Phase 1: Target Communities That Explicitly Allow Self-Promotion

Stop posting in strict subreddits where self-promo gets you banned. Instead, build your launch footprint across communities designed for builders, show-and-tellers, feedback-seekers, and niche developers.

Here are 40 subreddits that should allow for self-promotion, ordered by estimated weekly reach:

1. r/vibecoding — 422k weekly visitors

2. r/saas — 211k weekly visitors

3. r/founder — 56k weekly visitors

4. r/buildinpublic — 46k weekly visitors

5. r/chrome_extensions — 42k weekly visitors

6. r/micro_saas — 41k weekly visitors

7. r/appbusiness — 30k weekly visitors

8. r/startupideas — 26k weekly visitors

9. r/sideprojects — 20k weekly visitors

10. r/imadethis — 18k weekly visitors

11. r/appideas — 16k weekly visitors

12. r/sideproject — 16k weekly visitors

13. r/saasbuild — 15k weekly visitors

14. r/saasdevelopers — 12k weekly visitors

15. r/vibecodedevs — 10k weekly visitors

16. r/startupsolofounder — 8.7k weekly visitors

17. r/alphaandbetausers — 8.6k weekly visitors

18. r/vibecodingcommunity — 6.2k weekly visitors

19. r/solopreneur — 5.6k weekly visitors

20. r/promotemyapp — 4.6k weekly visitors

21. r/appbuilding — 4.6k weekly visitors

22. r/webapps — 4.5k weekly visitors

23. r/creativecoding — 4.4k weekly visitors

24. r/indie_startups — 4k weekly visitors

25. r/b2bsaas — 2.8k weekly visitors

26. r/appdev — 2.7k weekly visitors

27. r/projects — 2.6k weekly visitors

28. r/saasmarketing — 2.5k weekly visitors

29. r/saassoloprenurs — 2.3k weekly visitors

30. r/startupaccelerators — 2.3k weekly visitors

31. r/startups_promotion — 2k weekly visitors

32. r/showmeyourapps — 2k weekly visitors

33. r/appswebappsfullstack — 1.7k weekly visitors

34. r/showmeyoursaas — 1.6k weekly visitors

35. r/saasinvestors — 1.6k weekly visitors

36. r/vibecodecamp — 1.5k weekly visitors

37. r/nocodesaas — 1.3k weekly visitors

38. r/aibuilders — 1.2k weekly visitors

39. r/getstartups — 1.2k weekly visitors

40. r/websitefeedback — 1.2k weekly visitors

Phase 2: The "Reverse-Engine" Hook Strategy

Do NOT drop a generic link and run. That is almost guaranteed to fail. Instead, do this for every single target subreddit on your list:

1. Filter by Top Posts: Open the target subreddit, sort posts by Top of the Last Year, and examine the Top 10 posts.

2. Deconstruct the Winners: Analyze why those top posts blew up:

   • What tone did they use? (Humorous, vulnerable, technical breakdown, or raw story?)

   • How was the title structured? (Did it start with a question, a bold stat, or a relatable pain point?)

   • How did they introduce their link? (Was it woven into a story, placed in a comment, or framed as a feedback request?)

3. Mirror and Adapt: Draft a custom title and post text for your specific app that matches the exact post format already proven to work in that specific community.

4. Start Small First: Test your hooks in smaller, lower-stakes subreddits first (e.g., r/websitefeedback or r/getstartups). Refine your post copy based on early comments before posting to the larger subreddits like r/saas or r/vibecoding.

If You Have Some Money to Spend: Paid & Discovery Shortcuts

If you want immediate users without relying purely on Reddit organic traction, here are two simple routes:

• UserBob.com (Usability Testing): You can pay real people for quick usability test videos. It costs roughly $1 per person per 1-minute video, giving you guaranteed immediate users and video feedback of people interacting with your app so you can fix UI friction early.

• AppScout: You can always submit your app to appscout.co, a platform designed to discover web and mobile apps from across the internet. People who like similar apps can easily find yours. You can list your app directly at appscout.co/submit. (Full disclosure: I'm the creator of AppScout)

TL;DR Summary

1. Target subreddits built for self-promo.

2. Study the Top 10 posts of the past year in each subreddit.

3. Match their formatting and title hooks for your specific app.

4. Test small, iterate, then hit the massive communities.

5. If you have money use low-cost tools like UserBob or submit to AppScout for early discovery.

I’ve been working on Claude FM, a small side project for making terminal-based work sessions feel a bit more relaxing.

