... ever seen tracks the same things: DAU, session length, retention, engagement loops. All of them answer one question is the user coming back? But lately I've been thinking about a different question: is the user outgrowing us? At Murror, we're building AI that helps people prepare for difficult conversations. And the strange thing is, our best users use us less over time. They come in anxious before a tough talk with a partner or a manager. They work ...

... right now that worries me: the goal is to make AI the relationship. AI friends. AI therapists. AI partners. The pitch is always the same humans are complicated, AI is easy. No judgment, available 24/7, infinitely patient. But at Murror, we kept asking ourselves: what happens when the user closes the app? If the best version of their emotional life only exists inside our product, we haven't solved loneliness we've just made it more comfortable. So we took ... ... difficult conversation the app helps you understand what you're actually feeling and why, so you can show up more clearly with the real person. After a misunderstanding instead of venting to an AI that always agrees with you, Murror

... Most software wants you to come back every day. The business model depends on it. More sessions, more engagement, more opportunities to monetize. But what happens when your product's purpose is to help someone understand themselves better? At Murror, we've been wrestling with a paradox: if we do our job well, users should eventually need us less not more. Early on, we designed features to maximize return visits. Push notifications after 24 hours of inactivity. Streaks. Daily prompts ... ... made real progress on something, it explicitly tells you it's okay to step away. 3. We shifted our north star metric from daily active users to "life moments influenced" did the user actually apply something from Murror

... product in the mental health and self-awareness space: if you're doing it right, your users should eventually need you less. Most product teams optimize for stickiness. More sessions, more time in app, more daily returns. But at Murror, we've been wrestling with a different question what if the goal of our product is to help someone build enough self-understanding that they don't need to open the app as often? When someone uses Murror

... first year of building Murror, we optimized for the same metrics every other app optimizes for: daily active users, session length, screens per visit. The dashboard looked healthy. Usage was growing. We felt good about it. But something was off. Our most engaged users were not our happiest users. People who spent the most time in the app were often the ones who left the harshest feedback. Meanwhile, users who opened the app twice a week for five minutes were ... ... metrics with what we called "outcome metrics." Instead of tracking how long someone stayed, we tracked whether they reported feeling more clarity after a session. Instead of measuring return frequency, we measured whether people said they applied something from Murror

... first year of building Murror, DAU was the number we checked every morning. It was the first thing on our dashboard, the first metric in every team meeting, and the number we used to judge whether a feature was working. Then one day we noticed something strange: our DAU was climbing, but our NPS was dropping. People were opening the app more often, but they were less happy with it. Some of our most engaged users were showing signs ... ... what we started calling "compulsive checking" opening Murror

... When we first started building Murror, I spent a lot of time studying other AI wellness apps. I tracked their features, analyzed their onboarding flows, and mapped out where we could differentiate. I thought our competitive advantage would come from being smarter, faster, or more accurate than them. I was completely wrong about where the real competition was. Our biggest competitor

... 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

... 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. When we started building Murror, we almost fell into this trap. Our first instinct was to build the most capable AI assistant we could and then figure out the positioning later. The logic seemed sound: better technology equals better product. But here is what ... ... what does this person need to feel, understand, or accomplish in this moment?" That reframing changes everything. It changes the interface, the pacing, the tone, even when the AI chooses not to respond. For Murror

... 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. Here is what we missed: users were not coming to Murror

... 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. But here is what nobody warned me about: shipping fast without learning is just organized chaos. We shipped a mood journaling feature in three days. It looked great in our demo. Users opened ... ... ship a perfect product reason being lot of indie developers get stuck in the loop of adding feature, finding new bugs and fixing them. But that does not mean ship garbage. Comment from Muhammed Gazali Ye ilmen(@mgy_programmer): @monatruong_murror

... Everyone is talking about vibe coding right now. Let AI handle the code while you focus on the vision. It sounds revolutionary. So we tried it. For one week, our team at Murror used AI coding tools for everything. New features, bug fixes, refactoring. We wanted to see if it could genuinely speed up our development cycle or if the hype was getting ahead of reality. Here is what we found: Day 1-2: Euphoria. We were generating components ... ... that they change what matters about being a developer. The value is no longer in writing code. It is in knowing what code to write and, more importantly, what code not to write. For a product like Murror

... 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. It sounded incredible in our pitch deck. Users did not care. What ...

