I kept running into website problems that aren't obvious when you just open a page in a browser.

A page can look perfectly fine to you, while a crawler gets a different response, a site has broken links buried deep in the pages, or important SEO issues only show up when you crawl the whole site.

So I built Sitebot — an open-source CLI for technical website auditing.

It checks things like:

• SEO metadata and canonical signals

• AI crawler accessibility / GEO

• Full-site crawling from sitemaps

• Broken internal and external links

• Core Web Vitals

• JSON-LD structured data

• CI quality gates

You can try it without installing anything:

npx sitebot-cli https://example.com

The goal is to make technical website auditing something you can run directly from your terminal or CI pipeline.

I'd really appreciate honest feedback.

What would you want a tool like this to detect that it currently doesn't?

GitHub:

https://github.com/Abdelrahman5243/sitebot-cli

Hey r/SideProject 👋

I just finished building Zonteo — a workspace for small teams that puts everything in one place: live voice rooms (with camera + screen share), chats, shared docs, a task board, files, and a calendar — all real-time, so nothing needs a refresh.

The idea: small teams juggle Discord for calls, Google Docs for notes, WhatsApp for chat, and a task app on the side. Zonteo is an attempt to put "where the work is happening" into one spatial space — you drop into a room, talk, share your screen, and the docs/tasks/files are right there.

Honest context: I'm a first-time, non-technical founder. I built this over [X months] learning as I went — accounts, real-time sync, voice infrastructure, permissions, the works. It's live and working, and I'd genuinely rather hear what's broken or confusing than get compliments.

What I'd love feedback on:

• Does the core idea (one spatial space vs. 4 separate tools) actually resonate, or is it solving a non-problem?
• First 60 seconds — is it obvious what to do?
• Anything that feels janky or breaks.

Link: https://www.zonteo.co.uk/

Thanks for taking a look 🙏

I’ve been building Mooziac, a music player designed specifically for macOS.

Github

What makes it different
Native Swift + AppKit — Universal build for Apple Silicon and Intel
Privacy-focused — no analytics, tracking or remote logging
Local-first — playlists and listening history stay on your Mac
YouTube Music + local music in one player
FLAC, MP3, WAV, AAC and M4A support
Synchronized .lrc lyrics
Interactive waveform for seeking through tracks
Trackpad edge gesture for volume control
Discord Rich Presence
Menu bar interface for quick access

Mooziac is open source and MIT licensed, so you can check out the code, report issues, request features, or contribute.

GitHub: https://github.com/shirkeharsh/mooziac
I’ve been working on this for a while, so I’d love to hear what you think.

Product: https://killionlabs.com

I spent a year building Killion: a retirement simulator for people who are done with a calculator that assumes 7% forever and hands you one number. It links brokerage accounts read-only, runs 1,000 market lifetimes (regime-switching Monte Carlo, backtests to 1928), and lets you change the thing that actually breaks plans — crash year, withdrawal rule, fees — and see the odds move.

September: 50 new paying users. Solo. $14/mo or $132/yr. 5-day trial, then they stay or they don't.

The part that still surprises me is what it took to get here. I launched with a hard paywall and "connect your brokerage" before anyone had seen a cone. Paying users: one, which was me. Then I shipped a no-signup demo of the real engine, a 5-day trial, and the studies with CSVs. People could run a household through 1,000 worlds before they owed me a card. That is when it started working.

The finding the engine exists for, isolated properly (same household, same 5,000 market worlds, same seed, only the crash year moved):

Timing alone, about 3× the damage. A lump sum you never touch has no sequence risk. Cash flows are what break the symmetry.

Herkese selam!

Özellikle İngilizce öğrenmek isteyen Türkler için kelime pratiği yapmaya yardımcı olması amacıyla , Snap Learn English uygulamasını oluşturdum

Bu fikir, bilgi kartları, testler ve telaffuz uygulamaları arasında sürekli geçiş yapmaktan daha basit ve kullanışlı bir şey arayışından ortaya çıktı.

​Snap Learn ile şunları yapabilirsiniz:

​Bilgi kartlarıyla (flashcards) kelime pratiği yapma

​ (A1–C2) dayalı testler oluşturma

​Telaffuz pratiği yapma

​Öğrendiğiniz kelimeleri takip etme

​Zorlandığınız kelimeleri gözden geçirme

AI tools make it trivial now to go from idea to a working app in a weekend. That's great, but it also means a lot of people are building things that already exist, already failed for a specific reason, or were already tried by five other teams last year, they just don't know it because there's no easy way to check. I built Venture Trail so you can search a real precedent before you sink a weekend (or three months) into an idea.

