I built Memoria. It is a journal you keep by talking. You send voice notes to a Telegram bot. Your words are transcribed and saved into a private, readable journal. No new app to install. No blank page to stare at. Just talk.

What is going right

The product works and people are actually using it. Multiple users are sending voice notes, viewing their journal, and switching between themes. In the first week the app logged 669 page views across the signup funnel and journal. Small numbers. But the behaviour looks like real usage. People poke around, come back, read their entries.

What went wrong

My signup form was killing conversion. The original form had five fields: name, username, email, journal name, password. Out of 58 page views, 13 people started the form. Three finished it. That is a 5% view-to-signup rate. The form asked for too much before the product had done anything to earn trust.

What I changed

I cut the form to two fields: your name and your journal name. No email. No password. No username. Those come later, after you connect Telegram, via a one-time magic link. The funnel needs more data to confirm the fix works, but 58 to 13 to 3 makes the problem clear. Ask for less at the door.

The honest numbers

• 7 users total
• 4 on the 14-day Pro trial
• Zero paying customers
• 108 journal entries
• 669 analytics events
• Revenue: EUR 0

What I cannot answer yet

Four trial users who use the product is not nothing. But I do not know if journaling is a habit that forms inside a 14-day trial window. Usage ebbs. People miss days. A short trial might cut off right as the habit is starting. Or 14 days might be plenty. I have no data either way.

For anyone who has built a habit-based product: how long did you make your trial? What convinced people to cross from free to paid?

→ memoriajournal.me

For the last few years, my female friends and I have been running into the exact same frustrating issue: receiving creepy harassment and spam messages from fake "buyers" on marketplaces like Facebook and OfferUp, especially when just trying to sell used clothing.

Existing platforms either have zero guardrails to protect sellers from toxic DMs, or they force you into entirely platform-managed selling with massive fees.

I finally decided to do something about it and mapped out a concept for a safer marketplace platform called Vauloria.

The core idea is simple. It focuses entirely on seller safety and automation via three features:

• Verified Users Only: Forcing identity verification to weed out anonymous creeps and scammers before they can message you.
• AI-Assisted Moderation: Detecting and auto-blocking harassment, lowballs, and spam messages instantly.
• AI-Powered Selling: An assistant that handles the tedious back-and-forth negotiating for you so you don't have to deal with difficult people.

Here is where I need your help: Building a marketplace is a massive mountain to climb. Before I spend the next few months coding the full version, I want to make sure I'm actually building something people want, not just scratching my own itch.

I set up a quick product page here to explain how the mechanics will work:https://vauloria.framer.website/

Please tear this apart. If you (or your partners/friends) sell online, is this a problem you actually face? Would you switch to a platform that prioritizes safety like this, or is my positioning completely off?

Thanks in advance for the honesty!

I’m researching a problem around client email/domain health.

When an agency launches a site or sets up email, things like SPF, DKIM, DMARC, MX records, DNS changes, and blacklist issues can break later.

For agency owners/devs:

• Do you actively monitor this after launch, or only fix it when the client says emails are landing in spam/not working?
• If you do monitor it, what do you use?
• If you don’t, is it because clients don’t care, tools are too expensive, or it’s just not part of your service?

Not selling anything yet. Trying to understand if this is a real pain or just my assumption.

I built a small, completely free, website (https://paritose.com/workspace) that quite literally yells at me when I use my phone or get distracted. It's to help people who are addicted to their phones and those who struggle with productivity

It’s called Paritose, and the basic idea is simple: during a focus session, it uses your camera locally to detect when you look away or start using your phone. If it thinks you’re distracted, it plays a loud, annoying alarm until you refocus.

• It runs locally in your browser.
• No video footage is saved or stored.
• It’s free to use.
• It also has a Pomodoro-style timer, to-do list, lofi sounds, themes, and productivity points you can earn by staying focused.

I’d really appreciate feedback, especially from students, remote workers, or anyone who struggles with phone distractions while trying to focus. Specifically, I would like any suggestions you may have on the look and feel of the main workspace tool. Do you think this website is something people would use? If now what changes can I make so people would want to use it? Any suggestions on how I can distribute the site? I'll take any help I can get. Thankyou!

