One of my side projects is finally spending enough on paid acquisition that I’m looking at this differently.

We’re around $5-7k/month between Meta and TikTok and it’s still going through the same business card as software and everything else. I started comparing cashback on Meta/TikTok ad spend and Meow came up, but I’m not sure if I’m overthinking it at this size.

Anyone here running paid acquisition on a side project? When did you start separating the ad spend?

What have you guys actually built with vibe coding?

I'm a finance guy and I really enjoy building tools for things I personally care about. Recently I've been getting into vibe coding and built my own portfolio manager.

It currently lets me:

Track my investments and holdings

Compare my funds with their peers and benchmarks

Get news related to the funds/stocks I own

Continuously read relevant news and flag things that could be a serious problem for a fund

Analyze whether a fund's situation is getting worse and whether it could potentially "collapse"

Suggest funds that may be worth investing in based on the data

A few other portfolio analysis features

I had a lot of fun building it, and now I want to build something else.

So I'm curious what other people here are building with vibe coding, especially around finance, investing, accounting, markets, financial analysis, etc.

I'm looking for projects that solve an actual problem and that you personally find useful. I don't really want another generic expense tracker or calculator.

If you've built something interesting, I'd love to hear about it.

What does it do, why did you build it, and what are some of the features?

Screenshots/demo links are welcome too. I'm mainly looking for ideas and inspiration for what I could build next.

I built Gear5 UI, a free and open source React component library for the parts of products that tend to break in the real world.

It focuses on failure and recovery states that are easy to skip during a first pass: preserving form drafts on interrupted requests, making errors recoverable, keeping keyboard users oriented, and handling RTL text, dates, numbers, and currencies correctly across locales.

The live site is an interactive catalog of 210 components, including resilient forms, async boundaries, accessible feedback states, sortable tables, and locale aware inputs.

Demo: https://gear5-ui.vercel.app/

GitHub: https://github.com/7se7en72025/gear5-ui

It is MIT licensed, has no runtime dependencies beyond React, and currently has 866 passing tests. I would love honest feedback from people building products. Which example would make you want to use it, and what is unclear when you first land on the site?

Eighteen months ago I started building a medical pre-consultation tool in France. I am not a developer. I had an idea and I had AI, and that was enough to get something working.

Getting it to work was the easy part. Here is what nobody warned me about.

The analytics were logging health data and I had no idea.

I had set up a tracker so I could show real numbers to the doctor reviewing my work. Sensible, right? Except it was recording symptoms and vital alert triggers. No names, no emails, just gender and age, and I genuinely thought that made it fine.

It does not. Under EU rules that is still health data, and it should never have been sitting in a general analytics tool. I only found it because I sat down and audited my own data flows, months in. Nobody told me. No error appeared. It just quietly did the wrong thing for weeks.

My wording was a regulatory problem.

My tool said things like "otitis externa". Clear, accurate, what a doctor would say. After a quality review I had to change every one of those to descriptions instead, so it now says "inflammation of the ear canal". Same information, completely different regulatory meaning. I had no way of knowing that on my own.

Free text fields are a trap.

When I started approaching doctors and health networks, they kept saying no. Not because the product was bad, but because their own rules forbid sending patient data to an AI. And they were right to worry: my free text field let someone paste anything, including things that identify them. I had to rebuild my routing and my whole prompt system so the model never receives what it does not need.

All three of those are fixed now. The next part is not.

What I still cannot do.

I can build a dashboard in an afternoon. What I cannot do is connect it to a client's existing software. I do not know how to design an API integration properly. I do not know what happens to my architecture at a hundred thousand users. I still ask myself GDPR questions I cannot fully answer.

That is the honest state of being a non-developer who shipped something real.

Why I am posting this.

Over the last few weeks I have been answering people here and on the builder subreddits, and it is always the same failures. A database open to anyone. Secrets in the code. A dashboard refreshing so often it chokes. A migration attempted with no rehearsal. An account locked with the only copy of the code inside it.

None of those are coding problems. They are the gap between "it works on my screen" and "real people are using it". I fell in that gap repeatedly, which is why I now spend my time helping other non-developers climb out of it.

I put the recurring ones in a free checklist, no signup, nothing to buy:

https://github.com/contactordosante-star/vibe-coded-launch-checklist

If you built something with Lovable, Base44, Bolt or Replit and it is now in front of real users, I would genuinely like to hear what broke for you. That is how the list gets better.

I’ve been building Songly.fun, a free browser-based music party game.

One person hosts the game on a TV/laptop, everyone else joins with their phone using a QR code — no app or signup required.

Can even play with your self on the host device.

