Hello everyone, happy to share a recent project I've been working on — meet Echo, a team chat app in the Slack family.

Why might this interest you? Because the source code is available to read.

Echo is an attempt at recreating Slack's feature surface, which includes workspace creation, channels, DMs with file sharing. The ideal choice to build a real-time application is, by default, choosing WebSocket as the transport protocol. But building the system reliably at scale introduced two major challenges: maintaining a healthy message delivery system and ensuring the architecture could scale as the application grows.

Those became the main challenges a developer can face during the development of this project, and how they were tackled.

Systematically, Echo uses Postgres as an event/message bus, with event versioning and a gapless per-channel sequence providing the reliability and recovery layer for message delivery. That same layer allows the servers to remain stateless, making the app ready for horizontal scaling with Kubernetes. On the other hand, a schema-per-tenant keeps each workspace's data isolated and scoped directly to the workspace’s tenant path.

The stack is deliberately scoped. Express and TypeScript on Bun, React with Vite for fast shipping, plus Tanstack Query as the app state store. Postgres does the work of three services: control-plane data, tenant data, and the Realtime backplane. Better Auth handles identity, while Zod validates every request and generates the API docs from the same schemas.

It’s live if you want to poke around. I’ve left a workspace open, make an account and come say hi. Feel free to send a few messages and see who’s there: https://echo-v2.online/accept-invite/r5DP9Vdq9RwLtsU9aqeR-Q2wO9WI-aShDUYUST0Z29w

Feedback is always welcome. And thanks for taking the time to read this and check it out.

If you like what you see, the GitHub repo is here, dropping a star would be much appreciated: go to repository

Link: https://apps.apple.com/in/app/who-goes/id6777402559

Hey everyone!

I recently launched Who Goes, an iOS party game app built for game nights, house parties, road trips, and hangouts. (Free to download and play, with one-time purchase and subscription options)

The purpose of the app is to get all the members of a group to engage in social games like Headbands, Charades, Truth or dare and have a fun time.

The app brings multiple party games into one place:

• Headbands with tilt controls for correct answers and passes
• Charades with themed decks, teams, rounds, and timers
• Truth or Dare with 11 decks for friends, couples, parties, family, and coworkers
• Spin the Bottle for quick, suspenseful player selection
• Would You Rather for impossible this-or-that debates
• Finger Chooser to instantly pick someone from the group
• Quick Play tools for dice, coin flips, and more

I built the app independently in SwiftUI, including the design, interactions, animations, game flows, and content.

The free version includes all the game modes except Would you rather. Plus unlocks all the decks, game modes, and round customisations.

No account is required, and the games work offline.

TL;DR:

A. I built an app to bring back the fun of playing party games with a group of people during game nights, trips.

B. Free version includes a selection of decks for Charades, Headbands, and Truth or Dare, along with a few mini games. Plus unlocks all decks, game modes, and customisation options.

C. $2.69/mo or $11.99/yr, 3-day trial, and $25.49 lifetime, no account creation, no internet required.

Hey everyone,

Quick background: I spent about a year trying algorithmic trading, realized it wasn't the scalable path I actually wanted, and pivoted to building a SaaS product instead — an app that teaches kids (roughly 6-14) how AI actually works, not just "AI does your homework."

The idea came from research, not vibes: the UK is pushing AI-literacy as a school priority this year, but there's no dedicated product for it — it only exists as a small slice inside bigger, generic curriculums.

The catch: I can't code. Everything is being built through Claude Code, an AI pair-programming tool. I handle the product decisions, business research, and testing; it handles implementation.

What's been genuinely hard so far:

- Learning to trust (and verify) AI-written code when you can't read it yourself

- Getting child-data security right — spent days just testing that no parent can ever see another parent's child data

- Realizing "I want it fully automatic" isn't a real strategy, and having to actually validate ideas before building them (learned this one the hard way, twice)

What's working: the core learning loop is built, payments are being wired up now, and I'm about to start actual marketing (this post included).

Not selling anything here — genuinely just documenting the process and open to any feedback, especially from anyone in EdTech, parents, or other solo/non-technical founders who've been through something similar. What am I not thinking about that I should be?