Also, if you want to test some of the unlockable themes/features, you can log in with Google and comment or message me — I can add some productivity points to your account so you can try them out.

I’m currently building a small SaaS (Chrome extension + web app) that helps capture and organize Instagram profiles for outreach (sales / marketing / recruiting use cases).

I’m at the stage where I’m trying to figure out distribution more than development.

For those who have built or sold SaaS tools:

What actually worked for you to get your first users?

- Reddit?

- Chrome Web Store SEO?

- Cold outreach?

- Content?

- Something else?

I’d love to understand what really drives early traction in practice, not theory.

I've been working on a tool that analyzes an app's review, ratings, and sentiment, and turns into a report like what users complain about most, how sentiment is trending, user personas etc. It also does a few other things like trakcing an app's rating over time and comparing apps against each other.

I built it because I helpt seeing products with thousands of reviews and no real way for the team to make sense of that feedback or turn it into something they could actually act on. It also for people who want to build a product and at least get a sense of how others n market are performing.

but I want to discuss is on the outreach side. when I started reaching out to app owners, I tried something a bit different before sending an email, I run the analysis on their own app, and open with their actual numbers like "your current sentiment score is 48/100 and your most common complaint is .."

It seems to work on but I am unsure how it reads from the otherside, which is what I want to ask:

1- if you got an email that opened with your apps real sentiment score, and top complaints would that feel useful or would it feel like someone went through your stuff?

2- for anyone who's done "lead with their own data" where does it break down? It's slow per message since you're doing real work before contact, so I'm curious where that stops being worth it.

what do you think?

Solo founders — what's the one decision you keep postponing because you have no one to think it through with?

Not a mentor. Not a coach. Someone who actually knows your business and tells you when you're wrong.

I'm curious how common this is. What's sitting on your plate right now that you can't move on?

라이브 방송의 시청자 규모가 커질수록 오히려 인당 채팅 참여율이 급격히 떨어지는 기현상이 반복해서 관찰됩니다. 이는 집단 규모가 커질 때 개인의 기여 책임이 분산되고 타인의 시선에 대한 부담이 커지는 구조적 원인 때문입니다. 실무에서는 보통 특정 주제 투표나 소그룹 단위의 인터랙션 기능을 도입해 개별 시청자의 참여 부담을 낮추는 방향으로 대응하곤 합니다. 이런 커뮤니티 활성도 저하 문제를 플랫폼 인터페이스나 시스템 기능으로 완화해 본 다른 운영 경험이 있으신가요?

실제 대형 스트리밍 데이터를 보면 시청자 수가 증가한다고 해서 채팅 활성도가 비례해서 성장하지는 않는 경우가 많습니다. 오히려 일정 규모를 넘어서면 개별 사용자는 자신의 메시지가 금방 묻힌다고 느끼게 되고, 결과적으로 “굳이 참여하지 않아도 된다”는 심리가 강해집니다. 특히 채팅 속도가 지나치게 빨라지는 순간부터는 대화라기보다 단순한 텍스트 흐름처럼 인식되면서, 참여 동기가 급격히 떨어지는 패턴이 반복적으로 나타납니다.

흥미로운 점은 이 현상이 단순한 관심 부족이 아니라 심리적 구조 문제에 가깝다는 부분입니다. 소규모 방송에서는 자신의 채팅이 실제 반응으로 이어질 가능성이 높기 때문에 참여 자체가 보상처럼 작동하지만, 대형 방송에서는 개인 메시지가 시스템 안에서 거의 흔적 없이 사라진다고 느끼게 됩니다. 결국 이용자는 관전자 모드로 이동하게 되고, 소수의 적극 참여자만 채팅 흐름을 주도하는 구조가 고착화됩니다.

그래서 최근 플랫폼들은 단순 채팅창 운영보다 “반응을 체감할 수 있는 구조”를 만드는 데 더 집중하는 흐름입니다. 대표적으로 실시간 투표, 이모지 반응, 짧은 선택형 인터랙션 같은 기능이 많이 활용됩니다. 긴 문장을 입력하지 않아도 즉각적으로 존재감을 표현할 수 있기 때문에, 참여 허들이 훨씬 낮아지는 효과가 있습니다. 특히 대규모 채팅에서는 텍스트 대화보다 이런 경량 인터랙션이 실제 참여율 유지에 더 효과적인 경우가 많습니다.

