... could have. And I still don't have a clean answer on the verification-method question, because the honest version is that I don't yet know what I'd do differently with a government-ID-checked 16 versus a self-declared one. I'd rather say that than write a paragraph pretending I've resolved it. The thing I am confident about is narrower. The signal is sparse for a long while yet. Texas only covers accounts created after ... ... support-load event you'd much rather see coming than hear about. None of that is hard. It's just that none of it happens by default, and the default here has a penalty clause attached. Comment from Mona

... were blocked" and "we served a 500" stop looking the same. Two questions, access and response health, but one monitor can carry both. Comment from Omri Ben-Shoham(@omri_ben_shoham1): Good writeup - the distinction between blocking Training vs blocking Agent is the part people are going to get wrong for a while. One thing worth adding from the operating side of an agent, not the site-owner side - when an agent gets blocked, it usually doesn't fail loudly ... ... time instead of weaker, since every dead row you accumulate adds to the baseline instead of just being cleanup debt. One thing I'd watch for once you have the split working: does the ratio of "true 404 shape" vs

... content/entity gap; if Murror is cited but sends no visits, it is visibility without acquisition. That separation should keep a tiny referral channel from being mistaken for proof that the product is absent from the buying conversation. Comment from Mona Truong(@monatruong_murror): @jernej_jan_kocica  The permanence is the part I didn't know, and it changes the order of operations. If a declined category can never be requested again, the submission is the whole decision ... ... Murror best rather than the one that exists, and burned the attempt on it. Hope the pending one lands. Did they tell you the never-again rule upfront, or did you only find it after the decline? Comment from Mona

... destination? If the value is a result someone wants and doesn't care how they got an action then being agent-callable is close to free distribution and you should be looking hard at it before your competitor does. If the value is the experience of a person actually being there a destination then racing to become a tool call is optimizing for a future where your product's whole reason for existing has been abstracted away. Worse ... ... ones who shipped a server fastest. They'll be the ones who were honest about whether they should and, if they did, treated that borrowed trust like it was hard to get. Because it is. Comment from Mona

... dataset this size is that the work of making output safe and correct didn't shrink when the output got cheap. It grew, and it moved, and if you're small it moved onto exactly one desk. Comment from Mona Truong(@monatruong_murror): @ill_robyn Thanks and the reason it ended up as a budget rather than a rule is that I failed at every stricter version first. "Always review AI output" has no partial credit: the first week ...

... year it's noise. They'll be the ones who built a small, honest, embarrassingly manual way to see what their thing actually does to real people and looked at it often enough to catch it drifting. Comment from Mona Truong(@monatruong_murror): @getosmo  "Tagged by failure mode rather than benchmark name" is the line I wish I'd written. That's the whole thing. Once the cases are organized by how it breaks, the set stops being ...

... pricing metric rewards the behavior your actually want from users . If the metric can grow because the user is struggling more, it's probably measuring the wrong thing. That's a useful lens far beyond AI companions. Comment from Mona Truong(@monatruong_murror): @joseph_walker2   Thanks for reading it that closely. That's exactly the test I now run before shipping any plan: would this number go up if my users were having a worse week? If the answer ...

... Mona, a marketer turned founder from Germany. I'm building Xolora, a marketing analytics tool dedicated to solopreneurs and small business owners. I noticed that 80% of that niche is overwhelmed with their marketing and just guessing. When it comes to ads, this means that they're wasting money (around $10,000/year). And the sad truth is that there is no tool out there, that helps them. All the other marketing tools are made for marketers or big teams ... ... underserved niche. Xolora's goal is to simplify ad analytics, give back time, money and ultimately confidence. It just launched in beta and I hope that it will be valuable for its users. What is your niche? Comment from Mona

... loud and instant and mostly noise. In 2026, taking care of the builder is not self-help fluff. It's the actual bottleneck. Treat it like one. Comment from Omri Ben-Shoham(@omri_ben_shoham1): the make mode vs judge mode split is the one that actually changed something for me. i used to check analytics mid build and it wrecked the session every time, not because the numbers were bad but because i'd switch from building to defending ... ... pick it back up next day, or is there some catch-up rule? that's usually where these systems fall apart for me, not the routine itself but the recovery after the first missed day. Comment from Mona

