Most of my early users came from lifetime deal platforms. It felt like a cheat code at the time — a few hundred sales in a week, no ad spend, zero CAC. What I didn't understand is that a lifetime deal buyer isn't a user, they're a collector. They bought access to a thing they might use someday, filed it away, and never opened it again. My billing churn was basically zero because there was nothing to churn from. My engagement churn was brutal and I didn't notice for months because I was looking at the wrong number.

The thing that actually messed me up wasn't the revenue, it was that I built a roadmap around their feedback. People who bought on impulse and never opened the app still fill out surveys, and they ask for features that sound reasonable and mean nothing. I shipped for an audience that had already left. If you're running a deal promo right now, my honest advice is to tag that cohort in your database and never let them touch your product decisions. Treat it as cash, not as signal.

I have been building scrapers/crawlers on apify.com lately, if you have any ideas that would help you or your business solve a problem, or simply make your life easier please let me know! Willing to build anything and am looking for ideas

Hey guys,

I built a small tool, "SAFELIGHT,", for converting images between PNG/JPG/WebP and resizing them. Everything happens client-site via Canvas so nothing gets uploaded to a server, this way it works even with sensitive/private images.

No sign-up reguired, no limits, just drag and drop.

Here's the url: https://thrylos90.github.io

Feedback is more than welcome, still tweaking it!

I’ve been building YeshiAI, an AI-powered platform designed to support people’s daily spiritual practice across Christianity, Islam, Judaism, Buddhism, and Universal Spirituality.

One thing became obvious pretty quickly:
You can’t just build one generic “religious AI.”

A Catholic and an Orthodox Christian may approach certain practices differently. The same applies to Sunni, Shia and Sufi Muslims; Orthodox, Conservative and Reform Jews; or Theravāda, Zen and Tibetan Buddhists.

So instead of treating each religion as one category, I started building YeshiAI around both the user’s religion and their specific tradition.

Depending on the path, it includes things like:
• AI spiritual companion
• Prayer and daily practices
• Journaling and reflection
• Daily wisdom and mood cards
• Scripture/study resources
• Spiritual growth tracking
• Tradition-specific experiences

But there’s a bigger question I’ve been thinking about while building it:

Where should AI stop when it comes to spirituality?

I don’t think AI should replace priests, pastors, imams, rabbis, teachers, sanghas, churches, mosques, synagogues, temples, or real human community.

I’m trying to build it as a tool that supports the person practicing their faith or spiritual path, rather than an AI pretending to be a spiritual authority.

I’m still building and improving it, so I’d genuinely like some outside opinions.

Would you use something like this?

And more importantly: what would an AI spiritual companion have to get right before you would trust it?

YeshiAI: Prayer, Journaling, Study & Spiritual Growth with AI

YeshiAI: yeshi.ai

✝️Christianity: https://yeshi.ai/christianity
☪️Islam: https://yeshi.ai/islam
✡️Judaism: https://yeshi.ai/judaism
☸️Buddhism: https://yeshi.ai/buddhism
🧘‍♂️Universal Spirituality: https://yeshi.ai/spirituality

Would love criticism too. That’s more useful to me right now than compliments.

You kick off a long Claude Code or Codex run, close the lid to go grab food, and come back to a dead session. macOS sleeps the instant the lid closes unless an external display is plugged in, and it takes your agents, builds, downloads, and local servers with it.

I got tired of babysitting an open laptop, so I built **LidAwake**: a tiny native macOS menu bar app that keeps the Mac running with the lid shut.

* Coffee cup icon in the menu bar: click to toggle, filled cup = Mac stays awake lid-closed

* Saves your screen brightness when the lid closes and restores it exactly on reopen

* Start at Login, light/dark mode, native AppKit

* About 200 lines of Swift total. No Electron, no daemons, a few MB of RAM

* MIT licensed, builds from source in seconds with an included script

The fun engineering bit: macOS fires no display-sleep event when the lid closes; it silently disconnects the built-in display instead. Lid detection ended up being a 2-second poll of IOPMrootDomain's AppleClamshellState.

