Handling limited context windows

Nik raises context-window limits; they introduce embeddings, RAG, and summarization as strategies to manage many transcripts.

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Join me, Nik (https://x.com/CoFoundersNik), as I interview Billy Howell (https://x.com/billyjhowell)! I'm so stoked to have Billy Howell back on the show! Billy is a prolific entrepreneur who has built over 60 apps with AI despite having no traditional tech background. His agency, Stupid Simple Apps, helps other entrepreneurs build their own custom AI apps.

This episode, I challenged Billy to teach me how to build a chatbot specifically for my podcast, so I can easily query my extensive archive of 200 transcripts. We also dive into practical small business use cases for chatbots, from HR and onboarding to sales processes and internal SOPs.

You'll hear us discuss the challenges of managing large data sets and context windows, exploring solutions like OpenAI's embeddings (also known as RAG) and document summarization. I even share a Google Apps Script I built to summarize my transcripts into a spreadsheet database, which we then use as the foundation for our chatbot.

Enjoy the conversation!

Questions This Episode Answers:

• How can a small business use AI chatbots for internal processes?

• What's a cost-effective way to build a custom AI chatbot?

• How do you handle large data sets, like 200 podcast transcripts, for an AI chatbot's context?

• What's a PRD and how does AI use it to build an app in minutes?

• How can you manage AI API costs and avoid unexpected token spikes?

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Love it or hate it, I'd love your feedback.

Please fill out this brief survey with your opinion or email me at nik@cofounders.com with your thoughts.

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