Patrick

@alexrodukov @buildinpublic Interesting direction. One thing I'm curious about is less about the feature itself and more about user behavior. What do you think will make someone come back and use this repeatedly after the initial experience?

@buildinpublic This week we're improving an AI assistant that helps founders define and scope projects faster. ai.fourmeta.com

What are you working on this week?

@thebasedcapital @buildinpublic Interesting direction. One thing I'm curious about is less about the feature itself and more about user behavior. What do you think will make someone come back and use this repeatedly after the initial experience?

@buildinpublic building the most elegant and beautiful app to talk to multiple agents including codex , hermes and more all through your iphone and free and end to end encryption: sortie.fly.dev

@slmn_sh @buildinpublic Interesting direction. One thing I'm curious about is less about the feature itself and more about user behavior. What do you think will make someone come back and use this repeatedly after the initial experience?

@buildinpublic working on arib.io ai ecosystem where you can create agents and apps. connect your apps to interfaces like telegram, github and more.

@SystemsForScale Improving activation.Lower prices can drive signups, but activation determines whether users actually experience value and stick around. So activation first. A product that converts and retains users can justify higher prices.A weak activation funnel struggles even when its cheap

Would you rather lower prices or improve activation

@Robeinoz @buildinpublic Interesting direction. One thing I'm curious about is less about the feature itself and more about user behavior. What do you think will make someone come back and use this repeatedly after the initial experience?

@buildinpublic Hi everyone 👋 I just published Week 1 of the Replynt journey: AI assumptions, MVP mistakes, market research, surprisingly accurate predictions… and a few hilariously wrong ones 😂 Would love any feedback from people building with AI. 👇 x.com/robeinoz/statu…

@ycisaac @buildinpublic Interesting direction. One thing I'm curious about is less about the feature itself and more about user behavior. What do you think will make someone come back and use this repeatedly after the initial experience?

This week I'm enhancing FocusLens, which helps you by measuring real focus that matches your goals. Adding smarter distraction detection + better dashboard insights so users can actually understand where their focus goes. Small but meaningful improvements — shipping iteratively. #buildinpublic #focuslens #productivity

@tashaamandaa Perfect, I'll submit the form if theres any. Also, a DM for the setup would definitely help since I'd like to understand the intended workflow before I start testing. I'm looking forward to trying it out.

@_ayla85 Appreciate this. You’re looking at exactly the behavior I care about: what makes the memory become part of the normal loop vs something people abandon. I’d love to have you in the pilot. Form: brainos-hq.com/test/?source=x… If easier, I can also DM setup directly after you submit.

Small Brain OS dogfooding moment. Codex checked Brain OS first, found the tracked project state, then compared it against PLAN.md before answering. This is the product: AI agents should not just remember conversations. They should know the state of work.

Dashboards show activity, not health. What you measure shapes what you think is working. I hope this helps 🧏🧏‍♂️

Confused users never become active users. Onboarding isn’t information. It’s direction. Take note 📝 📋 Good morning CT

@tushardev_ @buildinpublic Have you thought about how you'll turn those qualitative success stories into something that drives adoption?

@tushardev_ @buildinpublic The only thing I'd be curious about is how you'll surface those stories externally. Since the product is privacy-first and offline, the challenge may not be proving value to the user, but making the value visible to people who haven't tried it yet.

@tashaamandaa I'll go through the pilot and pay particular attention to: what makes users keep relying on it what creates workflow dependency where users might still revert back to their previous setup Curious to see how people behave once it's part of their daily workflow. You can send a dm

@tashaamandaa I'd actually love to take a look. What caught my attention isn't just the memory layer itself,but the idea of making AI feel less like separate sessions and more like a continuous working environment. From a retention perspective,that's where I think a lot of tools struggle today

But it’s an artificial activity. And once incentives slow down, everything collapses. Real engagement doesn’t come from rewards, it comes from belonging, clarity, and identity. Most systems ignore this completely. Good day CT

Most Web3 communities don’t have real engagement, they have incentive-driven participation. The difference matters because incentive-driven users behave predictably: - they show up for rewards - they disappear when rewards stop So from the outside, communities look active.

@tushardev_ @buildinpublic Because sometimes reducing friction gets adoption started,but consistency usually comes from users feeling progress, dependency, or continuity across sessions. Curious what behavior would make you feel“okay, this is becoming a habit instead of just a useful tool people test once?

@tushardev_ @buildinpublic That actually makes a lot of sense. I think the interesting part will be observing whether the offline workout generation becomes just a successful first interaction or something users naturally build into their routine over time.

@tashaamandaa but they still feel external to the user’s natural workflow instead of becoming embedded inside it. what part of the current loop do you think creates that strongest dependency over time?

@tashaamandaa That’s actually the strongest type of retention in my opinion. When users don’t consciously return to a product, but the product quietly becomes part of how they already operate. I think that’s where a lot of AI tools struggle currently, they may be impressive,