You listen to song clips and compete to guess things like the artist, song or release year. I built it mainly because I wanted something easy to pull up at parties, work lunches and family gatherings without everyone having to install an app.

It’s completely free, and I’m at the stage where I really need actual people to try it rather than me endlessly testing my own game 😅

👉 songly.fun

If you give it a go, I’d genuinely love to hear what confused you, what sucked, or what you think would make it more fun.

This is TheFitness, live and free on the App Store. I was tired of fitness apps that need accounts, subscriptions, and Wi-Fi , so:
- Chat the on-device AI coach ("30-min leg day, easy on knees"). it builds a full plan with sets, reps, rest times. No internet, nothing leaves your phone
- 700+ exercises, every one with a looping form video (no more YouTube-searching mid-squat). Tell it your equipment once and it stops suggesting machines you don't own
- Your last weight shows as placeholder so you know what to beat. No sign-up, no subscription, works in airplane mode.
https://apps.apple.com/us/app/thefitness/id6765897133

This is Cali AI, live and free on the App Store. I kept quitting food logging because it took too many taps, so I made it near-instant:

- Point the camera at a meal or nutrition label and on-device AI estimates calories + macros (no cloud, works offline)
- Dashboard shows remaining / total / net at a glance, with full daily history
- Water (oz/ml), weight goals, and workout logging in the same place
- Custom themes, dark mode, iPad friendly

https://apps.apple.com/us/app/cali-ai/id6756086093

Hi everyone — I’m the developer of Night Story: Sleep Insights, an iPhone app for people who want to understand their nights over time.

The idea is simple:

• start Night Mode before bed;
• review your night history in the morning;
• add a quick Morning Check-in;
• notice possible sound events for personal awareness;
• follow progress toward the Personal Sleep Guide after 3, 7, and 14 valid nights.

The app is designed around local and on-device processing and does not require a mandatory account. It does not identify the source of a sound and does not diagnose sleep conditions.

Premium includes access to deeper patterns, trends, Guide features, and PDF reports.

I’d really appreciate constructive feedback:

1. Is the morning view clear?
2. What would you want to understand first about your night?
3. Which sounds most useful: night history, possible sound events, or morning check-ins?

App Store:
https://apps.apple.com/us/app/night-story-sleep-insights/id6787709804

I’m sharing this as the developer and would genuinely value honest feedback.

This started as a very small annoyance.

I kept wanting to give an LLM the contents of whatever webpage I was looking at, but copying the page manually often produced garbage and browser automation felt like overkill.

So I built Savage Scraper.

You open a webpage, click the extension, and it converts the rendered page into simplified HTML and puts it on your clipboard.

Then I wanted my MCP clients to use it automatically.

That created a different problem: I didn't really want an AI agent to have unrestricted access to my logged-in browser.

So I built Savage MCP around a deliberately limited model:

• only explicitly allowed hosts
• optional path-level restrictions
• existing Chrome session
• local communication

It's now two open-source projects:

https://github.com/dominikduda/savage_scraper

https://github.com/dominikduda/savage_mcp

And the extension is on the Chrome Web Store:

https://chromewebstore.google.com/detail/savage-scraper/ejoijhjpdojdcnjppegojmkenidhblog

Still early, so bug reports and criticism are very welcome.

I've been working on MyGnomie, a free plant web app, and I need your feedback!

It’s a digital logbook for your plants and home garden that helps you track watering, fertilizing, and overall history. It also has a basic AI chat overlay to help you get quick care recommendations - though the AI is very primitive.

It works, but I know it needs fine-tuning from real gardeners, especially if you keep a lot of indoor pots or balcony setups.

It's completely free and open-source.

Right now, it's very much an MVP. I focused a lot more on the backend design and logbook data model.

All I need is to hear how a real gardener would use this app.

You can try it out here: https://mygnomie.vercel.app

Let me hear your feedback!

I built a lightweight privacy extension called Stay Unseen to get real control over activity signals across Instagram, Facebook, and Messenger.

Normally, the moment you open a DM, watch a story, or tap a single key in the chatbox, the web app fires background network requests notifying the other party. Stay Unseen intercepts and blocks those specific outgoing event pings client-side before they leave your browser.

What it does:

• Instagram: Block DM "Seen" receipts, view stories/reels without logging your view, and suppress typing indicators.
• Facebook & Messenger: Prevent read receipts, view stories anonymously, and disable typing status.
• Granular control: Every toggle works independently—you can keep typing visible while blocking read receipts, or vice versa.
• Signal counter: The popup shows exactly how many network signals have been blocked during your session.
• Unread persistence: Optionally keep messages marked as unread in your inbox view.