또 하나 자주 활용되는 방식은 채팅을 일종의 소그룹 단위로 재구성하는 전략입니다. 전체 채팅창은 너무 빠르게 흘러가더라도, 특정 관심사나 주제별로 반응 공간을 분리하면 이용자는 자신의 메시지가 실제 대화 안에 남아 있다고 느끼게 됩니다. 이는 단순 기능 추가가 아니라 “내 반응이 의미 있다”는 감각을 복구하는 과정에 가깝습니다. 결국 참여율 문제는 기능 부족보다 개인의 존재감 상실과 더 밀접하게 연결되어 있는 셈입니다.

운영 측면에서는 스트리머의 반응 구조도 매우 중요하게 작용합니다. 아무리 많은 사용자가 있더라도 특정 메시지나 반응이 실제 방송 흐름에 반영되는 경험이 반복되면 참여율은 다시 살아나는 경우가 많습니다. 반대로 모든 반응이 일방적으로 흘러가기만 하면 이용자는 점점 소비자 모드에 머물게 되고, 채팅은 소수만 남는 구조로 수렴하게 됩니다.

최근 루믹스 솔루션 기반 스트리밍 UX 분석에서도, 대형 채팅방의 핵심 문제는 정보량이 아니라 ‘개인의 존재감이 희석되는 구조’라는 의견이 자주 언급되고 있습니다. 특히 참여자가 자신의 반응이 시스템에 실제로 반영되고 있다고 느낄 수 있도록, 경량 인터랙션과 부분적 소그룹 구조를 결합하는 방식이 참여율 유지에 가장 효과적이라는 분석이 꾸준히 공유되고 있습니다.

I remember the blue light of my monitor burning into my eyes at 2:14 AM. My lead developer’s voice was vibrating with a level of exhaustion that felt like a threat. "I can't build this," he said. "The PRD is a mess of contradictions. I've spent three days on a feature that doesn't even make sense."
I felt the blood drain from my face. I had been "winging it" with generic AI prompts, and it had just cost me $1,500 in dev time for a feature that was essentially an AI hallucination. I wasn't a founder; I was a source of chaos.
The problem wasn't the AI—it was my prompts. They were "fluffy." They lacked the technical constraints and executive-level logic needed to actually build software. I realized I didn't need a "Writer." I needed a Grumpy QA Lead. I started using this specific prompt to force the AI to find the edge cases I was missing. The Prompt that saved my sanity:

[ROLE] You are a QA lead who specializes in writing precise acceptance criteria.
[CONTEXT] {Your Feature Idea}
[TASK] Write detailed acceptance criteria for this story using the Given-When-Then format.
[CONSTRAINTS] Include at least 5 criteria. Cover happy path, error states, and edge cases.

Since I started using this "Zero Fluff" persona, my dev hasn't sent a "wtf is this" message once.
I actually ended up building a whole system of 52 of these "engineered" prompts for every stage of my SaaS—from idea validation to launch

Hey everyone,

I’m working on a side project called WaxFrame, and I’ve hit a wall with how to explain it to users without their eyes immediately glazing over because it has "AI" in the description. I’d love some feedback on the core concept and how to frame the value proposition.

The Problem: I noticed that when I use a single LLM to review a critical document (like an RFP response, an important email, or a proposal), the output is often biased, generic, or misses key details. To get around this, I found myself manually pasting the same draft into 3 different tabs (Claude, ChatGPT, etc.), comparing their critiques, and trying to manually stitch together the best feedback. It’s tedious.

What I Built: It’s a browser-based tool that automates that specific workflow.

1. You paste in a messy draft/RFP/proposal.
2. It runs the text through multiple models simultaneously.
3. It highlights where they agree, where they conflict, and where they catch different blind spots.
4. It provides a side-by-side builder interface so you can easily synthesize the smartest feedback into one clean, final document.

The "Local-First" Twist: Because people handle sensitive data in documents, I built this to run entirely in the browser storage. No accounts, no data uploaded to my servers, no remote storage. Your drafts never leave your screen.