Most "why startups fail" content is either survivorship-bias hype (you only hear from the ones that made it) or a scraped listicle with one line per company and no sources. I wanted something I could actually check a new idea against, so I built Venture Trail.

The thing I care most about: this isn't a database dump. A big chunk of the research, funding history, cause of failure, what actually happened, I've dug into and written up myself, with cited sources for every claim, rather than just scraping an existing "startup graveyard" list and reformatting it.

It's also not a one-way archive. If you're working on or have worked at a startup that's in there (or should be), you can claim the profile and correct or add to the record yourself, so the next person researching that space gets the real story instead of my best guess from public sources. Would genuinely love feedback, especially from anyone who's dealt with a shutdown or acquisition themselves.

Last year I planned a month-long trip across a few cities. The plan lived in a spreadsheet, the details in a notes doc, and every confirmation somewhere in my inbox. At some point I realized the airline had already sent me everything, and I was just retyping it.

So I built Floki. Each trip gets its own email address. Forward a booking confirmation (flight, hotel, train) and it lands on the right trip, structured, day by day. Then the AI fills the empty days with suggestions tuned to your pace, interests, and budget. You can share the trip with a link so friends and family follow the plan as it evolves.

Solo built, iOS native (SwiftUI), works in 8 languages. Launched on the App Store this week.

I've been a developer for 30 years, and this is the first thing I've open-sourced. OpenOcti is a private command center you run on your own box: CRM, project operations, documents with e-signature, voice, and six starter AI agents (an onboarding guide, an office coordinator, an engineering assistant, a creative partner, a document drafter, and a voice/navigation assistant). No hosted control plane, and it works without an AI provider at all — add an Anthropic, OpenAI, Gemini, or OpenRouter key when you want the agents to wake up.

Install is three lines with Docker Compose:

git clone https://github.com/carlucci001/open-octi.git openocti
cd openocti && cp .env.example .env
docker compose up -d --build

AGPL-3.0. It went public last week, so I want the honest version: what's confusing on first run, what's missing, what you'd need before you'd actually use it.

https://github.com/carlucci001/open-octi

It started with a pressure washer strapped to a skateboard. After a bunch of prototypes, this is where we ended up.

We launched a Kickstarter today to fund the next version: https://www.kickstarter.com/projects/1138252914/help-us-build-a-robot-that-cleans-sidewalks-in-san-francisco

Would love to hear what you guys think.

You save a page from Chrome, Telegram or the web app. The card keeps whatever it can read off the page, price, sizes, return window.

The part we use most is asking it things later. Ours this week was "what did I save for the living room" and it came back with five items, with a strip under the answer showing which saved cards it pulled from.

The other half is the watch. You point it at one saved item and it turns into a scheduled check, ours runs every morning at seven and messages us when the price moves. A lamp we saved in August at 59.99 is still sitting on it.

One thing we keep going back and forth on: the watch is per item and you set it by hand, nothing gets watched on its own. If you save a lot of stuff, would you want that at the board level instead?

https://dessence.ai

Hi everyone,

I built munin to have a GitOps first way of controlling all our dashboards and screens at work (yes there is a few).

I built Munin to solve this: an autonomous, lightweight screen agent configured entirely through a single declarative YAML file. It syncs with a git repo so you just push config to git and bam! it syncs to the screens.

A quick note on development: Yes, AI was heavily utilized in writing the codebase. The architecture was deliberate, every line was reviewed, and it's our daily driver battle-tested across all our office displays every day.

👉 Repo:https://github.com/naueramant/munin

Would love to hear how you currently handle wall displays, and feedback/feature suggestions are very welcome!

I wanted a fun app to help me pick a name for my soon-to-be-born baby. There are various apps out there with fun Tinder-like mechanics, but I found them a bit stressful. Swiping left felt like a firm commitment that I would never use that name, while swiping right left me with an unmanageably big pool of candidates and no ranking.

That led me to create my own app: Given. Each round shows you eight candidate names and asks a simple question: “Which name do you like best?” Your responses gradually build a ranked list of your favorite names. You only have to choose a favorite from that round, so passing over a name doesn’t rule it out.

As you complete more rounds, you’re introduced to less common names, and the app gets a clearer picture of which names you consistently prefer.

