Deepseek

In an earlier post I turned hundreds of hours of recorded Bible teaching into text. AI transcription is good, but not perfect — it mishears words, especially names and rare terms. So the obvious next step was to ask a smart language model to clean up the mistakes. These models have basically read the whole Bible, so I figured fixing a few scripture typos would be easy for them. It wasn’t. And the way it failed taught me something that goes well beyond transcripts — to anyone using AI to correct text against a trusted source. ...

I save every prompt I type when I’m building something. I started doing it long before this blog, for a dull reason: I forget what I did, and the log helps me pick things back up. Going back through one of those logs recently, I found a session worth sharing. It’s closer to what building with AI actually feels like than a clean demo is. The demos show you the good moment. You describe what you want, and a working app appears. That does happen, and it’s real. But most of the work isn’t that. A lot of it is more like this: a task that looked easy, and an AI that got it wrong a few times before we sorted it out. ...