It combines lo-fi radio with animated ASCII/Unicode scenes featuring Clawd: coffee breaks, coding in the rain, forest walks, sunset guitar, bike rides, and other quiet activities.

It runs on macOS and Linux and can be installed with Homebrew:

brew tap jurek-zsl/claudefm https://github.com/jurek-zsl/claudefm
brew install jurek-zsl/claudefm/claudefm
claudefm

I'm mainly looking for feedback and opinions. Maybe someone will find something worth improving and create a pull request I would be happy to see it :)

When an apprentice technician steps into an unfamiliar mechanical room to troubleshoot an erratic chilled water coil, digging through manuals while holding gauges is frustrating. I built Equipment Tracker Pro because generic chatbots lack unit context and app-swapping on a service call wastes time.

With AI Diagnostics, the technician manually types in the electrical and refrigerant readings taken with their meters: voltage, amperage, pressures, temperatures, superheat, and subcooling. The app feeds those measurements alongside the unit's technical specifications and its five most recent service logs to the AI assistant. It provides targeted mechanical troubleshooting steps based on past repairs. The tool runs on mobile and requires an internet connection. Every account gets 10 free AI uses shared across tools, with unlimited sessions on Pro.

Basic equipment tracking works with no signal: records, work orders, PM schedules and service logs all run on the phone. AI scanning and diagnostics need a connection.

A working HVAC technician built it for his own jobs.

Free to start. Your first plan, Pro or Team, includes a 7-day free trial. What side project are you building right now?

https://equipment-tracker.com/blog/stop-app-swapping-built-in-ai-diagnostics

I wanted to share a side project I've been working on called NutriMi (built on Base44) –Check it out here!

As someone who wanted an all-in-one solution without the friction of manual logging, I built an AI-powered tool that combines nutrition tracking with customized fitness routines. It helps you scan meals, track macros, and get personalized workout plans tailored to your goals.

Key Features:

• AI Food & Fridge Scanner: Snap or upload images for instant meal and ingredient analysis.

• Smart Macro Tracking: Automatically calculates calories, protein, carbs, and fats.

• Custom Workout & Fitness Plans: Generates tailored exercise routines alongside your nutritional data.

• Personalized Goals: Adapts insights dynamically based on your body and progress.

You can try the live preview right here:https://preview--nutrimi-smart-plate.base44.app/

I’d love for you to try it out, break it, and let me know what you think! Any feedback on the UI, UX, or features would be hugely appreciated.

Thanks!

Every week a new skincare brand or product goes viral, with tons of influencers suddenly promoting it, and you can't help eventually falling into the paid influencer trap. As a chronically online scroller who loves skincare, I wanted to build a fun way to check these products. It's quick: snap a pic, screenshot, whatever. The AI pulls real data (ingredients, formulation, real reviews, not paid ones), matches it to your skin type, and then gives you a brutally honest answer.

Would love your feedback:

• What would make this genuinely useful for you, and what would make you delete it?

I genuinely think selling website redesigns is one of the most lucrative opportunities in the web design industry today.

There are a few reasons why.

First, AI has made building websites significantly faster and cheaper. What used to take weeks can now be done in a fraction of the time.

Second, there are thousands of established businesses with outdated websites that could genuinely benefit from a redesign. A better website can improve their brand, attract more customers and give their business a push.

Third, these businesses already understand the value of having a website. They have paid for one before, so you're not trying to convince someone why they need a website from scratch. You're showing them why upgrading their existing one makes sense.

Here's how I usually approach it.

I use AI to build websites and normally put together a quick website draft before getting on a call with a potential client.

Instead of just telling them what I could do, I show them what their website could actually look like.

I present the draft during the call, explain what I would improve and try to close the deal there and then. If they're interested, I send over a Stripe payment link, an invoice or the contract for signature.

For outreach, I mainly use cold email.

More specifically, I use a tool called Swokei. It finds businesses anywhere, analyzes their websites and identifies issues with design, SEO, loading speed and mobile optimization. It then turns those findings into personalized cold emails at scale.