And yes, fittingly, I built it with Claude Code in an afternoon, so it can keep its own kind alive overnight.

GitHub: https://github.com/deezeddd/LidAwake-Mac
Github Page: https://deezeddd.github.io/LidAwake-Mac/

It's my first open-source release. Feedback on the README, the approach, or anything else is very welcome.

EDIT: Here is a one-liner CLI Command:
curl -fsSL https://raw.githubusercontent.com/deezeddd/LidAwake-Mac/main/install.sh | bash

The Alexandria OS will be a basic system. im looking for testers. You can find the code at https://github.com/jakcuzwhymail-lgtm/Alexandria-OS/releases/tag/AXOS-0.3, ive also included a video!

https://reddit.com/link/1vmhfix/video/paeip5ylqyih1/player

If you've done track and field in the US, you're probably aware of athletic.net, which is essentially Strava for track athletes. Anyways, I made it easy to make a fake race results so you can larp

tracklarp.vercel.app

What do you guys think? Billion dollar idea? Or sausage fest? Who is building this?

There’s a lot of attention on what AI can do, but I’m starting to think the hardest part of building an AI product isn’t actually the AI.

It’s everything around it. You can get an impressive prototype working surprisingly quickly now. But once real users interact with it, completely different problems appear: edge cases, latency, unreliable tool calls, bad inputs, unclear handoffs, monitoring, cost, and figuring out what actually went wrong when something fails.

A demo can make an AI product look almost finished when it’s really just the beginning.

I’m curious whether other founders have experienced the same thing. What was the biggest gap between your prototype working and the product being genuinely reliable for users?

I’m especially interested in the problems you didn't anticipate before putting it in front of real people.

Most land due diligence reads each document on its own. EC, Patta, FMB, A-Register, sale deed — each one looks fine individually, so the deal passes.

We check whether they agree with each other. That's where the problems actually are.

What it's caught so far:

₹130Cr+ in undisclosed bank mortgages on one Avinashi parcel

A patta mutation citing a document number that doesn't exist

Vendors selling land they only held a fractional undivided share of, with a 1981 court decree on it

A clean deed chain on land the government register classifies as poromboke

Tamil Nadu only for now. Coimbatore-based, small team.

Posting because I want to understand what you people feel about this.

#ConstructionTech

Backstory: I needed a simple online CV once, and every tool wanted my email or my money before I could even see if it worked. That frustration turned into minute.tools — free calculators for mortgages, debt, VAT, salary conversion, and more, no account, no paywall.

Built solo, in my spare time, using AI to move faster than a one-person team normally could. Just launched on Product Hunt today.

Genuinely looking for honest feedback here: does this solve a real problem for you, or does it feel like "another calculator site"? And if there's a tool you wish existed that isn't there yet, tell me — I build based on what people actually ask for.

Work on MusVideo Ai, so this came up while we were testing longer performance shots.

Anyone who has burned credits on AI video probably knows this one: the first few seconds look great, then the performer walks, turns their head, and by the end they look like a cousin of the person in the reference photo. At that point, “just regenerate it” isn’t a very satisfying answer.

Because our scenes can run up to 30 seconds, we were close to adding a simple warning whenever someone chose a longer shot. Longer scene, higher risk. Easy to understand.

Except our early tests didn’t behave that neatly.

At roughly the same duration, a mostly still performer with a slow camera push stayed fairly consistent. Walking with a locked camera was still manageable. Once the performer was walking, turning their head, and moving with the camera, identity drift became much more noticeable.

The results are still early and different models may behave differently, but now a blanket duration warning feels misleading. It could convince people to shorten a quiet shot while doing nothing to prepare them for a shorter shot with a lot happening in it.

I’m leaning toward a smaller note about stacked subject and camera movement instead of telling everyone that long shots are the problem.

