I have been thinking about this a lot lately: why do so many AI products feel interchangeable?
You open one, you open another. Different logo, different color scheme, same experience. A text box. A chat interface. Some version of "ask me anything." The wrapper changes but the feeling does not.
For months, our most requested feature at Murror was a chat function. Users wanted to talk to the AI the way they talk to a friend. It seemed obvious. Every competitor had it. Every feedback form mentioned it.
Everyone tells you to ship fast. Move fast and break things. Get to market before someone else does.
I believed this for a long time. When we were building Murror, speed was everything. We pushed features weekly, sometimes daily. We celebrated every deploy like a small victory.
There is a moment that separates products people use once from products people come back to every day. It is not a feature. It is not a notification. It is the feeling that the product remembers who you are.
I have been thinking about this a lot while building Murror. We spent so much time on acquisition, onboarding funnels, and activation metrics. But the thing that actually moved our retention numbers was something much simpler: continuity.
Most people are using AI wrong and I was one of them.
For the first year, I used AI like a fancy Google. "Write me a product description." "Summarize this." "Give me 10 ideas for X." Useful? Sure. Transformative? Not really.
After our first launch on Product Hunt, our team spent a little over a month upgrading the product. There were major changes to the UI and several new features added, so the process took time from discussions and redesigning the interface to testing, fixing bugs, and updating AI prompts.
We re also a very small team, so everyone had to push themselves to give 200%. Time and resources are limited, and at the same time, we also had to work on securing funding for the next six months to keep the team running and continue developing the app.
When we first started adding AI features to Murror, we built what we thought users wanted: sophisticated emotion detection, detailed mood analytics, and smart pattern recognition that could tell you exactly how your week went in a neat little chart.
We were proud of it. The tech was solid. The accuracy was impressive. And almost nobody cared.
Our team is planning to launch a new version of our product on Product Hunt next week, after a period of optimization and improvements. As we get closer to launch day, I realize there s a lot to prepare, and I m curious about how other teams usually approach this process.
So far, here s what we ve been focusing on:
Most importantly, making sure the product works well and delivers real value
Continuous testing to ensure performance and stability
Designing clean and clear product screenshots
Preparing a summary of what s been updated, fixed, or optimized
Writing launch content (tagline, description, first comment, etc.)
Maintaining good health and a stable mindset for the launch
Expanding our network and connecting with other makers
Every AI product I see launching right now is racing to add the most impressive, most complex AI feature they can build. Autonomous agents. Multi-step reasoning. Real-time analysis of everything.
When we started building Murror, we fell into the same trap. We wanted to build the smartest emotional AI possible. Something that could analyze patterns across months of conversations, predict emotional states, generate deep psychological insights.
