How to Build an AI Content Research Engine: a Claude + Reddit Case Study

Sun, 17 May 2026 00:00:00 +0000

TL;DR

For most solo builders and small teams, content research is the bottleneck, not writing.

A weekly Collect → Cluster → Score → Synthesize pipeline turns real customer conversations into a ranked list of topics you can scan over coffee.

The pattern works for any niche where your audience talks publicly somewhere: Reddit, Indie Hackers, niche Discords, forums.

The scoring prompt is where most of the leverage lives. Treat it as a markdown file you keep rewriting until its top three match the ones you’d pick by hand.

As I was building out Storkly, I was pretty confident in getting us up and running to an MVP/Soft Launch phase. I had enough experience with software and web development and while there was (and still is) a lot to learn, getting from zero to one wasn’t my primary worry. It was, “how do I drive people to this product?”. I knew we needed to create content to get the word out there but I always found myself frozen at what to write about and _what to post about.

Why we're building Storkly

Wed, 13 May 2026 09:00:00 -0400

We were waiting on the call from the hospital for our scheduled induction. Originally we were supposed to come in Friday afternoon. The call didn’t come until Saturday evening. Almost twenty-four hours of waiting, waiting, waiting — and a constant stream of texts, calls, and “any update?” messages from family and friends who loved us and just wanted to know.

Somewhere around hour fifteen, half-laughing, half-broken, we said it out loud: there has to be a better way to do this.

chasrobinson.com

How to Build an AI Content Research Engine: a Claude + Reddit Case Study

Why we're building Storkly