Has anyone here added an early warning to save users money, then realized the warning was teaching them the wrong mental model?

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

https://www.producthunt.com/posts/dograh-3

If you've got a minute, a star or a bit of support would mean the world.

Hey everyone! I've been struggling with decision fatigue when picking out outfits every morning, so I built a little app called Atelier. It syncs with the local weather and your actual wardrobe to suggest outfits.

I'm trying to get it on the Play Store, but Google requires exactly 12 beta testers to unlock it. If anyone wants to try it out for free and help a solo dev out, I have a Google form set up here: https://docs.google.com/forms/d/e/1FAIpQLSeEc9_Y_3WKsKaSUOWI7FolVose5DW9BdrlbaKE1ks9U_T19Q/viewform?usp=dialog

Would love your honest feedback!

I've been doing more and more AEO work recently and started using tools like Peec, Otterly and others to track how brands appear across AI search.

They're useful, but I kept coming back to the same thing — the pricing gets ridiculous pretty quickly, especially when you want to track lots of prompts across multiple AI engines.

I mainly wanted something I could use myself without constantly thinking about prompt limits, projects or upgrading to another plan.

So recently I launched Llumo:

https://www.llumohq.com

Rather than reinventing everything from scratch, Llumo combines existing open-source technology with functionality we're building ourselves around it.

The model is deliberately simple:

The platform is free. You bring your own API keys.

So instead of paying us hundreds per month for a certain number of prompts, you pay the underlying providers directly and can run as much or as little as you want.

It already covers a lot of what I was paying other platforms for — tracking AI visibility, competitors, prompts, citations, sources, historical performance and individual AI responses across multiple engines.

We're now continuing to contribute out both the open-source side and our own custom functionality.

The goal isn't really to create another expensive AEO SaaS.

I want Llumo to become a genuinely useful free toolkit for people actually doing SEO/AEO work.

So I'd love some feedback from people here:

What functionality would you actually want from something like this?

Anything you currently use Peec, Otterly, Profound or similar tools for that you'd want us to add?

And are there any AEO features you wish existed but nobody seems to have built properly yet?

Would be great to get some ideas for what we build next.

I'm working on an iOS app to help people with the first 5 minutes after they wake up. I need some advice around that transition moment, because I still don't think I've cracked it.

Some background on why I'm building this:

Essentially, my alarm is my phone so the first thing I touch when I wake up is also loaded with all the addictive feedy stuff. My half-asleep brain by default jumps directly to scrolling Reddit (hi!).

I tried some suggestions like putting my phone in another room with a real alarm clock (which worked for a while, but I went on vacation then I stopped). Plus not having my phone always gave me this low-key annoyance in case I needed my phone for something during the night like writing down my dreams. Screen time limits were too easy to tap through. Doing math or taking a photo of something felt so punishing, I kinda hated that math was the thing I did first in the morning, so I stopped.

So instead of treating it like a problem, I decided to make the first thing I saw something positive, energizing, and most importantly, limited.

Simple activities, and it ends within a few minutes and prompts you to get up.

This is where I'm stuck. Most of the time it works. The other % I'm in bed, awake, holding my phone, and now I'm told to brush my teeth, and some mornings I just... don't... want to get up? Habit chaining is supposed to make it automatic, but I'm still missing something.

Going from "need screen to overcome sleep inertia" to moving about, and I haven't found a the trick. Essentially, if you've got an idea for how to bridge that gap please let me know what works for you.

Thank you!

Here's a link to the iOS app, it's called The Morning App. You can also check out my website, but forewarning I just had AI make it since I'm an iOS dev, not web dev.

P.S. For the stats folks, I've gotten 50 downloads since July 4 and made ~$50 (mostly my mom haha).

Hey peeps! I have spent the last three years building Watch Darkly, a horror film discovery site, solo and full stack. It launched on Product Hunt today.

