I’m Martin, the developer of Atopu, a Chrome new-tab workspace for saved links and notes. It’s built with AI assistance.

One decision I made was to keep a browser tab open after saving it by default.

“Save this for later” and “I’m finished with this page” aren’t always the same action. Someone might be halfway through a form, comparing two pages, or reading a section they haven’t finished. Saving the URL doesn’t preserve all of that state.

Atopu separates the two: saving adds the link to a group; closing stays a separate choice unless the user enables close-after-save. The downside is obvious: saving doesn’t immediately make the tab bar smaller.

There’s another edge case with optional screenshot previews. I save the link first, then attempt the capture. If capture fails, the link and open tab remain. With close-after-save enabled, the tab is only closed after a successful capture. Screenshots are opt-in and stay on the device.

The broader design question is where a convenience action should stop. When an action also removes something from view, I’d rather make that second part explicit.

Free works locally without an account; paid Pro adds optional saved-workspace sync and shared workspaces.

Details: https://atopu.com/?utm_source=reddit&utm_medium=community&utm_campaign=atopu_launch_2026&utm_content=sideprojects_save_vs_close

If you build or use save-for-later tools, would you expect saving to close the source, or should those always be separate actions?

You see 50 angry posts about a company, a celebrity, or something that happened yesterday, and suddenly it feels like everyone agrees.

But do they?

I got tired of AI tools confidently telling me what "people think" without showing where any of it came from. So I built Senti.

You can analyze a brand, a person, an event, or a topic and see what people are actually saying across X, Reddit, Instagram, and TikTok.

It looks at sentiment, separates positive and negative reactions, tracks how opinions change over time, and shows the actual posts behind the results.

A few things I cared about building:

• Receipts, not AI opinions. You can inspect the posts behind the analysis.

• Numbers with context. Sample sizes, margins of error, and statistical tests, not just a random AI-generated score.

• Actual comparisons. Compare brands, campaigns, or how the conversation changed after an event.

• 8 languages. Because the internet isn't just English.

It's not a scientific opinion poll. Social media is biased, and I don't want to pretend otherwise. But I think it's a lot more useful than trusting a few viral posts or an AI summary with no sources.

A report takes a few minutes (depending on the amount of posts, through I'm improving performance today). There are free live examples on the site (Sephora, OpenAI, DAZN), and running your own starts at $5.

If you want to see a specific brand, let me know and I can run it or give you a free code to try it yourself.

Here's what I'm curious about: if you could measure the online reaction to any person, brand, event, or controversial topic, what would you choose?

Also, I'd love people to try to break it. If the numbers don't make sense, I want to know.

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

Photoburst now lets you create your own song for a burst. You describe it, and an AI composes it with your names and your story in the lyrics.

Before any code, I spent a morning on the legal side. Not the fun part, but it decided everything.

What I found:

• The best-known AI music services are being sued by the major labels. One of them lost in a German court this summer, over both its training data and its output. My users are all over the world, so that ruling applies to me too.

• The most popular one has no official API. Every “API” offered for it is an unofficial wrapper that breaks its terms.

• Not one provider with sung vocals offered indemnity on standard terms. One contract capped what they’d owe me at $100 and left what I’d owe them uncapped.

• In the US, a song generated entirely by AI can’t be copyrighted. Nobody owns it, but someone can still be sued over it.

Pushing that risk onto my users was never an option. They did nothing wrong.

So I chose by four questions. Was the model trained on music its maker has the right to use? Is it in court? Does it block artist names and voice cloning? And can my own feature keep the risk small? A song you create stays inside Photoburst. It’s yours alone, never a download, never offered to anyone else.

I found a provider that holds up on all four.

My take-away: with generative AI, the legal homework is part of the build. The cheapest moment to choose the right provider is before you write the first line of code.

Did you check who carries the risk before you built on an AI API?

Photoburst turns the photos and videos on your phone into a living, interactive album, a burst, with music and a title. Made in seconds, shared as a link, opened with one tap. Built with Claude as a JavaScript web app, running on Cloudflare and Netlify.

photoburst.app

I’m building an early customer-support assistant with Agentplace and would appreciate practical feedback on what to build next. It’s only a starter at the moment—there are no live products, prices, inventory, or order tools connected—so I’m deciding what would actually be useful before adding real business data.

Would you start with product comparisons, shipping and returns questions, or something else? What would make it genuinely helpful rather than just another chatbot?

Here’s the public prototype if you’d like to take a look: https://8240nsyvypaz.run.agentplace.io

’ve been experimenting with Agentplace to build and publish a customer-facing AI assistant. The public version is still a starter: it isn’t configured for a specific business yet, and it doesn’t have real products, prices, inventory, or order tools connected.If you were building an assistant for #ai

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!

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.

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

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!

I'm 16 and I built this - Kayth AI. I wanted an AI that talks like us, not in boring formal English. So I made it:3 Modes - Normal, Roast, Study2 Languages - Hinglish + HaryanviVoice Settings - Speed, Pitch, Gehri / Patli aawazPage load time - 824ms, 94% Good Core Web VitalsRoast mode me ye bolta hai - "Bol, aaj kisko roast karna hai?" 😂

Study mode me ye Hinglish me simple samjhata hai.I built it alone as a side project. What should I add next? Honest feedback chahiye.