... that idea, more than the platform itself. I've been dealing with a version of this same problem: figuring out where the line is between actions an agent should just do versus actions that need a human to say

... apps it's 30.7%. Monthly retention is 6.1% against 9.5%. Refund rates run about 20% higher, 4.2% against 3.5% at the median, with a much uglier upper bound 15.6% against 12.5%. So the AI label makes people sayyes faster, pay more, and leave sooner. Now notice the timing, because that's the part that actually costs you money. Trial conversion is visible in a week. Refund rate takes a month. Annual retention takes twelve months, which for most indie ...

... follows up until they engage. Curious how others building agency or sales tooling handle this same problem: do you lean on live personalized demos, case studies, money-back guarantees, something else? What's actually gotten a skeptical prospect to sayyes ...

... most audit trails answer 'did this action happen.' the ones that hold up under legal scrutiny answer something harder: 'would the reviewer who signed it still sayyes if you asked them today.' ive been calling this consent-of-record. not just reviewer id, but reviewer knew X at time of sign-off and stands behind it now. it sits above the usual forensic level (timestamp, user, action, immutable hash chain). that layer proves it happened. it doesnt prove ... ... should have an unique identifier, a human owner, timestamp and within Prefactor, we define an agent contract. Eg, what the agent is able to do, what the risk profile and quality profile of that agent is. Ultimately our contract

... feel heard by an AI instead of helping them hear themselves. The hardest product decisions aren't about what to build. They're about what to refuse to build, even when users are asking for it and the metrics sayyes. Anyone else held the line on a feature like this? Curious how you explain the "no" to users who genuinely want it. Comment from Mona Truong(@monatruong_murror): @omri_ben_shoham1  We do share the data ... ... principle. anyone can argue in theory that a chat interface would change the posture, but you actually watched entries get shorter and shallower in the same two weeks you'd expect the opposite from a stickier feature. do you

... been "temporary" for about 4 months now. It works, it's covered by tests, and it's ugly enough that every time an agent touches that file it asks if I want it cleaned up. Every time I sayyes, I regret it a little. Not because the refactor is bad, usually it's genuinely cleaner, but because now I've burned review time on code that wasn't broken, and there's a small chance the agent introduces ...

... Every store asks the same thing: "Got our rewards card?" Sayyes, and I'm digging for an app or handing over my phone number.

... Everyone here will probably feel identified with this: You just finished building the first version of the product. And got a dozen or so people who are kind enough to sayyes to try it out. To try it out because probably they like you, they like the idea of your product, or they simply are too polite to

... Always curious what the SEO/affiliate folks here run vs. the general maker stack. Comment from mono.(@shakutovbekzat): Here s my stack for building mobile apps today: Antigravity + Codex (AI Agent): Switched to this setup recently. Previously, VS

... many developers, designers, and marketers want to work on interesting projects but aren't sure which ones are worth their time. I'm curious: Have you ever joined an early-stage startup before it had funding? What made you sayyes? If you said no, what was missing? For me, trust seems to be one of the biggest challenges. People need to believe in the idea, the team, and the likelihood that something meaningful will come from their effort ...

... vs remote-yes

... just launches you straight into them. What actually works Before you build, validate the problem. Not the solution. The problem. Talk to buyers, not just users. The people who control the budget. Ask them what they need to sayyes. Before you launch, align the team across engineering, marketing, sales, and support. NPI fails in silos. Engineering builds something production cannot make economically. Marketing promises a ship date logistics cannot hit . Before you go to market, make sure your product ... ... same as momentum. You can ship quickly and still arrive nowhere if you have not earned the right to be in the room. Earning that right takes patience. Patience is not popular. It is just true. The problem

... thought we knew We assumed enterprise customers wanted the same things as our small business users, just more of it. More security. More control. More features. We never talked to them. We read blog posts. We looked at competitor pricing pages. We guessed. Here's what we missed: Procurement cycles. Enterprise deals take 6-12 months. We had 30-day sales cycles. We weren't built for that. Security reviews. We needed SOC2. We didn't have it. Customers asked ... ... because the sales motion wasn't designed for them. The product is almost never the reason; it's procurement cycles, internal champions, and legal that kill it. The fastest fix is usually going back to a segment that can say

... where it was going. It felt like I was following a script someone else wrote. So I taught myself to code. Built project after project on my own. Spent an entire summer sending out CVs. Eventually, somehow, IBM said yes. Four years there. Two big projects. The first was managing infrastructure and migrating applications to Azure OpenShift for a Finnish city government. The second was building a procurement chatbot with a bunch of complex data integrations. Real systems, real users ... ... burned out. Simple as that. But I had this rule I made for myself early on. Every year, do one thing that really scares you. Move somewhere new. Take on something you're not ready for. Say

... change. It's small requests that seem reasonable: "Can we add one more page?" "What about social graphics too?" "One more revision, just to be safe." Each feels minor. Saying no feels petty. So you say

... Hunter, Sheraz here (CTO/Co-founder). I m exploring a shift from support chatbots to a sales agent that actually helps shoppers decide and places items in the cart when they sayyes. What we re testing that s different: Decisioning, not deflection: compare two products in-chat with real specs/stock. Zero training ingest: it learns catalog, price, and inventory automatically. Timed nudges: smart bundles/discounts only at the moment of intent. One outcome: add to cart right inside chat + clear funnel/AOV analytics ... ... talshyn): Add-to-cart feels fine, but checkout should stay human-approved. A quick "undo" or mini receipt in chat would build trust, as it keeps things helpful rather than pushy. Curious though, how are you thinking about nudges

... feeling to connect, but sometimes it leads to complicated situations that are uncomfortable to deal with. So I decided to write down some lessons and real-life examples I ve come across. Here s what NOT to do! 1. Sayingyes to every opportunity Whether it s a quick call on LinkedIn or being asked to help promote on the Product Hunt sure, the adrenaline can be exciting, but not everything deserves your time and attention. 2. Giving blind reviews ... ... more visible you are, the less time you have. :D What is your main social media to show up? Comment from Fei C.(@feichen_): Completely agree. Rejection is not personal, sometimes people and products are just not a match.

... Community-driven product development is a huge advantage hearing directly from your users fuels better ideas and stronger loyalty. But it also comes with a classic challenge: feature bloat. How do you decide which user requests to sayyes to, and which to decline without alienating your audience? How do you keep your product vision focused and sharp when the feedback pulls in so many directions? I d love to hear your strategies for balancing user-driven growth with staying ... ... core problem we originally intended to solve? Evaluate whether the number of users requesting this feature truly represents the needs of the majority of users or just a vocal minority. Distinguishing between what users want and what users

... copy, design, offer, value proposition, etc. Based on those early insights, I iterate quickly and it could be small tweaks or full rewrites, depending on what people are saying. To make it easy for them to say

... abadesi and I were wondering if the direction Apple is headed in right now would be something Steve would ve liked and it s been hard to come up with reasons to sayyes. What do you think ...