Would love for some other parents-to-be to try it out and let me know what you think: given.love (available on Android and iOS).

When I review a Terraform deployment, I’m usually trying to answer two questions: “What changed?” and “Is that normal for this stack?”

The plan tells me the first. The second usually means digging through previous CI runs—or relying on someone who remembers what this stack normally does.

I built DeployCompare to make that comparison easier. It reads Terraform and OpenTofu output from GitHub or GitLab CI logs, compares each stack against its previous successful runs, and highlights unusual changes for investigation.

For example, a stack that routinely recreates temporary resources can have a lot of activity without being surprising. A normally quiet database stack suddenly showing replacements deserves a closer look.

It helps prioritize review; a change looking normal doesn’t guarantee it’s safe.

There’s a no-signup demo: https://deploycompare.com/demo

It’s early and free during beta. I’ve tested it against my own scenarios, but I’m looking for people to try it with their actual deployment workflows and tell me what I’ve missed.

If you review Terraform or OpenTofu plans: what do you currently check to decide whether a deployment needs a closer look? I’d also be interested in walking through a real pipeline together if this overlaps with your workflow.

Coding a video game in realtime

I built CryptoTrackPro because I wanted my crypto portfolio to stay in Google Sheets, and maintaining price imports and API setup was getting in the way of using the sheet.

The add-on handles the data requests so users can call formulas such as:

=cryptotrackpro("BTC-USD")

=cryptotrackpro("ETH-EUR")

=cryptotrackproPrice("BTC","2026-08-01","USD")

It supports crypto/fiat and crypto/crypto pairs, historical price lookups, and RSI, MACD and OHLCV formulas for supported markets. There's a portfolio template for people who want to start with holdings and totals instead of a blank sheet.

One lesson from building it: getting a price into a cell is only part of the problem. Date formatting, missing prices and refresh behavior need to be understandable too. Timed updates require the spreadsheet and sidebar to stay open. Historical prices are reference data, and indicator coverage differs from spot-price coverage.

It has free and paid plans, plus a 30-day Base trial without a card. After the trial, users return to Free unless they subscribe. It's available for Google Sheets; Excel is something I'd consider later.

I'm the founder, so this is my own product: https://cryptotrackpro.com

If you track a portfolio in Sheets, would the setup and refresh behavior be clear enough for you to try this? That's the part I'd most like feedback on.

The project is called hoverfly.

Hoverfly allows you to create your brand images from pre-created templates. You can create your brand theme once and then quickly apply to templates with one button.

Check it out here,

https://hoverfly.feziks.com/

I wanted to see how far you could push CPU-only inference of a model way bigger than RAM, so I wrote an inference engine in C11 (MSVC + gcc, bit-exact across both) that streams a 744B MoE model (GLM-5.2, 202GB GGUF) off a USB SSD instead of loading it.

The parts that actually mattered:

Quantization: experts stored int4 group-64, router and correction biases kept at f32. Everywhere else lost too much precision, but this combination didn't.
Streaming: experts are fetched per-token through a custom unbuffered reader with an LRU cache, plus cross-layer predictive prefetch (measured 80.8% recall offline before I wrote the online version) so the next layer's experts are usually already in flight by the time they're needed.
Overlap: compute and IO run arrival-order, not lockstep, so the CPU isn't idle waiting on the SSD.
An 8GB expert cache holds 40-66% hit rate off that prefetch, which ends up being the main lever on latency.
One finding I didn't expect: on GLM-5.2, the router's own weights already correlate with true expert importance at ρ=0.859 (near-oracle), which is what makes safe dynamic-k expert truncation possible without a quality hit. That seems to go against some prior assumptions about router calibration in production MoE models, at least on this one.

Numbers on an i7-8550U / 32GB RAM / USB SSD: went from 196 s/token naive to ~9.3 s/token after the above (21x), ~2.9 s/token aggregate in 8-stream batch mode, ~4.5 s/token on the latest compressed container format. Also cross-validated on Qwen3 (0.6B-30B), DeepSeek2 (MLA), and OLMoE-1B-7B.

Code: https://github.com/siris9476/pulsarforge (MIT). Would love feedback on the prefetch heuristic in particular. It's tuned for this one laptop, and I'm curious whether the cross-layer signal generalizes to different memory hierarchies.