... this: if building is no longer the moat, then the moat is available to anyone willing to do the unglamorous work. Knowing your person. Owning a relationship instead of renting attention. Being early to a workflow before a competitor gets embedded in it. None of that requires funding or a team. It requires you to stop hiding in the part of the work that feels productive and go do the part that actually decides whether the thing lives. Ship ... ... hosseinyazdi): I agree with this. Building has become much easier, but getting people to find it is still the hard part. In my experience, distribution, and consistency usually take much more time than writing the code itself. Comment from Mona

... best day, on a task you made up. Your users meet it on an average day, on the task they actually have. Build for the average day. That's the whole game now. Comment from Mona Truong(@monatruong_murror): @dalemooney   This is a sharper version of my third point than I wrote, and you're right that it has the same shape as the problem a report sensor only fires when the user already caught ... ... transcripts starts accurate and then decays, not because the model changed but because your users did. Which means it has to be refreshed from live traffic on a schedule, or in a year you have rebuilt the exact lab-versus

... sentence an AI says about you when you're not in the room. You can't write that sentence. You can only be the kind of product it's easy to say something true and good about. Comment from Mona Truong(@monatruong_murror): @raffay_sajjad  That "a little scared of what it says back" is exactly the right feeling to have before running it. Mine came back describing a version of the product we'd moved past a year ... ... what my product does in one plain sentence to a person, no model's doing it for me either. Going to actually run the three-assistant test tonight, a little scared of what it says back. Comment from Mona

... inside your app if they can only feel understood while they're talking to your model you haven't solved loneliness. You've made it more comfortable to stay lonely. You've built a very sophisticated waiting room. The alternative is to design for the exit. Concretely, that means three things. Point users back at real people, not deeper into the app. The most valuable thing an emotional AI can do isn't be a better listener than your friends ... ... reported follow through? without a proxy for the good kind of drop-off, "designed for the exit" is hard to distinguish from a nicer story about normal churn, even if the intent behind building it is genuine. Comment from Mona

... builders land on this. When you imagine your product working perfectly, does usage go up forever, or does someone get what they needed and walk away? And which one were you actually optimizing for? Comment from Stacy Wycoff(@stacywycof83995): Mona, this is the question I keep circling back to while building FounderFlow. My honest answer is uncomfortable, I want usage to go down over time, not up. If it is doing its job, a founder should need fewer ... ... that is supposed to make itself less necessary? Comment from Nika(@busmark_w_nika): imo, the whole thing with AI agents is becoming oversaturated the same way as it was with AI in 2024 Comment from Asad M.(@asadmalik901): Mona

... stay more philosophical in practice? Comment from Khaild Naseem(@khaildnaseem): Have you thought about offering chat only after someone finishes writing? It could keep the reflection process while giving users another way to explore their thoughts. Comment from Mona Truong(@monatruong_murror): @khaildnaseem  We've thought about this a lot, and it's the most tempting version of the idea. The problem we kept running into is that "after writing" is exactly when the reflection has the most value ... ... into seeking. We'd essentially be rewarding the hard work of writing with a shortcut to skip the payoff. That said, we are exploring lighter ways to help people explore after they write just not through conversation. Comment from Mona

... animation and 8 seconds of silence. Our engineer thought it was a bug when he first saw the spec. "You want me to add... a delay?" Yes. On purpose. Here's why. We ran an experiment: instant AI response vs. an 8-second pause before the same response. The content was identical. The only difference was time. Users who got the pause rated the AI's reflections 40% more helpful. Same words. Same insights. They just felt more considered ... ... there, it isn't "pretending to think", but rather just pacing so the person can reflect for themselves first, and the discomfort goes away. If it only works while it's invisible, that's the harder question. Comment from Mona

... face value though, or would you always want to spot-check it against the actual code once, given the same agent could narrate its own architecture wrong the same way it narrates a data flow wrong. Comment from Mona Truong(@monatruong_murror): @omri_ben_shoham1  that 2am scenario is exactly what keeps me up honestly. you're right that the middle ground matters I've been getting better at asking the agent diagnostic questions like "what could cause this ... ... data flow here." it's not the same as reading the code yourself, but it's a different kind of literacy. learning to debug through conversation instead of through code. still early in figuring that out though. Comment from Mona

