I've been thinking a lot about what separates AI products that people actually stick with from those they try once and forget. The pattern I keep noticing is that the ones that win aren't necessarily the most powerful they're the ones that feel like they understand your context.
Think about it: most AI tools today are essentially fancy command lines. You give them an instruction, they spit out a result. But the products gaining real traction are the ones that remember what you care about, adapt to how you work, and meet you where you are emotionally not just functionally.
I wrote a forum post not long ago on marketing as one of the rising in importance hires for all startups. This is all the things we've done, with some results and free resources.
We've been talking to hundreds of teams building with Cursor, Claude Code, and other agentic tools and the honest answer from most of them is: "We just run it and hope."
Some do a quick manual click-through. Some write a few spot checks. Some just ship and wait for users to find the bugs.
We built TestSprite to solve exactly this autonomous testing that runs from your PRD and codebase but I'm curious what your actual workflow looks like before you merge.
