Marcus Fletcher

When a free user complains, it's easy to ignore. But when a long time paid customer drop a harsh cancellation note or leaves a blunt review, it hits differently even if the overall churn rate is low.

Early on, every churned user feels like a personal failure of your product vision.

As you scale, do you naturally build a thick skin toward churn feedback, or do you just learn to separate product noise from signal?

Every shortcut removes a bit of friction, and some of that friction was doing a job. I'd like to hear which parts of your workflow you handed over and which you took back.

When a tool makes something easy, you rarely notice what the difficulty used to give you. Writing a first draft by hand forced me to decide what I actually thought. Reading user feedback line by line made me notice phrasing that a summary flattens. Writing a spec from scratch was slow, and the slowness was where I found the holes.

As search becomes a core part of AI workflows, things like data coverage, QPS, and cost start to matter, especially when your agent needs to search repeatedly across different sources.

That's why we've launched AnySearch Pro , built for developers and teams running AI agents and search-heavy applications.