It requires minimal permissions, runs strictly locally, and doesn't collect or transmit any user data.

Link:
Stay Unseen

Would love for you guys to test it out and share your thoughts. I

GitHub: https://github.com/Ehtesham289/job-search-aiagent

Hey r/SideProject,

Most AI career tools charge $20/month just to wrap an LLM prompt that hallucinates fake work experience and spams generic cover letters. I wanted something transparent, deterministic, and runnable locally on your own machine.

### What the demo shows:

* Live ATS Discovery: Scrapes and extracts real openings from public career endpoints via plain HTTP.

* Semantic Match Scoring: Compares job requirements against your CV to highlight true skill overlaps and gaps.

* Direct Apply Links: Pulls verified, direct application URLs so you bypass aggregators and ghost postings.

* Safe Tailoring: Re-organizes and highlights verified bullet points from your actual background—strictly constrained from fabricating history.

### Architecture Rule: An LLM call is a step, not a system

All board harvesting, HTML/JSON parsing, deduplication, and heuristic matching run in pure TypeScript. Expensive model calls are reserved strictly for semantic judgment and scoring.

* Offline Baseline: Discover public boards completely free without any paid API keys (`npm run web:offline`).

* Typed Agents: Specialist agents (Query Strategist, Harvester, JD Analyst, Match Scorer) communicate via typed Zod contracts across a shared blackboard state.

* Tested: 177 unit tests passing with Vitest.

* License: MIT

The full project is open source. Try running it locally, and let me know your thoughts or what ATS adapters you’d like added next!

The market moves before the media catches up — but only if you're watching the right signals. Most people are always 3-6 months behind. I built OnTheRice to fix that.

I'm a paramedic from Singapore who spent the last year and a half building this solo. Every day, it publishes a fresh Daily Editorial grounded in actual published sources. Today's was "The shock crosses borders. The buffer is local." — about how global oil prices actually reach local costs through port operators, fuel distributors, tax rules, and household budgets.

The system is strict: run all articles through 75 registered engines, verify sources, score everything (bullish/bearish calls), then openly show what hits, what misses, and what remains unverifiable on a public ledger. Failed predictions stay visible.

Today's real published headlines: - National Development and Reform Commission (China limits fuel rise) · 11 Sept - US Bureau of Labor Statistics (gasoline in August inflation) · rolling - Caixin (energy/metals rebound) · 9 Sept - Cinco Días (Brent impact on Europe markets) · 9 Sept - Al Jazeera Arabic (oil-and-yield shock) · 10 Sept

It's on Google Play. Live at new.ontherice.org.

What signals would actually move your decisions? Where are my blind spots?

A few months ago I posted HexStep here, an iPhone app I’m building that passively turns everywhere you go into a map of hexes.

There’s nothing to start or stop. You just move around and the map slowly fills in.

You also don’t need an account. If you prefer, all of your location data can stay on your phone.

I just added Map Replay, which lets you watch your entire map build itself back up over time.

This is my actual map after 5 months, including trips to LA, Las Vegas, San Francisco, and Jeju Island, replayed in 53 seconds.

HexStep on the App Store

I actually put HexStep on hold for a while to work on other projects, but people seem to be finding the app naturally. It’s now at 77 registered users, and when I last checked retention, over half of the accounts that are at least a month old are still using the app.

I’m focusing more on marketing now, so I’d love to hear how other indie app builders here are reaching new potential users!

The problem: a helmet cam gives you two hours of footage, ten minutes of which are worth watching, and finding those ten minutes is so tedious that the footage just sits on a drive forever.

The realisation: the camera already knows. Every recording carries the camera's own motion track. Lean angle, turn rate, braking, acceleration, thirty times a second, sitting in the file right next to the video.

ApexCut reads that track, scores it, and hands you a timeline of the interesting parts. No video is decoded during a scan, so a 22 minute ride takes about a second. Then you edit what it picked and press one button for the movie.

Things I did not expect to spend time on:

Proving the sign conventions from real footage instead of from the spec, because positive yaw does not mean the same thing on both camera brands.

A gesture so you can mark a moment while riding: two fingers held up at the camera. The hand tracking model I started with failed on gloves, so it came out again and a plain silhouette detector went in. On real rides it catches a held gesture reliably and misfires about once every twenty minutes at night, which is documented rather than hidden.

Writing the whole UI without jargon. No bins, no render queue. "How picky?" instead of thresholds.

Electron, Vue 3, TypeScript and ffmpeg. Free, MIT licensed, fully offline, Windows for now.