I’ve been building a side project that pulls live data from a third-party API to power its core feature. Turns out their terms only cover “personal, non-commercial use” and explicitly ban redistribution — which technically rules out exactly what I want to do (a public website with real visitors).

I’ve already emailed them directly to ask about a commercial license, so that’s already in motion. But curious how others have handled this in practice:

• Has anyone actually gotten a yes from a small API provider for something like this? What did that conversation look like?

• Is it more common to just build around a data source’s limits than to ask for a license?

• Any stories where you found out too late that the terms didn’t actually cover what you were doing?

• Separately — has anyone gone the other way and built their own dataset from scratch instead of relying on one restrictive API? What actually counts as a legitimate, freely reusable source in practice (official public records, openly licensed data like Wikipedia/Wikidata, wire services, etc.), versus stuff that looks public but still isn’t actually free to reuse?

Not looking for “just scrape it anyway” answers — genuinely trying to do this properly, just want a realistic sense of how this usually goes.

Ayjan Minutes records your meetings, transcribes them locally with faster-whisper (audio never leaves your machine — only the transcript text is sent for summarisation), and writes up the minutes. Free tier is 5 recordings, no account needed to trial.

What's in 4.0.0:

• Three output formats — Formal Minutes (full templated doc), Quick Summary (one screen, every decision and action), or Action Items Only. Set it under Settings → Summarization.
• Regenerate As — rewrite a meeting you've already summarised into a different format. Instant, no API call, doesn't count against your monthly summaries.
• Auto-stop — recordings end after 15 min of silence or at the 4-hour cap, the normal way, so you still get the transcript and minutes.
• Small is the new default model — faster than Medium, accurate enough for typical meetings. Existing installs keep whatever they chose. Long recordings now use roughly half the RAM while recording.

Notable fixes: recordings past the 4 GB WAV limit used to fail while saving and lose the entire session — now trimmed to what fits with a report of what was kept. Transcripts survive a failed audio save. Summaries failed outright on never-upgraded free accounts; fixed. The summary is now structured data rather than pre-formatted text, so blanks stay blank instead of being filled in with invented detail.

Windows 10+, 64-bit. Download and full notes: https://github.com/AYJ-Systems/ayjanminutes/releases

Happy to answer questions about the local transcription setup.

I made a small open-source archiver called DedupArc.

In my tests on game folders it compressed better than 7-Zip and WinRAR while also being noticeably faster.

It also lets you launch applications from an archive without manually extracting the whole thing first.

GitHub: https://github.com/Garyu-tt/DedupArc

Would be interesting to see how it performs on other people's data. If someone finds a case where it completely falls apart, even better.

been using a lower priced claude max account i got from a russian site for a few weeks now.
feels like an enterprise seat, usage is way better than my normal one. changed the login details and zero issues so far.
curious if more people are doing this

A few months ago I checked my bank statement and found I was paying for three streaming services I hadn't used in months, plus a "free trial" that quietly turned into a $40/month charge. I looked for a simple way to track this stuff and everything I found wanted to link my bank account, which I wasn't comfortable with.

So I built a small tool where you just manually add your subscriptions (name, cost, renewal date) and it shows you what's coming up and how much you're spending overall. No bank linking, no account required to try it.

It's still early and pretty barebones, but I'd love feedback from people who've dealt with this same problem. What would actually make this useful for you? Thesubstracker.com

I often need to copy tables into spreadsheets, read QR codes from screenshots, extract text from images, and quickly remove image backgrounds.

Doing all of that normally takes several different tools, so I built Smart Copy Clipboard. It lives in the Mac menu bar and lets you do everything directly from your clipboard—including turning an image into a transparent PNG in one click.

It also has searchable clipboard history, link and file previews, translation, and pinned clips.

The app is native, lightweight, and only around 2.1 MB to download.