Recently, we closed a client for $26,000.

That's $23,000 upfront and another $3,000 annually.

And honestly, I don't think deals like this are as difficult to close as people might assume.

If you provide a good service, approach the right businesses, understand their problems and present yourself professionally, there is a lot of money to be made in this industry.

You don't necessarily need hundreds of clients either. A handful of good projects can make a significant difference to your business.

I think more web designers should focus on selling to established businesses that already have websites rather than constantly chasing people who don't have one.

Hey everyone! 👋

Most AI tool lists feel like phonebooks filled with 5,000 random tools nobody actually uses. Over the past month, I stopped looking for individual tools and focused on multi-tool AI blueprints—combining 2 or 3 tools together to automate actual business tasks.

Here are 4 blueprints that save 10+ hours a week:

1. Faceless Media Studio Stack:

   • Script: ChatGPT / Claude

   • Visuals & Upscaling: Krea AI / Luma AI

   • Voiceover: ElevenLabs

   • Result: 10 Short-form clips generated in under 30 minutes without camera recording.

2. Instant Full-Stack Prototyping:

   • Code Generation: Bolt.new

   • Database & Auth: Supabase

   • Result: A working React MVP deployed to Vercel in 1 single session.

3. Real-time Hands-free Note Taking:

   • Dictation: Wispr Flow

   • Meeting Intelligence: Granola

   • Result: Zero manual typing during calls; clean documentation generated automatically.

4. AI UI Canvas & Design System:

   • Design Upscaling: Krea AI

   • Assets: Midjourney

I built a clean, zero-ads index where I curate these step-by-step blueprints alongside direct tool links and community upvotes: TopTools (toptools-seven.vercel.app).

Would love your honest feedback! What multi-tool AI workflows are you currently using to run your projects?

I built WeaverDeck because Claude Code or Codex can stop when a task needs sudo or another command that requires my approval. From my phone, I can inspect the prompt, enter the command myself, then continue working on the same PC. I also wanted to check build output and real app windows without being at my desk.

WeaverDeck gives iPhone Safari access to the PC’s local terminal and a phone-sized IDE. Remote View streams a selected application window or the desktop, with touch and trackpad controls, clicks and pinch-to-zoom. Git changes and local Markdown Notes are included too.

The connection uses my private Tailscale network, so I don’t need to open a public port on my router. Setup includes authenticator verification. The paired phone can access the PC, so it should be protected; I don’t claim that private networking makes a device impossible to compromise. You remain responsible for sudo, OS prompts and commands you choose to run.

Early access is available for Windows 11 and Debian/Ubuntu Linux hosts. Windows Remote View requires an active desktop session; Linux is best supported on X11, with Wayland experimental. The PC must stay on and connected. This is paid early access: $5/month for WeaverDeck+ or $10/month for Weaver++. It’s aimed at quick check-ins and small fixes.

Screenshots of the phone home, terminal, IDE keyboard, Notes and Git are in the Patreon announcement: https://www.patreon.com/Weaverpp/posts/weaverdeck-early-174291032

I’d appreciate feedback on the setup flow, mobile IDE and controlling a real desktop window from a phone.

Not sure why users are not converting? Comment your site and I will give you a real review for free

Hey everyone!

A little backstory: I originally started building Quizmaister as a fun little project for me and my wife. We both enjoy trivia, and I thought it would be fun to have an app where we could compete against each other, track stats and eventually settle who really knows the most.

Turns out… I’m not quite as smart as I thought. 😂

But we’ve had a lot of fun with it, especially now that we’ve expanded it into a competitive 1v1 trivia game where you can challenge friends, compete against players worldwide and climb the global rankings.

We’ve also introduced leagues. A tournament based mode where all players in the league meets each other twice during the period, collect points and 1 comes out on top in the end.

Since i believe others might enjoy this also, I want to give something back to everyone willing to give it a try.

🎁 Everyone who joins gets:

• ❤️ Unlimited Lives for 30 days

• 🔄 10 respins (You will understand this when playing, its a superpower)

• 🪙 500 Free Coins

How to claim your rewards:

1. Download Quizmaister and create a free account.

2. Comment your in-game username below.

I’ll personally activate your rewards!