... 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. When a user opens Murror

... When we started building Murror, I made the same mistake most AI founders make: I marketed the technology. "Powered by AI." "Smart algorithms." "Personalized insights." All the buzzwords. And you know what happened? Crickets. The turning point came when I stopped explaining what Murror

... months ago, the number one feature request for Murror was a detailed mood analytics dashboard. Charts, graphs, weekly trends, monthly breakdowns. People wanted to see their emotions visualized like a stock ticker. So we built it. And almost nobody used it more than twice. Here is what we realized: people do not actually want to analyze their feelings. They want to feel understood. There is a huge difference between those two things. The dashboard turned something deeply personal into ...

... When we started building Murror, we did what most technical founders do: we disappeared into code for months. We built an emotion analysis engine. We refined our NLP pipeline. We designed beautiful dashboards. We were so proud of what we had made. Then we put it in front of real people. The first 50 users broke every assumption we had. They did not care about the sentiment accuracy score we spent weeks perfecting. They did not use the features ... ... that first raw feedback without waiting for a crisis to happen. My goal for Lifeline: SOS Countdown App is to simplify safety down to a single sentence, just like you mentioned. Comment from Mona Truong(@monatruong_murror

... 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. It took maybe two days to build. The AI engine took six months. I've seen this ... ... Nika(@busmark_w_nika): Sometimes I wish to somehow test the prototype of features among sample of people so you can save most of time for something that is not so important to them. Comment from Mona Truong(@monatruong_murror

... 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. This is something we think about constantly while building Murror. The future of AI isn't just about intelligence it's about relationship. When an AI product can reflect back who you are, help you see yourself more clearly, and grow alongside you, that's when it stops being a tool ...

... dozens of high-quality one-off videos every year. But if you want a 25-hour course on some deeper subject (how to play piano, speak French, etc) this is a different medium entirely. It is hard to consume vs easy to consume. So you can charge for this, because trying to play piano or speak French via random single YouTube videos is almost impossible. You need an indepth course, which means you need to pay money. Comment from Pavel ... ... genuinely hard when you're building for people going through something difficult. with Murror

... imagine you're thinking about a backend to enable storage and collaboration features down the line? Comment from Ryan Hendrickson(@ryan_hendrickson): @maria_vannicola  Nice! Was there something that brought you to use Firebase over other alternatives? I agree with your decision to focus on building the network first, which will make it easier to open doors to monetization later. Comment from Nadia Eldeib(@nseldeib): @ryan_hendrickson  thanks, and hope these are helpful options. Comment from Pashupathi Mali ... ... scheduled a meeting through your link :) Comment from Ryan Hendrickson(@ryan_hendrickson): @astrovinh  You're spot on with your issue -- cool that you're trying to find a solution. What has the process of adding guardrails/protections to Murror

... tomorrow. For me, the most important part is consistency just keeping these habits alive over time. What about you? Do you have a daily (non-work) checklist or personal habits you try to maintain? Comment from Mona Truong(@monatruong_murror): @busmark_w_nika  I'm still learning. This is the website that I'm learning you can try, it is really hard for non-tech like us, but take it slow. https://www.codecademy.com/learn Comment from Mona Truong(@monatruong ... ... murror

... really good at as builders: we constantly try to improve our work and our product every single day. But an honest question I often ask myself is: do we put the same effort into updating ourselves? At Murror , we re a small team of around five people. For me, it s important not only to improve the product, but to continuously update my mindset, skills, and learnings and share them openly with the team. I try to communicate everything ... ... journey? Comment from Musa Molla(@musa_molla): This resonates. Growth compounds when you treat mindset like a product, observe, iterate and stay intentional. Emotional clarity often shows up directly in product clarity. Comment from Nika(@busmark_w_nika): @monatruong_murror

... same year I left Google s Mountain View HQ where I was working on subscription experiences used by billions to pursue Murror, two engineers also left Google to build Character AI. Their early prototype raised safety concerns, but the idea evolved into a platform where people could create virtual characters such as AI companions, assistants, or friends. We started from similar places, but chose very different paths. Character AI focused on moving fast to meet market demand and scale quickly ... ... then kids committed suicide using the product. Murror

... defeated, but because I understand that they are projecting their emotions onto me. Many problems could be resolved if we learned how to regulate anger more mindfully. This realization is also what led me to reflect deeply on Murror, and why it exists in the first place. Murror