... health aren't always the same direction. Sometimes the right metric is one that goes down. Anyone else building products where you've had to choose between engagement and user wellbeing? Curious how others navigate this. Comment from Mona Truong(@monatruong_murror): @omri_ben_shoham1   It started manual. Our therapist advisor would flag entries that looked like spiraling patterns, and we'd send a gentle in-app message. Once we understood the signals better -- repetition in language, shrinking reflection ... ... been here a lot today. want to try something offline first?" No blocking, just a pause. You're right that most dashboards can't distinguish love from loops -- that's probably worth its own post. Comment from Mona

... Every time we push information at users, engagement drops. Every time we let them pull it when they're ready, it goes up. Has anyone else found that making AI less visible actually made it more valuable? Comment from Mona Truong(@monatruong_murror): @ilyaofliian   Really appreciate you naming it -- "chilling effect" is exactly the right framing, and honestly we hadn't connected it to that body of research until now. The privacy-by-design angle is spot ... ... coincidence. When users feel their private space is truly private, they use it more honestly. That's the whole point of Murror. Thanks for drawing that connection -- it gives us better language for explaining why this works. Comment from Mona

... They want the outcome AI enables. The moment you lead with the technology instead of the transformation, you attract curiosity instead of commitment. Anyone else found that de-emphasizing "AI" in positioning actually improved their product metrics? Comment from Mona Truong(@monatruong_murror): @galdayan  That's such a good point about the AI label setting an expectation of a specific interaction pattern. We saw the exact same thing -- people expected a chat interface and were confused when Murror asked ... ... specific product Comment from Gal Dayan(@galdayan): @monatruong_murror  exactly, and the 41% retention jump is the proof - people weren't confused about what the product does once the label stopped setting the wrong expectation upfront Comment from Mona

... strategy is giving people permission to leave. Products that feel safe to step away from are products people actually want to return to. Anyone else found that removing a high-performing feature actually improved the overall experience? Comment from Mona Truong(@monatruong_murror): @prashant_patil14   Thank you for putting it so well. "The emotional cost is hidden" -- that's exactly what we were missing. We were so focused on the numbers going up that we didn't stop ...

... very different things. The trust didn't come from accuracy. It came from the AI knowing when to step back. Anyone else navigating this tension between what your AI can do and what it should say? Comment from Mona Truong(@monatruong_murror): Thank you both for the thoughtful responses! @alpertayfurr You nailed it -- "reflection instead of surveillance" captures exactly what we learned. That distinction became our core design principle. Even small language shifts, from declarative ("you are") to curious ...

... from Amard Sonal(@amard_sonal): I ve definitely experienced this. The weird part isn t that the AI wrote the code it s realizing your role shifts from builder to evaluator. The bottleneck becomes judgment, not implementation. Comment from Mona Truong(@monatruong_murror): Reading all of these and honestly feeling seen. @Nitesh Kumar I don't think deep technical expertise becomes less valuable I think it splits. There will always be people who need to understand what's happening under ...

... makes you feel understood enough to keep going on your own. Has anyone else found that reducing friction (even well-intentioned friction) unlocked deeper engagement in your product? Comment from Divv Saxena(@divvsaxena): @monatruong_murror that s so good mona u r thinking the right way i have seen this when I don t have someone to talk then if I want to do some analysis i will use ai to do that so that its more clear ... ... well done Comment from Mona

... milestones we have crossed, things we do not want to bring up ever again or things we can never say to any other human. Deleting them is shedding weight that we have carried for far too long. Comment from Mona Truong(@monatruong_murror): @fatima_shehzad   Really appreciate you saying that, Fatima! Comments like yours remind us why we started building Murror in the first place. Keep journaling -- and know that every entry matters, whether you keep ... ... Thank you so much Comment from Bryan Williamson(@bryan_williamson3): Maybe that's because I write my rawest thoughts when nobody is watching. Sometimes deleting an entry feels like closing a chapter, not hiding the truth Comment from Mona