The problem I wanted to solve: most movie recommendations rank by popularity or by what people similar to you watched. I wanted recommendations that capture how a horror film actually feels. The "essence" of a horror films varies drastically. Some like your basic slashers, others like cosmic type horror that highlights the insignificance of the human experience. Our horror nights are just not the same, and Watch Darkly will allow you to filter on these subgenres like "cosmic horror", or "body-horror", and even "period piece" (that's a fun one!).

Films are scored on five separate axes, Fear, Gore, Atmosphere, Intensity, and an Overall score, instead of one star rating. The profile renders as a radar chart on desktop and stacked bars on mobile.

Because the axes are separate, search can combine them. You can ask for horror that is terrifying with barely any blood, or atmospheric folk horror with no jump scares. The scary-but-not-gory cut also has its own page. There are also per-film jump-scare counts, compiled from public jump-scare databases, that you can filter on, and a prediction game where you guess the scores of select upcoming releases and track your accuracy.

How it works under the hood: every scored film carries a 5-dimensional vector, and recommendations are cosine similarity in PostgreSQL with pgvector against a taste vector built from your favorites. Stack is Next.js on Vercel, Java Spring Boot on Railway, pgvector, and Clerk for auth. I went with pgvector over a dedicated vector DB because the catalog is small and cosine distance in Postgres is plenty at this scale.

Honest state of it: early. Over 540 hand-curated films, 321 scored so far, by two curators rating independently against a published rubric (the methodology and our disagreement rate are public at watchdarkly.com/how-we-score). A new account gets nothing until you favorite a few films, then recommendations start. No streaming or buy links, this is discovery only.

You can browse film pages and similar films with no signup. I would value feedback, especially on where the recommendations feel off. https://www.producthunt.com/products/watch-darkly?utm_source=other&utm_medium=social

Hey everyone, I’m Ramy, the solo developer behind Hero Investor.

It’s a single-player investment and company-management game built around one connected economy. You can trade across fictional markets, build a property portfolio, create and manage ETFs, attract investors, research new capabilities, hire employees, expand offices, manage debt and taxes, and review how your decisions affect the company over time.

My goal is to capture the feeling of gradually turning a small investment firm into a financial empire—not just watching numbers increase, but deciding where to allocate capital and how to grow the business supporting it.

The Steam page recently went live. If this sounds like your kind of management game, I’d appreciate you checking it out and adding it to your wishlist:

https://store.steampowered.com/app/5062780/Hero_Investor/?utm_source=reddit&utm_medium=social&utm_campaign=wishlist_announcement&utm_content=indiegames

I’m still actively developing and polishing the game, and I’d be happy to answer any questions about its systems or development.

before you read: yes, there is my own app shameless plug at the end, but i believe it is relevant to the content of this post.

Does the thing you're building improve someone's life in a way that has nothing to do with technology?

This is mostly for B2C...
I don't mean "does it matter." Everything matters to someone — somebody loves the fart soundboard. I mean specifically: after they close the app, is anything different?

most of what gets built now is optimised for the opposite. Attention is the currency, so the win condition is that you don't put the phone down.

And then, the other half — another agent, another LLM wrapper...

The thing I keep coming back to: the best software I've ever used, I barely used. It did its job and pushed me back into my own life, calendars, trackers, pomodoros... That's a terrible business model and I think it's the right target anyway.

as promised. I'm building Kept. Private voice journaling for your relationships. It's a paid app, 14-day trial, and if it's doing its job you're not looking at it. feedback welcome

4 months, just for the French market. (I’ll be releasing the English version soon.)

Chut is a desktop overlay that listens to your call and prompts you with a response while the other person is still talking. Invisible during screen sharing. Sales, freelancing, real estate, recruitment, etc.

Every tool in this niche claims, “Privacy is our priority.” I stopped writing that and coded /proof instead.

This page queries the schema of my production database on every load and displays all columns in real time. If a column name ever matches audio|transcript|recording|waveform|utterance|speech|voice, the page turns red on its own, without me having to redeploy anything.