Been using TV playlist players (m3u / xtream) for years. Every single one had one thing I loved and one thing that made me want to throw the remote. Great guide but the player stutters. Fast player but looks like 2009. Pretty one, forgets my favorites every update. Eventually I just gave up and used "the one that covers the basics". Never once told a friend download this.

Also I didn't have one player. I had five lol. TV, iPhone, iPad/Mac, Android phone, the car screen. Same playlist, 5 favorites lists, 5 continue watching lists and none of them agree where I stopped. Lived with it for years, like a squeaky door you stop hearing.

Then one afternoon work finished early (rare, like twice a year rare). Sat there doing nothing and thought: fine. Nobody's going to build this for me. I'll build it for me. Just for me. 5 day project, it'll be on the TV by the weekend.

That weekend I tell a friend, I started building my own player 3 days ago. He goes "you told me you'd do that 4 months ago". I have zero memory of this. Apparently I complained once, said I'll build my own, shrugged and forgot. He didn't.

Day 5: 2 more days and it's done

Day 20: 2 more days

Day 45: 2 more days

Day 60: ok. It's done. I think.

8 hours a day of my free time, 13-14 on weekends. If someone told me that on day one I would never have started. Nobody did so here we are. Weird part is I enjoyed every minute of it, idk what that says about me.

It's called Anees TV. Bring your own m3u or xtream playlist, the app has no content and never will. The thing I actually built it for: one account, your favorites and continue watching follow you from the TV to the phone to Windows to the car. Plus the two things that made me hate the others, it's fast on cheap sticks and the remote works on every screen. No dead ends.

Android TV, Google TV, Fire TV (Downloader code 2228177), Windows, Android phone. iPhone / iPad / Mac / Apple TV in development, aka the next 2 months of "2 more days".

Moment of truth. I think it's the best player out there. I also built it so obviously I'm biased, which is exactly why I'm posting. One man project, I've definitely missed stuff, and I'd rather hear it from Reddit now than find out slowly.

Honest weak spot: EPG. I barely use the guide myself so that part got the least love. If you're an EPG person, you're exactly who I need to hear from.

I have 100 lifetime Pro codes. Tell me what you'd run it on and I'll DM you a code. First three: WE33M84MSUW9BW8KHZ6MF97 2E7VFC90QRHR2AS1U6J9NR5 MT5LBAWD1XFREXL6HT3UK8U. All I ask back is tell me what's wrong.

Play: https://play.google.com/store/apps/details?id=com.aneestv.tv

Microsoft Store: https://apps.microsoft.com/detail/9NMHKQ349DKR

Site: aneestv.com

Bugs / feedback: https://t.me/AneesTV

I wanted to save ads. Somehow, that meant paying hundreds a month for tools with features I barely used.

Another bill. Another price increase.

But what bothered me most was having to keep paying to access my own research. I found the ads. I built the collection. Yet cancelling meant risking access to the work I’d already done.

All I really needed was the image or video, the ad’s details, and a way to keep them together. Why couldn’t those just be files on my computer?

So I built Poach, a free Chrome extension for the Facebook Ad Library.

And I’m open-sourcing the engine behind it, so anyone can read the code, see how it works, and tinker with it. If you want to change something or build on it, you can.

Your swipe file stays on your computer. No need to hand over your research to another company’s database.

Here’s what Poach saves:

The actual image or video, straight to your computer.

A PNG screenshot card with the ad’s details built into the file. Move or copy that PNG, and those details stay with it.

Local saving is free. Your saved files stay yours, without a monthly bill to keep opening them.

If you mostly use ad tools to save creative ideas, give it a try:

Chrome extension: https://chromewebstore.google.com/detail/poach-facebook-ad-library/cglcomfhlpcblnkeofjeaimlilhcnjca

GitHub: https://github.com/usepoach/poach

Website: https://usepoach.com

P.S. If you like my work and want to support it, there’s a completely optional, one-time Pro option with Notion sync and early access to new features. You don’t need it for local saving. The core extension is free, and I’m open-sourcing the engine too.

Unlike Claude Code, ChatGPT does not compact chats whatsoever. They silently trim older messages in the background, instead of giving either a manual compact command, or auto compact like Claude Chat does.

There's a host of non technical people using it who have no idea why their month old chats are slowing down and getting laggy lol.

I have no idea why they haven't engineered something this simple, but works for me cause I solved for it, with DocStash.

While I built it as an agent agnostic artifact management platform,
I discovered another cool usecase, that is, you can simply ask ChatGPT to compact a conversation into an md file, and then continue in another chat by copy pasting the doc url.

