Building hyper-personalized AI Apps..

I’m a PowerPoint jockey and a very rusty programmer. Yet, over the weekend, I built something that had been an idea for years.

I write constantly – notes, emails, journals – using writing to process thoughts and help calm the chaos in my head. But I couldn’t find a journaling tool that worked exactly as I wanted: private, organized, tagged, and summarized with my specific quirks.

So, I built a custom workflow using Claude and MCP. I dump thoughts into Claude via text or voice. It offers prompts for elaboration, generates metadata and tags, creates markdown files, and pushes everything to my private GitHub repo. Claude even helped write a GitHub action to maintain an index whenever I created a new entry.

Extremely nerdy? Absolutely. Could I have used an off-the-shelf app? Probably. But building something that behaved *exactly* how I wanted is why LLMs excite me.

This represents something bigger than one nerdy weekend project. What required technical knowledge today will soon be accessible to everyone. What took me a weekend of GitHub repos and MCP servers will quickly be declarative workflows in mainstream tools.

We’ve spent decades accepting software uniformity. SaaS companies optimize for the broadest user base, creating generic interfaces. We adapt our workflows to software constraints rather than software adapting to us.

LLMs could flip this script. Instead of adapting ourselves to software, software could adapt to us. Hyper-personalized workflows, bizarre interfaces, and tools that match how we think and work.

Remember when personal computers were personal? Before everything became a web app that looked exactly like every other web app? We might be heading back there, but everyone gets to be the programmer this time.

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Screen grab is from the metadata of an early draft of this post. You can find a link to the project prompt in the comments.