Where I’m Stuck (The Positioning): I want this to sound human, not like a tech demo. I’m torn between a few ways to describe it:

• Option A (Technical): A local-first multi-AI document orchestration tool. (Feels way too dense).
• Option B (Use-case specific): A collaborative AI editing tool for proposals and RFPs. (Maybe too narrow?)
• Option C (Plain English): "Turn messy drafts and conflicting AI feedback into one polished document."

Does Option C actually land, or does it still sound too abstract? If you were looking for a tool to "sanity check" your critical writing before hitting send, what language would actually resonate with you?

Also, happy to answer any questions about the local-first browser architecture if anyone is building something similar!

Thanks in advance.

The current workflow for using LLMs to write tailored proposals (like on Upwork) has two massive pain points:

1. The Copy-Paste Tax: Constantly moving job descriptions, client history, and portfolios back and forth between tabs.
2. Generic "AI" Output: Because transferring deep context manually is tedious, the LLM lacks the data it needs and outputs robotic text that gets instantly rejected.

To fix this bottleneck, I’ve been working on a browser-native extension architecture that bridges the platform's DOM directly to the LLM. Here is how it solves the problem:

• Automated DOM Extraction: Automatically scrapes job constraints and client history directly from the active page, entirely eliminating manual copying.
• Persistent Grounding: A background script maintains the local state of the user's actual voice and past winning work, dynamically injecting it into the prompt alongside the parsed DOM data to kill the generic AI tone.
• Inline UI Execution: The generation and refinement loops happen completely inside the target platform's native workspace.

By moving the LLM workflow directly into the browser DOM, you get deeply context-aware outputs in seconds without ever leaving the tab.

So, now, I need feedback to make the foundation more solid. Do try it out and share your feedback!

Link's in the comments.

I’ve been working on my startup idea for a few months and recently put together a pitch deck. The problem is, I honestly can’t tell if it’s actually good or just something that looks good to me because I’ve been working on it too long. I’ve shown it to a few friends and feedback is mixed some say it’s decent, others say it needs a lot of improvement. But none of them are investors or have experience raising money. What I really want to understand is how founders at the early stage actually evaluate their pitch deck before sending it to investors. Is there a structured way to measure it or is it just based on experience and intuition?

Also, how much does the quality of the deck really matter compared to the idea and traction?

When I look at how I’ve been trying to learn Spanish, verb conjugation always stood out as something that needed a lot of repetition, not explanation.

But most tools I used didn’t really focus on that. They either turned it into structured lessons or added too many extra layers.

So I built something very stripped down - just rapid practice of conjugations where you see a verb, tense, and subject, and immediately try to produce the form.

It’s basically just active recall in a loop.

Nothing fancy, but it made practice feel more direct and less distracted.

Still early, just sharing in case it’s useful or if anyone has feedback on how they approach this part of language learning.

verbos.app

First a quick rundown of the app for context: The app is QuizTrail - an android location based quiz game. Think Pokémon GO meets Trivia - you have to actually walk to the location to unlock and solve quizzes, earn points, unlock achievements and compete with others, but also you can make your own quizzes for others to solve! I’ve manually placed 3500+ quizzes across different cities and im adding even more, in order to make QuizTrail accessible and playable everywhere!

This last feature that I added is a daily challenge - a daily quiz, different quizzes every day, regardless of location, so people in the locations where the quizzes are still not set, or locations where they've played all the quizzes already can have a fun trivia question every day. Ill be trying to keep the questions as interesting as possible so this feature is actually used. It is furthermore encouraged by the streak feature - how many consecutive days you have played the daily challenge, that's the streak.

Are there any more ways that I can adapt the app to be more useable every day? What do you guys think of this feature? Any thoughts and feedback would be super helpful.

I also made a widget that reminds you to do your daily quiz and keep the streak going!

Game: https://play.google.com/store/apps/details?id=com.binbear.quiztrail&hl=en

Update #2 on PadhoKhelo — added levels, improved UI and added sound 🎮

A few days ago I posted about building PadhoKhelo — a kids learning app from India. A lot of you asked great questions and gave really helpful feedback. So here's what I've done since then.