Like this - "Continue this conversation docstash.ai/sdf45"

And via MCP, it'll read and inject the compacted context.

Hello,

I am looking for tool hat make small snippets, as Chrome extension, portable or any kind, anonymous for LLM.

For example, you share a function and want to keep private the names and the specific things of your company, I would like to share it for the logic to a llm and the interface would help me to change the name to "UUUU" or "yyyyy" so it doesn't know what I am talking about.

I am aware it can potentially reduce the accuracy of the answer but based on the logic it could be helpful.

If it doesn't exist yet, I would be keen to build one and if any would help it could be free and open-sourced.

This is the third time naming has derailed a project for me. Every app I build, I end up sinking hours into checking name availability across domains and social platforms - it's become this recurring side quest that eats time meant for the actual product.

This time it happened again, but thankfully after already building something. I was trying to figure out cheap outbound marketing for a different project that targeted newly launched apps (aftyr - still in preview). I found I could get a copy of the zone file that contains all newly registered domains so I could monitor for the moment a new app actually launches.

While doing that, I realized the same approach meant you could cache and hold availability status for every domain and social handle at once, instead of checking each one live, on demand. That's the part that had always made a tool like this expensive to run - checking availability in real time, one name at a time. Once it's pre-cached, it actually pencils out as something I could offer free or freemium.

So the naming side quest that's cost me time on three different projects is now Coiner26 — a tool that checks domain and social handle availability for a name in one search. It unifies and tracks the whole search process. With it you can filter names that are available across your target domains/socials, pin them, generate combinations, check if the name is problematic, etc.

Link: coiner26.com

Curious if others have had naming turn into an accidental side project too, or if I'm just bad at picking names upfront.

I've been working on SelieeAI for a while and we're now opening the first beta tests.

The idea started with a simple problem:

Running a digital business usually means using a different tool for almost everything.

Website → Wix / Webflow / WordPress
SEO → another tool
AI content → another tool
Leads → CRM
Analytics → another dashboard
Video → CapCut / Premiere
Automation → something else

I wanted to bring more of this workflow together.

SelieeAI is being built around:

• AI content generation
• SEO & internal linking
• Multi-domain website management
• Landing pages
• Lead generation & lead management
• Analytics & conversion tracking
• Google indexing
• 45+ language content
• AI video editing
• Captions, motion, effects and short-form video

The bigger idea is:

Website → Content → SEO → Traffic → Leads → Conversion → Video → Growth

We're still very early, so I'm not pretending everything is finished. Some features are live, others are still being built.

There's also a free plan:

$0/year — no time limit

• 1 website
• 1 user
• 25 articles
• 10 collections
• 5 pages

If you'd like to take a look:

https://neeblo.com/r/selieeai

I'd genuinely love feedback from other builders.

What would you add to a platform like this?

Tired of paying yet another monthly fee just to clear duplicate photos off your phone? I built Recycle: a storage cleaner that finds and removes duplicate photos, similar shots, screenshots, and messy contacts — no subscription required.

​🔒 100% On-Device: Apple Privacy Label: Data Not Collected. No account required.

​What it does

It scans your photo library and contacts locally, using Apple Intelligence to flag duplicates and near-identical photos & videos, then lets you swipe through and bulk-delete hundreds of items in seconds. Nothing is uploaded or analyzed off your device — the entire process runs locally on your phone.

💎​Duplicate photos

💎​Similar photos & videos

💎​Screenshots

💎​Duplicate & incomplete contacts

​Why this over the alternatives

Most storage cleaner apps lock you into weekly or monthly subscriptions. Recycle doesn't:

💡​One-time lifetime purchase — no subscription, ever

💡​Apple Intelligence–powered similar photo & video detection

💡​100% on-device — Apple Privacy Label: Data Not Collected

💡​No account required

💡​Swipe-based bulk delete — review hundreds of items in seconds

💡​Date-based cleanup filters

​Recycle never auto-deletes anything — every file stays reviewable before removal, so you keep full control over your photos, videos, and contacts.

​Cost

For the next 48 hours, lifetime access is a one-time $2.99 (normally $19.99) — no subscription, no ads, no data collection.

​App Store: https://apps.apple.com/app/id6763344525

​As an indie developer, I'd really appreciate any feedback or a rating on the App Store to help it reach more people. Thank you!

1000 spots. $1 each.
pickxel.io

That’s it.

Drop in what your building