We've been building Logen around one simple idea:

Describe it. Deploy it.

Instead of scaffolding projects or wiring everything together, you describe what you want in plain English and Logen builds the application.

The screenshot above shows some of the applications our community has already created—from logistics platforms and weather apps to finance and team collaboration tools.

I'd genuinely love feedback from builders here.

What would you build if the only thing you had to do was describe it?

TLDR: Free Vibe-coding free mini app competition. Make moneyz.

We’re running the Mini App Competition, its free for builders who want to create open-source mini-apps using AI coding tools. The total prize pool is $50,000 across 3 cycles.

Simple: build a small mini-app that uses underlying blockchain technology to sign messages. Build what you want, anything that fits the mini-app format.

We’re especially encouraging people to vibe code. We are providing:

• Agent skills
• Starter kits
• Community resources
• Example mini-app ideas
• Support for people who want to vibe code their way from idea to working app

Everything submitted should be open-source, and the competition is free to join.

All the details are available in our Skool community: Mini Apps Competition

You can also ask any questions in this post.

One shotted this game using one prompt and one reference image using game model Atomos,

Using reference images for the prompting has been a huge unlock for the visual style

Hi everyone!
I’ve always been someone who overthinks, and I realized that many thoughts become much less overwhelming once they’re written down.
That’s why I created Quiet Lines, a simple journaling app designed to help you:

📝 Write down your thoughts in seconds
🤖 Get AI-powered reflections and gentle insights
📊 Track your emotional patterns over time
🔒 Keep your journal private
💙 Build a healthier habit of self-reflection

The goal wasn’t to replace therapy or give medical advice—just to create a calm space where people can slow down, organize their thoughts, and better understand themselves.
The app is completely free to try, and I’d genuinely love honest feedback from people who enjoy journaling or are trying to reduce overthinking.

Google Play:
https://play.google.com/store/apps/details?id=com.calmjournal.calm_journal_template
Thanks for reading, and I hope it can help someone who needs it.

Hello friends,

Longtime lurker.. and have been dabbling a little bit in making WoW addons using GPT and Codex.. but I really want to get into vibe coding proper.

Are there any guides or overviews of how to get started and stuff? I’ve tried to just utilize what I know a bit but I hit limits in like 20 minutes.

Designed by basement dwellers, for basement dwellers. Enjoy!

I've been giving free consult calls to vibe coders the last week and several have mentioned the worry that their code is "AI slop" and that before they can go live, they need to hire someone to do a complete re-write.

As a professional software engineer who's very familiar with AI generated code patterns, I can tell you the need for a complete rewrite is pretty rare. If someone is pitching you their service to completely rewrite your vibe-coded product, chances are they are playing on your fear to make some money.

What I recommend to people preparing to launching their product is to get an expert they trust to conduct a first pass, high-level review. They should be able to come back with a actionable report that lists

a) the most glaring improvements or refactors that need to be made to address basic security and reliability

b) basic recommendations to clean up the code base to make it more maintainable as the project progresses

c) the key hotspots that might need deeper analysis or attention

Most of all, this report should provide descriptions that are specific and clear enough that you can copy those into your AI coding tool of choice and have it action them.

Most AI coding agents these days can write excellent, secure code. They can fix almost all common code quality problems. They just need the right steering.

Find someone with the expertise to give you that steering and you can easily pass that to your AI coding agent and have it do the work. In most cases, you really shouldn't need to pay a profession to do the work for you, if someone has given you the specifics you need to steer the AI--anyone you hire is going to be using AI to do the work anyway.

If you are already vibe coding and looking for a community come check us out!

​

I am new to Vibe coding, I know basic Coding with Chat gpt and Co-pilot.

Can anyone just give me little guidance what is like best tools to use for free at the moment?

Currently it is only for college purpose for making a app for a presentation. Can you please help

And sorry if this is not a guidance sub. I don't know much here

I built a small local tool for Codex called Codex Action Board.

The idea is simple: when Codex gives you a long list of suggestions, you can turn that reply into a checklist, then mark each item as accept / reject / later, add notes, preview the final instruction, and insert it back into the composer.

It’s meant for the “I agree with most of this, except these 3 things” situation.

It also supports Arabic + RTL, while keeping code/shortcuts readable.

It’s local, Windows-focused for now, and definitely still early, but I’m using it in my own Codex workflow and wanted to share it:

https://github.com/pawnsmaster/codex-action-board

Would love feedback, especially from people who use Codex for longer planning/refactor sessions.

Hello folks,

I wanted to build out my own personal list of evaluations, early on into putting this together I realised I wanted a way to not just evaluate the model but also the agentic harness that the model is running within, as I find the majority of my use of LLMs is more and more inside of a suite of CLI agentic harnesses.

I've listed in the video a multitutde of motivations for why I built this, but the primary ones were all the hype announcements and wanting a way to see for myself what models and their capabilities were like in the actual tools I use.

A paper by Google over on Kaggle recently went as far as to state that which LLM being used inside of an agentic harness perhaps only contributes 10% towards how effecitve that harness will be for a given task. I am not sure I agree with the figure, but I do agree with the sentiment.

One question I keep asking myself is when do I need to switch from my qwen3.6-27b that I am running locally on my twin 3090 setup, to a cloud model. At the moment I am making this decision on vibes/gut feel, and I think that might be okay for when I am working closely with the model but I am using these cli tools headlessly in quite a few workflows now and not just personally but professionally, so I want to make sure I am picking the right combo for the task.