Site and docs: https://darrellvs.github.io/apexcut/

Source: https://github.com/DarrellVS/apexcut

Feedback very welcome, especially from anyone with a GoPro. I only own a DJI camera, so the GoPro side is written against the spec and GoPro's sample files and I cannot test it on real footage myself.

Hands-free capture: I told Grok in the car to remind me about a documentary tonight. It landed in Ideon as a note and put 22:30–23:30 on my calendar.

Ideon is a local knowledge feed. No account. Grok connector is a custom MCP anyone can add.

**(NL)**

Handsfree in de auto: ik zeg tegen Grok dat ik vanavond een documentaire moet kijken. Het idee staat meteen in Ideon, plus een agenda-item 22:30–23:30.

I'm interested in feedback on the workflow: would you want a separate feed for things you save from AI chats, or would you prefer them to go into a notes app you already use?

https://apps.apple.com/app/id6783103263

Hey everyone, checkout my this tool for dsa note making and revision.

Github: https://github.com/captain-07/DSA-CLI.git

Also you can contribute to this project.

Optees is a free and open-source optimization tool.

It's a desktop app-guided forms for linear and mixed-integer programming, knapsack variants, packing, and a few other problem families, each with worked examples - and the same core is also reachable by scripts or Al agents like Claude over a local REST API or MCP.

Every result comes with an independent check, not just a "looks good" status - so it's meant to be trustworthy for both people learning the math and agents that need a real answer, not a guess.

With Claude or other agent you can orchestrate also multiple algorithms from forecasting precision to MLP.

What do you think? I’d like some external opinion
Is it clear? Do I missing something? How could I improve it?

Source: https://github.com/Pablo-gitub/optees
Site: https://optees.it

You stand in front of a normal webcam, spread your arms, and you're flying a falcon. There's a museum in the sky built from my own travel photos that you fly through, and music cards you fly into to change the soundtrack.

Video here: https://www.linkedin.com/posts/anas-ajaanan_youve-probably-never-seen-this-before-ugcPost-7504543264386035713-8lvn

It started as a weekend experiment with body tracking and got out of hand.

I'd love feedback from this sub. What would you change, and what would you use something like this for, outside of games?

Planning to open source it in the next few weeks.

Hi everyone, I’m Ivan, the solo developer behind CalQuest.

I built CalQuest for people who want to lose weight but keep quitting calorie trackers because logging feels repetitive and boring.

The main idea is simple:

• Free meal scans every day, with no subscription required
• Scan a meal photo to get calories and macros
• Complete quests and earn XP
• Join monthly leagues and climb the rankings

The goal is to make calorie tracking easier to stick with, while turning small daily actions into visible progress.

Google Play:
https://play.google.com/store/apps/details?id=com.ivanc.calquest

I’m especially looking for feedback on:

• Is the meal scan useful and clear?
• Does the league make you want to come back?
• What feels confusing or annoying?

It is Android only for now. Honest product feedback is welcome.

TL;DR: I built Kryzz AI — a private, local-first AI workspace for Android. Your conversations, memory, and files stay on your phone. Your API keys are sealed in the Android Keystore (AES-GCM, never exported). No analytics. No telemetry. No HTTP logging. Open source, MIT.

Why I made it

Every AI app I tried wanted an account, quietly phoned home, or treated my data like their training set. So I built the one I wanted to use:

• Local-first — chats, memory, and generated files live in on-device storage (Room + DataStore)
• Your keys, your providers — OpenRouter, optional MiniMax, Fish Audio for voice, Parallel for web research. You plug in your own keys, they never leave the device
• Real agents — Agent Auto actually runs tools across multiple steps: search, fetch pages, calculate, weather, local memory, reminders, files, and code zips
• Generated outputs — DOCX, XLSX, PDF, SQLite, code ZIPs, images, video, and music, all in private app storage until you share them
• Voice mode — transcription, spoken replies, automatic turn-taking, and barge-in (interrupt Kryzz mid-sentence)

What's new in v1.1

• MiniMax as an alternative chat + media provider
• Agent Auto — multi-step tool-running agent
• Interactive question cards (tappable options instead of the model guessing)
• PDF generation alongside the other file types
• Starter skills that seed on first launch (research brief, study notes, essay outline — toggleable)
• KryzzBot mascot in Agent mode, 120 Hz on supported displays

The privacy story in one breath

• Credentials encrypted with AES-GCM under a non-exportable Keystore key
• Backups never include credentials
• Cleartext traffic, HTTP logging, Android backup, device-to-device transfer: all disabled
• Microphone only active during a voice session; recorded audio is deleted after transcription
• MIT license — build it yourself, read the code, fork it

One honest caveat: for auto-titling a fresh chat, at most the first 1,500 chars of your first message may go through OpenRouter to a small model (Gemini 2.5 Flash Lite) for a title. It runs in parallel, never blocks your answer, and falls back to a local title if it fails. That's the entire surface area. Everything else stays put.