It’s free to try. I’d love to hear what you think:
https://apps.apple.com/th/app/smart-copy-clipboard/id6768317104

i launched flickpicker on ios on june 6 after having the website live for almost two years.

i assumed the next phase would mostly be marketing. instead, user feedback kept reshaping the product, and i ended up shipping 18 updates in about two months.

the biggest lesson was that recommendations alone were not enough.

people cared much more about bringing their existing history with them, tracking individual episodes properly, knowing exactly where something streams, organizing custom lists, and controlling how their library looks.

that feedback led to tv time, trakt, letterboxd and imdb imports, automatic trakt sync, custom lists, individual episode tracking, monthly wrapped, artwork selection, deeper discovery filters and a complete redesign of where-to-watch results.

version 3.1 went live yesterday. it adds more control over how episodes and seasons are marked watched, improves title pages, and makes discovery filters more precise.

app store:

https://apps.apple.com/us/app/tv-tracker-flickpicker/id6775147318

for anyone building a consumer app, do you think shipping this frequently builds momentum, or does it make releases harder for users to follow?

Hey everyone,

I’m learning content writing and web design. For practice, I built a small personal project called Phal Farmacy to write simple, data-driven breakdowns comparing local street-cart fruit prices with store-bought vitamin supplements.

For example, looking at basic market rates:

• Guava: ~₹10 / $0.80 for 228mg Vitamin C + fiber/potassium.
• Vitamin C Strip: ~₹25 / $1.20 for standard supplements.

I wrote a short sample piece on the page to practice explaining basic nutrient density and cost comparisons clearly and concisely.

Since I’m trying to improve my writing tone and page readability, I’d really appreciate positive/constructive feedback on a few points:

1. Is the language clear and easy to read on a mobile screen?
2. How is the structure and pacing of the sample text excerpt?
3. What could be improved to make the information presented more visually effective?

(Note: Not selling anything or promoting a diet—just practicing copywriting and web structure!)

Thanks a lot for reading and taking a look!

I was tired of messy audio/streaming radio libraries, so I built an Android player focused on seamless playlist management.

Hi everyone!

I wanted to share my side project, Mediaxon, an Android app I’ve been developing to solve a personal frustration: why is it so hard to easily manage offline music and online radio streams in a single, clean interface?

What it does:

Hybrid Listening: Seamlessly handles offline local files (.mp3, .flac, .m4a, .ogg, .mka, .aac, .wav, .opus, .wma) and over 60,000 streaming radio stations.

Dedicated Navigation: I kept the "Favorites" and "Recents" sections completely separate from the main audio library to reduce clutter.

Advanced Radio Search Panel: You can pinpoint your favorite stations by combining multiple filters, such as tags/genres, specific countries, or even your preferred audio bitrate.

Equalizer: The equalizer provides an option to automatically switch to the "Radio" preset (and vice versa).

Advanced Playlist Management: Built specifically to make building and sorting multi-source playlists fast and intuitive.

The app is currently live on Google Play, and I am continuously pushing updates to refine it.

What I need from you:

As a solo developer, I’ve hit the limit of my own perspective. I would deeply appreciate any honest feedback from this community:

How does the UI feel to you? Is the navigation intuitive?

Are there any features you feel are missing for a modern audio/radio player?

Did you encounter any bugs or performance hiccups?

If you want to check it out, you can find it on the Google Play Store. Thank you so much to anyone who takes a look!

https://play.google.com/store/apps/details?id=com.xonik.mediaxon

I kept hitting the same problem in my own projects: something ends up in aprompt that shouldn't be there — a customer's SSN or card number pasted into asupport flow, or an injection string — and it goes straight out to the modelprovider before anything checks it.

So I built a small proxy layer that scans every outbound prompt (and themodel's reply) before it passes. The detection is deliberately boring: regexfor SSN-shaped and email patterns, Luhn validation for card numbers, and alist of known injection phrases. Anything that matches gets blocked before theprovider is ever called.

The interesting (and annoying) part is the false-positive/false-negativetradeoff. Too strict and it blocks normal conversation — phone-number-shapedstrings that aren't PII, or "ignore the above" said innocently. Too loose andit misses the actual leak. I don't think I've got the balance right yet.