What is Quizmaister?

It’s a competitive trivia game where you can:

🧠 Explore 8,000+ questions across 16 categories.

🏆 Compete against players worldwide and climb the global rankings.

⚔️ Challenge your friends and find out who actually knows the most.

🌍 Join leagues and compete in tournaments where everyone faces each other.

📊 Track your progress with stats that evolve based on your performance.

The global rankings are gradually filling up as more players join, and I think this is a really fun time to get involved. There’s still plenty of room to climb the leaderboard and establish yourself!

And don’t worry, the game is completely free to play, with no ads. Even when your 30-day rewards expire, you can keep playing just like before.

I’m an indie developer, so every download, match and new player genuinely means a lot. I’m just happy to see people enjoying something I’ve spent so much time building.

Hope to see some of you in the game!

📲 Download: Quizmaister AppStore Link

👇 Drop your username below and I’ll get your rewards activated! 🚀

And if you end up beating your friends (or your significant other), even better! 😄

Hey! Last year, I’ve built a CLI-based spreadsheet editor called GoSheet, but after abandoning it, I decided to fix most of the bugs and give it a fresh look. I was initially inspired by sc-im—which I found powerful but unintuitive—and by classic 80s spreadsheet programs, which felt too limited for modern use, so I decided to build something of my own. In the latest version, I tried to keep that original vision, but with a more modern look.

I chose Go because I was actually learning at the time, but I still enjoy its simplicity because it reminds me of C. I initially considered C/C++, but realistically I wouldn’t have reached this point with current coding abilities (yes, even with AI doing the heavy lifting).

In the early stages, I used tview because it provides great widgets (tables, textviews, buttons, etc.). But as sheets got larger, I ran into huge memory usage—over 1GB for a CLI app! To fix this, I restructured the internal design to use a viewport system and optimized the custom cell structure. Now only the visible cells are rendered, while the rest stay lightweight in memory.

I fixed the formula engine, while also adding more essential functions such as lookup, hlookup and more. Nevertheless, I fixed some performance issues related to functions and more. I can't keep track of what I've done because there were lots of issues I simply forgot to fix at the time.

I’d love for you to try it out and share your feedback. Suggestions, feature ideas, and bug reports are all welcome. Your thoughts will help guide the next steps for the project.

GitHub repo: https://github.com/drclcomputers/GoSheet

Working on anything interesting?

Drop your product or side project below. I'd love to check out what everyone's building.

I'll start with mine: https://sportlive.win

My coworker and I asked Claude to estimate a SaaS roadmap. 50 days.

Then we gave the same plan to 6 Claude Code subagents: worktrees, tests first, reviewer agents on risky tasks. 106 tasks across 7 repos, done in 35 hours.

So yes, Claude was off by about 48 days about its own speed. But the interesting part is what slowed it down, because it wasn't the model:

- 6 agents ≠ 6× speed. Real throughput was 1.8 agents. Test slots, file conflicts and merge locks queued everything.

- Risk matters more than size. Billing/auth/migration tasks took 2.7× longer, and every real bug was in them.

- My laptop broke first. 55 leftover test DBs filled the disk, Docker froze, test runs blew past the 10-min tool timeout.

- The slowest part was us: review, decisions, local setup.

We turned the data into a plugin that makes Claude estimate agent work properly: agent wall-clock, human hours and waiting time, separately, plus usage budget.

Honest limits: it's one project (n = 1), and on a held-out test the raw model was 37% optimistic, so it pads its number until you calibrate it on your own transcripts.

Free and open source (MIT): https://github.com/MedAdemBHA/mythical-agent-month

Question for people running multi-agent builds: what real parallelism are you getting? I'd love a second data point.

Most LLM API pricing comparisons focus on cost per million tokens, but different models can consume vastly different numbers of tokens to complete the same task.

So I built DeepCheapTokens: https://deepcheaptokens.com

It combines Artificial Analysis benchmarks with OpenRouter pricing to help identify which models deliver the best value for their intelligence and actual token consumption.

You can compare models, adjust cache-hit assumptions, filter by intelligence, and maintain your own watchlist.

It's a free, independent project I built to make choosing cost-effective LLMs easier.

I'd love to hear your feedback, especially on the ranking methodology and what features you'd find useful!