring AI and StoryTime App
Mike introduces his AI-powered app, StoryTime, which generates children’s stories. He explains his motivation for building the app, describing how he used ChatGPT to create stories for his own children and wanted to simplify the process. The chapter covers the basic functionality of StoryTime, including how users select age groups and topics to generate customized stories. Mike also discusses the integration of image generation using Stable Diffusion, highlighting the differences in prompting between text and image models.
09:00 - Technical Details and Prompt Engineering
This chapter covers the technical aspects of StoryTime. Mike explains the tech stack, which includes Next.js, the Vercel AI SDK, and Prisma ORM. He shares insights into prompt engineering, showing the template he uses to generate stories. The discussion covers various prompt engineering techniques, including the use of expert personas and the debate around threatening language in prompts. Mike and Anthony explore different AI tools and custom instructions sets like ChatGPTAutoExpert and Grimoire, demonstrating their use in improving AI outputs.
23:48 - AI App Development Challenges and Future Plans
The conversation shifts to the challenges of AI app development, including managing costs, implementing user authentication, and handling content moderation. Mike discusses his plans for future features, such as allowing users to explore existing stories, implementing a rating system, and potentially generating e-books. They also touch on the importance of AI skills in the job market and how understanding AI can give developers an edge. The chapter concludes with a discussion on the unique possibilities AI opens up for app development and the potential business models for AI-powered services.
42:52 - Reflections on AI in Development and Conclusion
In the final chapter, Mike and Anthony reflect on the broader implications of AI in software development. They discuss how AI tools can enhance productivity and enable the creation of apps that were previously impractical. The conversation touches on the balance between using AI in personal workflows and integrating it into products. They also consider the potential for AI to change job market dynamics in tech. The episode concludes with Mike inviting feedback on StoryTime and providing his contact information for viewers interested in learning more or trying out the app.