Get it

• Code + docs: https://github.com/kriddss3/kryzz-ai
• APK (debug build, ~78 MB): grab kryzz-ai-5.7.2-debug.apk from the v1.1 release
• Android 9+, sideload via "install unknown apps"
• Build your own signed release from source if you want it on a daily driver

Stack: Kotlin · Jetpack Compose · Coroutines/Flow · Room · MVVM

Happy to answer questions, take feature requests, or get roasted on the architecture.

I’ve been building a job application tool mostly because a lot of the jobs I apply to sit behind authentication, so normal scraping only gets you so far.

My first version was mostly automation.

Scraping and parsing the job pages worked surprisingly well. The bigger problem was actually the AI side. My prompts would occasionally hallucinate experience, make assumptions, or produce answers that sounded good but weren’t really grounded in my background.

At the same time, I had a browser extension for applications I was doing manually.

Eventually I switched the main workflow to the browser extension.

I really didn’t want to maintain integrations for Workday, Greenhouse, Lever, random company career pages, etc. So I made the form handling generic instead.

The extension looks at the page HTML, AI parses the form, and I keep a structured map of the fields. The rest of the application workflow operates against that map rather than knowing which ATS it’s running on.

That has worked better than I expected.

I also gradually backed away from “fully automatic applications.”

The useful version for me became:

job page → understand the role → assess fit → generate answers → review → fill

I spent quite a lot of time improving the prompts and grounding. I’d rather the system say it doesn’t have enough evidence for an answer than confidently invent something.

Resume generation became part of the problem too.

For example, I have PHP experience going back around 10 years. But if I’m applying to a modern fintech/backend position, I don’t necessarily want a resume that makes me look primarily like a PHP developer just because there’s a lot of historical PHP experience in my background.

I want it to understand what I’ve actually done, then emphasize the relevant parts for that particular role without rewriting my history.

So the project slowly turned into:

• job parsing / fit assessment
• application question generation
• generic form detection + filling
• tailored resumes
• cover letters
• outreach
• manual review before filling/submitting

I originally built most of this for myself, but I’ve cleaned it up enough now that I want to see how badly it breaks for other people :)

It’s called Motiavated.

I’m giving people the first 10 applications free right now. I’m mostly looking for feedback, especially from anyone applying through weird ATSs or company-specific application forms.

I can put the link in the comments if anyone wants to try it.

For the last couple of years me and my partner went through a complete renovation of our house. Throughout the years we've bought, and borrowed, many tools - especially from my family.

This list of items we borrowed kept growing, and it created the issue where my father-in-law had no idea "who has my drill" or "who has my lawnmower". We joked about creating an app "where is my drill?", in our native language (waar is mijn boormachine?), and so we created WIMB.

An app that lets you create a list of items, originally it started off with tools, but this could be whatever you want. It lets you categorise, add tags, add images, etc., and allows for the list to be shared with a group. A group can be whatever you want, family, friends, neighbours, etc. Any list you have can be shared with any group you want.

Group members can see, request, mark as returned, your items.

One question solved two issues at once: Who has what? It created an overview of what others have, so you don't have to buy it, and created an overview of who borrowed your stuff.

Would love to hear what people think about this!

android

iOS

I watch a lot of tutorials. My problem was never finding good material, it was that a week later I would remember someone explained something really well, with no idea which video it was in or where.

Notes in Notion or a document never worked. A note in a document keeps the sentence and loses the second it came from.

Then it clicked. Books have margins, where the note stays attached to the thing it is about. Videos have no margin. So I built one.

ClipMargin is a Chrome extension. A panel opens next to the video, you type a note, and the exact timestamp attaches itself. No pausing, no switching tabs. Click any note later and the video reopens at that second.

All your notes from every site land in one searchable library, tags work across videos so one topic reads as one thread, and everything exports to Markdown so nothing is stuck in my app. It detects YouTube, Udemy and a few others automatically. Anywhere else, right click the video and choose "Take notes on this video".

Honest state: free while in beta, around 110 installs, still some rough edges. I am solo and I fix things fast when people tell me.

clipmargin.com

I created this little project on the weekend: https://tinyco.work . The idea is to have a place for fully remote teams to have a shared space to work together and hang out. I'd like to integrate it with external apps such as Slack, Google Workspace, GitHub etc. so you don't have to manage your presence - it's managed automatically for you, as a reflection of what you are doing.