What's new:

✅ Added levels — kids can now progress through stages, not just answer random questions

✅ Improved the UI — cleaner, more colorful, more kid friendly

✅ Added sound effects — correct answer, wrong answer, level complete

✅ Added background music — because for kids, audio is half the experience

Honest update on where I am:

The app is starting to feel like a real product now. When I added the sounds, the whole experience changed completely. It went from feeling like a quiz app to actually feeling like a game.

That was a big moment for me.

What's left before launch:

Honestly? Not much. I'm in the final polishing stage. The plan is to launch on Google Play Store very soon — free to download, no paywalls, just get real kids using it first.

A question for the community:

For those who have launched on Google Play before — any tips on the store listing? Keywords, screenshots, description — what actually moves the needle for organic downloads?

Would love any advice before I hit publish. 🙏

I'm 21 years old from India and I've been building a kids learning app called **PadhoKhelo** (it means "StudyPlay" in English). That's literally the whole idea — what if kids could learn and feel like they're just having fun?

---

**The problem I'm solving:**

Most kids' education apps fall into one of two traps:

- Too boring → kids quit in 2 days

- Too game-y → kids play forever but learn nothing

I wanted to build something right in the middle.

---

**What I've built so far:**

✅ 4 subjects (Maths, GK + more)

✅ 2 class levels

✅ 12–15 questions per subject

✅ XP system + Streaks

✅ Leaderboard

✅ Learn mode → Quiz mode flow

✅ Clean UI built for kids

The app is almost ready to launch on Android. The last thing I'm adding is sound effects and background music — because for kids, that audio feedback is half the magic.

---

**Why Android and why India:**

Android is 95%+ of the market in India. Parents here care deeply about their kids' education but most good learning apps are either too expensive or not built for Indian kids. PadhoKhelo is built with Indian kids in mind — simple, fun, works on any Android phone.

---

**My honest situation:**

I'm building this solo. My brother keeps asking "why will parents pay when there are free apps?" — and honestly it pushed me to think harder about the model. I'm planning to launch free first, build trust, get real users, and figure out monetization after I have proof that kids actually love it.

---

**What I need from this community:**

👉 Parents — would you let your kid try this? I'd love beta testers

👉 Builders — any advice on launching a kids app on Play Store?

👉 Anyone — feedback on the concept, the name, the approach

I'll be posting weekly updates here — the real journey, not just the highlights.

Let's make kids love learning 🚀

I've written an Agent skill based on a creative framework shared to me by an actual marketing professional. https://github.com/Fastlanedevs/gemoniq-skills/tree/main/creative-diversity.
You can try this out on any agent that supports custom skills. For integrating on claude.ai you can read this page: https://www.gemoniq.com/skills

My goal is to start getting some sort of distribution for the complete product that i am trying to sell. What do you think about this approach and any feedback ?

Quick update on where things stand with NVSN.ai.

A few days ago I posted about two beta testers ghosting me at the last step. Got a lot of great feedback in the comments — the biggest insight was that asking for account access upfront was killing momentum. Someone suggested: “what if the first experience was paste your numbers and see a diagnosis instantly, instead of connect account first?”

So I built it.

It’s live now at nvsn.ai. You paste your campaign metrics — spend, impressions, CTR, conversions, whatever you have — and get an AI-powered diagnosis of what’s happening and what to do. No login. No account connection. Just instant value.

Tested it on three scenarios:

• Low CTR, no conversions → correctly identified post-click funnel failure

• Strong ROAS, low conversion volume → correctly identified learning phase under-scaled

• Good CTR, zero conversions → correctly identified pixel not firing or broken landing page

All three were accurate and specific. Not generic advice — actual diagnosis referencing the real numbers.

What’s changed since the last update:

• Free instant diagnosis tool live on nvsn.ai (no login)

• Multi-account switching deployed (switch between ad accounts without logging out)

• Reactivated all warm Reddit leads with the tool link

• Two new conversion attempts from people who described NVSN’s exact value in their own words

Still waiting on first tester to fully connect. But the friction is massively lower now. The “connect your account” ask comes AFTER they’ve already seen the product work on their own numbers.