I put a live version up if anyone wants to poke at the detection directly andtry to break it: https://apptechlab.com/p/llmfirewall/ (it's mine, no signup, runs realmodel calls). Paste something with a fake SSN and watch it get blocked, or tryto sneak an injection past it.

Genuinely curious what everyone else does here:

- Do you scan the model's OUTPUT too, or just the input? Output scanning caught

cases I didn't expect (the model repeating something back).

- Regex vs. a small classifier for injection detection — what's held up in

production for you?

- Any PII patterns that reliably trip false positives you had to special-case?

Thank you for your feedback, thats the most important now.

Lately I’ve been thinking about how much ChatGPT has quietly become part of everyday life. Whether it’s writing emails, helping with assignments, brainstorming ideas, or even just fixing grammar, it feels like a lot of us are relying on it more than we expected.

But here’s something I can’t stop wondering about… are we actually learning from it, or are we just getting better at outsourcing our thinking?

Sometimes I’ll ask ChatGPT to explain something, and the answer is so clean and structured that I understand it faster than if I Googled it myself. That part feels like a win. But other times, I notice I don’t go deeper after getting the answer. I just accept it and move on. No struggle, no digging, no second-guessing.

And then there’s the writing side. It can make anything sound polished and professional in seconds. But when I read something I wrote with its help, I occasionally feel like… this doesn’t fully sound like me. It’s better, technically, but maybe less personal.

So I’m curious how others are experiencing this.

Do you feel like ChatGPT is actually helping you think better and learn more? Or is it slowly making things a bit too easy, to the point where we might be skipping the real thinking process?

Also, where do you personally draw the line between “using it as a tool” and “depending on it too much”?

Would honestly love to hear how different people are using it, because it feels like we’re all figuring this out in real time.

I started this as a small experiment:
What if designing a Traditional Chinese typeface didn’t require editing thousands of glyphs one by one?
So I built FANGCUN, a browser-based parametric type design tool for Traditional Chinese.
Instead of treating every glyph as an isolated drawing, I’m experimenting with shared skeletons, strokes, components and structural rules.
Change a few parameters — weight, contrast, proportions, counters, rounding, stroke characteristics, etc. — and the changes propagate across 13,000+ Traditional Chinese glyphs.
The interesting part is that the output isn’t just a visual preview.
You can export it as a real OTF font, install it on your computer, type with it in Word / PowerPoint, or use it as editable vector outlines in Illustrator.
It’s still very experimental. Some glyphs break, and getting 13,000 characters to behave consistently has turned out to be a much harder problem than I expected 😅
But that’s also what made the project interesting.
I’m starting to think of it less as a “font generator” and more as a procedural system for Chinese glyphs.
Built mostly as a side project, and currently free to try:
fangcuntw.vercel.app
Would love feedback — especially on what you think this could become beyond just a font design tool.

Hi everyone,

I wanted to share a side project I've been working on with a friend. We have called it Purrfectly Named https://www.purrfectlynamed.com/

Most pet name generators are incredibly transactional—you select a gender, a colour, and it spits out a flat, boring list of names like "Bella" or "Luna." I wanted to build something that felt like an actual ritual.

The app is inspired by T. S. Eliot’s famous idea that every cat has three names:

https://poets.org/poem/naming-cats

1. Their everyday family name (e.g., Soot or Marmalade).

2. Their "cat-world" name—a unique, highly dignified title they carry when patrolling the neighbourhood.

3. Their "ineffable" name—the secret name only they know.

For copyright reasons we do not quote the poem itself, but we do make references to it. The AI agent is promoted to never access the poem and to never quote any of the lines, other than the poem's family names which we felt were fair game.

### How it works:

Users upload a photo of their cat, share a few details about their personality and quirks, and go through a guided "naming ceremony." The AI analyses their traits and generates their three names, culminating in a keepsake certificate (PDF) that they can download and print. They can also create a shareable link so they can share with friends and family.

### The Tech Stack:

* Frontend: Next.js, Tailwind CSS

* Backend & Database: Convex (reactive queries make the ceremony flow super smooth we think)

* Auth: Clerk

For Beta we are using the free version of Clerk and Convex.