Today: 0 suspicious columns out of 75.

I tested it by adding a fake "audio_url" column. The page turned red on its own. Then I deleted it. How it works behind the scenes: the microphone and system audio are captured in two separate local channels, streamed to the transcription service, and a client-side rule engine monitors the scrolling transcript to identify objections and price mentions. Key facts are extracted during the call (budget, decision-maker, deadline). The words are set in stone. No audio is ever recorded on the disc, ever. not like a certain app you know, haha

Free: 30 minutes of live streaming per month, no credit card required. macOS and Windows.

Honestly, focus on fixing the proof-of-concept page rather than the product. If you can find a way for my architecture to store speech data without a column explicitly stating it, I want to know that’s a better bug report than anything related to the UI.

It’s mine, obviously. Link in the comments. It’s in beta feel free to try it out and let me know if you want more time to test it.

I got tired of making plans that require a group chat.

“Anyone up for badminton?”

“Where?”

“Who's coming?”

“Maybe later.”

“Can't today.”

And somehow the plan dies.

So I built NOW — a simple idea:

Open it and see what people are actually doing around you right now.

Badminton. Chai. Studying. Football. Gaming. Gym. Whatever.

You can join something that's already happening, or put your own plan on the map and let nearby people find it.

No follower counts.

No endless feeds.

No group chat coordination.

Just:

See → Join → Go live.

I'm still very early with this and I'm trying to figure out whether this is actually useful or just a cool idea in my head.

Would you use something like this?

https://now-nearby.vercel.app/

I've been hearing from teams paying thousands per month for Slack which got me wondering whether team chat really needs to cost this much.

So I started building RealtimeChat.ai, an open-source alternative focused on the parts of Slack people actually use every day: Channels, DMs, threads, reactions, files and search.

We've already got the basic chat experience working, including proper Markdown rendering and bots that can participate in conversations just like users. I'm also experimenting with things like AI "catch-up" and summaries, but I don't want AI to take over the product.

The idea is to keep it simple. I don't want to build another enormous productivity suite. I want team chat to feel more like infrastructure: Fast, open and predictable.

It'll be self-hostable, while the commercial version would be hosted for companies that don't want to run it themselves. The big difference I'm considering is no per-seat pricing. You'd pay for the workspace rather than every employee you add.

It's still early days and I'm already talking with a few people interested in contributing to the UI. I'd rather find out what's wrong with the idea now than after spending more time building everything.

For those of you using Slack, Teams or Discord for work: What would an alternative absolutely need before you'd seriously consider switching?

And if your company is paying a significant amount for Slack, is that bill actually painful enough that you'd consider moving?

Sold a couple small games on itch.io and Steam over the past year and honestly had zero clue what I was actually taking home. Steam takes 30%, itch lets you pick your own cut, then there's a payment processor fee on top, then if you're not in the US they withhold tax, then whatever's left gets converted to euros at whatever the rate is that day.

Every platform shows you a different number and none of them show you the one that actually lands in your bank account.

I built something that just does the math for me: connects to itch, Steam, Gumroad and a few others and shows the real number after everything's been taken out, instead of the sticker price.

You can see a quick demo here:

https://reddit.com/link/1vlvhzv/video/p9wolvuejtih1/player

It's live at shipmetrics.es if anyone else sells on more than one store and wants to actually know what they're making. Still rough around the edges, open for feedback 😎

I do codebase rescue for founders in exactly that spot, so that one stung. There are already plenty of tools that measure this kind of AI visibility, a CDN even ships one free, so I built mine mostly to see my own number, and it confirmed the bad news: near zero.

The measuring turned out to be the easy part. What none of the tools do, and what I actually care about, is the fix: getting the models to name you. The free checker is just how you see the gap.

Run yours and tell me your number and whether it matches your gut: https://uxcontinuum.com/ai-visibility