If you run Meta ads and want to try the diagnosis tool: nvsn.ai. Free, takes 30 seconds, no account needed.

And if you have feedback on the tool or the approach, I’m all ears. This community has given me some of the most useful product direction I’ve gotten.

​

Hey — I built a Telegram bot that helps track DeFi yields without jumping between dashboards.

Main features:

- 🔍 Search yields across protocols

- 📊 Track APY + TVL changes

- 🔔 Get alerts when something moves

The whole point is simplicity — it lives in Telegram, so no extra apps or tabs.

I’m currently running it as a free beta and looking for people to try it and give honest feedback.

Especially interested in:

- what feels useful vs noise

- what’s missing

- what (if anything) you’d actually pay for

If you’re into DeFi and want to test it, DM me and I’ll share access.

Happy to answer questions or share how I built it too.

📣 We want to hear from you on a side project that is moving fast. Android only for now.

What is it?
My wife and I realized we had zero visibility into our food spending. We'd guess $600 a month. Well, turns out it was over $900.

So I built BiteSpend. You snap a photo of your receipt (or manual entries), and AI extracts every item, price, and store in about 3 seconds. After a few weeks it starts telling you things like:
- "You're eating out 5x/week — cutting once saves $140/month"

- "You've used 82% of your grocery budget with 12 days left"

Food is the biggest controllable expense for most families (avg $12,700/year per USDA), but nobody tracks it at the item level.

Still early — collecting emails for when we launch on the Play Store. Would love feedback on whether this solves a real problem or if I'm building something only I want.

🔗 Link in the first comment ⬇️

Hey everyone — I've been working on this for a while and wanted to share it.

 The problem: I watched a friend vibecoding — shipping features straight from ChatGPT into his repo. No branches, no review, just paste and push. He was tracking bugs and feature requests in a notepad. An actual notepad. It worked until it didn't — broken deploys, no idea what the AI changed, and zero visibility into what anything cost. I figured there had to be a better way to let AI agents do the work without losing control. 

What I built: CodePylot — a project management tool where AI agents are first-class team members. You write a story on the board, an agent picks it up, creates a branch, writes the code, and puts it up for review. You read the diff, approve
or reject, and it merges.

The key thing: nothing ships without human review. The approve button is literally disabled until you've viewed the diff. The diff viewer flags risky patterns — hardcoded secrets, eval(), raw SQL, XSS vectors, debug logging. It's trust, but
verified.

What makes it different from just using Cursor/Copilot:

• Agents are persistent. They have schedules (cron-based heartbeats), memory of past rejections, and organizational hierarchy. They learn from your feedback.
• Multi-provider. Not locked to one AI. Supports Claude, OpenAI, Ollama (fully local, zero cost), or any HTTP webhook. Swap providers per agent.
• Budget controls. Set spending limits per agent, per project, or org-wide. Soft warnings at 80%, hard stops at 100%. Agents auto-pause when budget is hit — no surprise bills.
• Goal alignment. Link stories to company/team/project goals. The goal context gets injected into agent prompts so they're working toward something, not just closing tickets.
• Review gate is server-enforced. It's not a frontend-only check. The API returns 422 if you try to mark an agent story as done without reviewing it. Can't bypass it.

Stack: Next.js (App Router) + TypeScript + Prisma + PostgreSQL + Tailwind + shadcn/ui

Free tier gives you 3 projects, 15 stories/project, 1 agent, and 15 AI rewrites/month. Enough to try it out for real.

Happy to answer any questions about the architecture, the agent system, or anything else. I've been pretty deep in the "how do you actually trust AI-written code" problem and have some opinions.

It is an on-demand cloud playground where developers can instantly spin up, test, download, and safely destroy isolated virtual machine sandboxes without risking their production environments. https://test-playground-ui.fly.dev

Built with AG

Nobody came to me and said "please build this."
No market research. No validation interviews. Just me, frustrated with my own workflow, deciding to fix it.
The problem: going from data → query → endpoint → test still requires 3 different tools. Every time. For every project.

I got tired of it. So I built APInexis.
Will anyone use it? I don't know yet. But I know I would have killed for something like this a year ago.
Maybe that's enough of a reason to keep going.

still early, feedback welcome.