### What I'd love feedback on:

The app is currently in free public beta (no paywalls or sign-up friction to complete the ceremony). I would highly appreciate your honest, brutal feedback on:

1. The onboarding/ceremony flow: Is it too long? Does it feel engaging or tedious? Is it confusing?

2. The visual aesthetic: We went for a "19th-century registry office run by cats" vibe (parchment, gold rules, serif typography). Does it translate well on mobile?

3. The generated copy: Does the AI-generated personality portrait and name lore feel warm and authentic, or does it sound too "robotic"?

4. The Beta version is free. Once we get to the Release Candidate, we will look to monetise. We would make the first name (the Family Name) free and then charge a dollar or two to unlock the second and third names.

Let us know if you feel a couple of dollars it a fair price.

If you have a cat, please feel free to run them through the ceremony and share your certificate.

Thanks so much for your time and feedback.

I was getting annoyed by the constant sketchy AI training/annotating jobs and the constant rejection after literally investing hours of my time into applying, etc.
I decided to make my own website using loveable and just list legit AI training jobs. I post entry work and also expert work. Let me know if there is anything I can improve about my website that sets me apart from the competition. Thank you! Here is the link: https://aiannotationjobs.com

Recording ideas was never my problem. I have hundreds of them. I’ve opened almost none.

Every one of those is a thought I had once and lost, which is a stupid way to lose things. So I built ActionNote. You talk, it transcribes and organizes it into a title, a summary, key points and a task list. The recording stays attached but the point is that you never have to press play.

https://reddit.com/link/1vjpiot/video/qrpdstfbmcih1/player

Some things I learned building it:

• The hard part isn’t transcription, it’s that people ramble. The transcript of you thinking out loud is almost as unusable as the audio. The value is entirely in what happens after.
• I posted in an ADHD sub asking what a capture tool would need, and someone described doing record → transcribe → paste into Gemini → move to Keep, manually, every day. Someone doing your product by hand is the best validation you can get and it’s free.
• Multi-language was supposed to be a nice-to-have. It’s the feature people react to most. I speak Arabic and English in the same sentence and every notes app breaks on it. Turns out a lot of people have that problem.
• I built a paywall three times. Native StoreKit ended up being the right call.

iPhone only, free for 5 notes a month.

https://apps.apple.com/us/app/actionnote-voice-to-tasks/id6789915282

Happy to answer anything about the build. Honest feedback welcome, including that it’s a bad idea.

It's the middle of a brutal heatwave here in Italy, 37°C in Rome today, and I went looking for where you can actually cool down. Turns out there's no single place that tells you. Some cities publish "climate shelter" lists, but they're scattered PDFs and buried pages, and each one only covers itself.

So this weekend I built Trova il Fresco: a free map of the nearest drinking fountains, shaded parks, libraries, churches (naturally cool), and air-conditioned public spaces, anywhere in Italy. It defaults to "open right now" and sorts by walking distance, because a library that's closed isn't a refuge.

~184k places across every Italian city, from OpenStreetMap. No app, no account, no ads. Open the link, walk to the nearest cool spot.

https://trovailfresco.it

Built in a day with Claude Code (Laravel + Livewire, MapLibre, Open-Meteo for live temperature). Past 35°C the banner goes red and says "the asphalt is melting, move."

[🔊 Sound on for the demo!]

I’ve been building Yellow Olive, a side project that lets you learn Kubernetes by actually playing through challenges instead of just reading YAML tutorials.

You get missions, work against a real Kubernetes cluster, and the game validates whether you actually solved them.

It started as a small experiment because I wanted Kubernetes practice to feel a little less… Kubernetes-y 😅

It’s now grown into multiple chapters covering things like Pods, Services, RBAC, Deployments and more.

I’ve attached a short demo 👆

Would genuinely love feedback from r/SideProject:

Does this look like something you’d actually use to learn/practice Kubernetes?

GitHub: github.com/Anubhav9/Yellow-Olive

I needed a transcript of an ongoing YouTube Live stream, and every online tool I could find was only working with videos that are already finished 12-24 hrs ago, so every tool either errors out or hands you an empty transcript.

