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.
When we were building Murror, we spent months perfecting our AI emotion analysis engine. Deep NLP pipelines, sentiment layers, the whole thing. We were so proud of it.
Then we launched, and you know what users kept telling us they loved? The simple daily check-in prompt. A single question that asks "How are you feeling right now?" before showing them anything else.
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.
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
The market has never been this crowded. AI has made it possible to go from idea to shipped product in days which means Product Hunt is now flooded with launches every single week. More products, more noise, more competition for the same front page.
So I've been thinking about this a lot: what actually separates the products that make it to the top from the ones that quietly disappear by noon?
From where I sit as a builder, here's what I genuinely believe matters:
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.
Many people have told me that being part of Gen Z comes with advantages we have time, energy, and plenty of opportunities to shape our careers in the AI era. And I do feel lucky to have grown up with technology, to have had early exposure and opportunities to learn and explore it.
But the AI era feels different. The shift is not only new, it s happening at lightning speed. Before I ve even fully adapted to working with AI, we re already seeing waves of layoffs where human roles are being replaced or reshaped by AI systems. And honestly, that creates uncertainty and anxiety not just for me, but for many people around us.
