387: Your API Documentation is Not For Developers Anymore

Hey. It's Arvid, and this is the Bootstrap Founder. Today, we're gonna talk about something fascinating that happened to me this week. Something that made me completely rethink how we as software founders should approach API documentation in this wild new era of AI powered development. And this is not just about technology. It's about expectations. This episode is sponsored by paddle.com. They are the merchant of record that has been responsible for allowing me to reach profitability just a few weeks ago. There truly are more, m o r, merchant of record, because their product allowed me to focus on building my own product that people actually wanna pay money for and enough to actually make it profitable too. And that's why Paddle does so much more for you. They deal with taxes and reaching out to customers when their payments fail. They charge people in their local currency if they want it and need it. All these things that I don't need to focus on so I can really be present for my customers and their needs. It's really amazing. Check out paddle.com to learn more. Now I had this really interesting experience with a customer of PodScan recently. They reached out saying that they were having trouble with integration into our API and this is not unusual. Sometimes we get these requests and I help them out and check out what's going on but what happened next with this person completely changed my perspective. I did what I usually do. I recorded a quick Loom video and I walked them through the basics of how to create an API key and make that first request to show that it's working and then how to search for a podcast and get its episode listings. Just a really simple five minute guide to get them started and connect with me as a founder. Their response? They said, when I watched it, something clicked. They made me happy. But then came the part that surprised me. You know, I'm not technical at all. That's what they said. I'm just using Cloud and ChatGPT and Replit to build some integrations. And then they explained to me what they were actually building. So they were taking all these podcast episodes, the backlogs, the transcripts, feeding it into a what was it? Like a vector database to then run an internal LLM on top of and ask questions about podcasts in their industry and what things should happen and what things they shouldn't do. Like, mining the data in these public conversations from many many dozens of podcasts to all feed into one database and have an AI filter out information. And that stopped me in my tracks. Here was somebody with self proclaimed no technical background using AI tools to build what turned out to be a super sophisticated system. Right? Download episodes from an API, put them into a database, build this LLM to generate insights and verify information. That's quite …