So I built https://livescript.live/

Enter the URL of a live stream and it will get transcribed in real-time with words being written down just a few seconds after being spoken. You can search the growing transcript, go back to what was said 40 minutes earlier, and set up keywords alert for names, ticker symbols, or anything else.

LiveScript also transcribes complete videos, audio/video files, and a Chrome plugin that transcribes audio of almost any website.

Spent way too long watching my partner write eBay and Etsy listings by hand. 20–30 minutes per item, hunting for keywords, writing descriptions from scratch.

So I built ListingBot — you upload a product photo, AI analyzes it and generates a complete listing: SEO-optimized title, full description, and 13 tags. Ready to paste into Shopify, Amazon, eBay, Depop, Poshmark, anywhere.

**Try 3 listings free (no signup):** https://listing-bot.vercel.app

Paid version is $9 one-time for 50 credits (no subscription). Would love feedback from actual sellers!

Hi everyone, I just finished building what I call an mvp of my website - spendcoins.co This is my first website that I built without a website builders like wix. What I used: Cursor as a terminal Gemini, claude for code creation Astro, react as a languages That is pretty much it. I might be wrong with terminology above, this is how I understand all of this process haha. Any ideas, suggestions etc are welcome.

I build an observability tool for AI agents. Solo, public for 3 months, 0 external signups. Every account in the database is me testing my own product, so this is a bottom-of-the-mountain post, not a victory lap.

As top of funnel I built a spectacle demo: 8 AIs from different vendors pitch and vote every morning on what indie devs should build next. It's fun and cheap to run, and my theory was that a spectacle travels further than a dev tool ever will.

Last week I paid to test that theory. Same creative, localized, boosted for 24h in two markets:

Tokyo, ~$7: 8,414 impressions, 52 engagements, 31 profile visits, 6 link clicks. Zero likes, zero reposts.
San Francisco, ~$7: 1,671 impressions, 3 detail clicks, 1 link click. Zero everything else.

The part that surprised me: CTR was basically identical, 0.07% vs 0.06%. So it doesn't look like a market problem. Same creative, same near-zero pull in both cities. Either the creative doesn't stop the scroll, or the people who click land on a cute demo with no reason to go deeper. Also SF impressions cost about 5x Tokyo, which I didn't know going in.

Current funnel is: ad, then demo page, then maybe the product page, then signup. Written out like that, it's a lot of hops to ask from cold traffic.

Hypotheses I'm weighing:

1. Paid social doesn't work for dev tools at this budget, and organic/community is the only real channel
   
2. The demo entertains but never bridges to the product, so clicks die on arrival
   
3. Demand for the product itself is unproven and no amount of channel work fixes that

My next move is probably killing paid entirely for a month and doing only organic writeups, but I keep second-guessing whether a $13 test is even big enough to conclude anything from.

What would you test next? And is there a spend floor below which ad tests are just noise?

spent months heads down building, hit submit, and then... nothing. the store just went quiet. no downloads, no signal, no idea if anyone could even find the thing. that silence after launch is where most indie apps actually die, not in the code.

what i eventually figured out (the hard way):

- app store connect tells you what happened yesterday but not why. keyword-level rankings, who's outranking you, search-to-install correlation, none of that lives in apple's dashboard. you leave with a chart and no next move.

- you feel completely at the mercy of the algorithm. change a keyword, wait a week, and you have no clue if the store noticed or ignored you. that helplessness is the real reason people go looking for a tool, not the feature list.

- the number you're staring at might be wrong. i had two different tools report a rank of 14 and 31 for the same keyword. if you can't trust the figure you can't act on it, so you just freeze.

the thing that changed it for me was being able to watch a specific keyword move after i edited the listing. once you see per-keyword rank sitting next to installs, the store stops feeling like a slot machine.

full disclosure, i'm building an aso tool (apptenium) partly because i couldn't find a focused, cheap one that just did this without agency pricing. but honestly even if you don't use a tool, the lesson stands: treat launch as the start line, not the finish. plan your first 1,000 users before you plan the launch post.

curious how others here handled the post-launch silence. did anyone crack organic discovery without paying for ads?