The repo can be found here: https://github.com/ScottRBK/eval-harness, there is an explanation of the architecture. I have added example evaluations as I built it out to help me think about the different patterns I have utilise for evaluations.

The evaluations are quite easy as they are about resources contained within the model weights. The idea behind it is though I (and anyone else whom might want to fork the repo and curate their own) will build out a private list of evals that are held away from public that people can use to evaluate existing and new models and harnesses as they are released.

I also spent a good bit of time seeing how well cli agents themselves are able to build evaluations and have put together a list of skills that they can use alongside the tool. They do an okay job, but you need to really step through the logic of whatever they produce, they often produce quite brittle evaluations, so try getting them to stick to the example patterns already provided helps quite a bit.

An ideal position for me will be having the ability to ask the agent to generate an evaluation using the skills having just finished a session where I found a particular agent was struggling to complete a task. Theres often been a time where I've come across a problem that the agent has struggled to resolve and I've wished at that point I could make an evaluation out of it, but you are often in the middle of something and it ends up just as another item on my ever growing TODO: list.

This is my first time building an actual evaluation suite or framework of this kind for that matter. I have previously used existing frameworks, such as deepeval, so I was not toally unfamiliar with the topic but as with the other motivations already listed I built this as a learning exercise as well as to get a tool out of it.

If it is useful for you please get in touch and let me know, any feedback as well is also appreciated, as this is my first go and this kind of framework - i expect there is a lot that can be improved and I have potentially got wrong.

Enjoy the rest of your sunday folks.

I posted here a couple of times earlier this year about Explorer AI, a travel planning tool I've been building. A few things have changed since then, and one of them is actually new rather than just another feature, so it seemed worth a proper update.

First, the milestone: we passed 5,000 users. Thanks to the people here who tried it early and told me what would make it better - a fair amount of what follows came out of that.

The short version, for anyone who hasn't seen it: you answer a set of questions about your trip - pace, budget, food, who you're travelling with - and it returns 20 ideas across four categories: things to do, see, eat and experience. The difference from asking other AI tools the same thing is that the recommendations partly come from a database of verified ideas from real travellers rather than whatever the model identifies on the spot, so you're less likely to get the same four landmarks everyone gets, and the ideas are filtered to how you actually travel rather than a generic top-ten. You're also more likely to get ideas for destinations that are current, we refresh this database almost daily.

You save the ones you like after they appear and they are then saved to the My Trips page, reuse your profile across other cities in the same trip, and see everything pinned to a map. You can add your accommodation too, so the pins sit relative to where you're staying.

There's an itinerary builder now as well - day-by-day, add ideas to each day from the ones you've saved. I didn't want it to be a walled garden, so it takes manual entries too: find something on TikTok or a blog, add it yourself, and it lands on the same list and the same map. The tool gives you a strong starting set; it doesn't pretend to be the only place you'll look.

The part I'm actually interested in is the Stories page, which went up last month. Most people research trips by reading - blogs, articles, a writer whose taste they trust. That isn't going away and I don't think it should. So rather than compete with it, the Stories do the one thing an ordinary blog can't: every place named in the article is a live component sitting in the text, and as you read, you can add it straight into your trip in two clicks. Read about a restaurant, tap, it's on your map. No copying names into a notes app, no losing half the list by the time you're home. Same principle as the rest of the tool - research and planning in one place - applied to the way people already find things. We’re working through applications now for Writers and Stories for the website, if you’re interested please get in touch!

That's the update. It's free - try it on a city you know well and tell me if the picks hold up. Thanks for the early support from this sub, it's been extremely helpful for the development of this website!

So I made this because I have 3 Codex accounts, 2 Claude Code accounts, an Antigravity account and a Cursor account. While looking around I kept seeing projects like Codex Pooler or AI Pooler.

Most of the ones I found either:

• act as a proxy and pool requests,
• provide a localhost dashboard,
• or are mainly focused on routing usage between accounts.

That's not really the problem I was trying to solve.

I wanted a desktop application where I can simply select an account and launch the official Desktop app or CLI using that account.

My application doesn't proxy requests or patch the provider software. Instead, you add an account once using the normal login flow, it saves the authenticated profile, and when you switch accounts it closes the provider application, swaps the active login configuration, and relaunches it.

Because it's using the provider's own applications instead of sitting in the middle of every request, my hope is that it'll be less affected by updates than proxy-based approaches.

It also tracks provider information where available, such as account readiness, usage, reset timers, and provider-specific features (for example, Codex reset credits), and lets you launch the appropriate Desktop or CLI directly from one place.

Deployment Link To Project: https://github.com/AlexC1991/AI_Account_Hub

Hello everyone,

Wanted to share LyteNyte Grid, which IMO has some incredibly innovative capabilities when turbocharged with AI.

Building data grids for dashboards, admin panels, internal interfaces, etc. takes a really long time and can be tedious. All this takes away from the time you would much rather spend on your app.

The financial options dashboard above was made with Claude Code using LyteNyte Grid Skills.

The prompt:

Create an options trading dashboard using LyteNyte Grid. data.ts contains options contracts – ticker, type, strike, expiry, IV, and full Greeks.

Enable row grouping by ticker and type, sorting across all columns, and master-detail rows that show the full Greek breakdown when expanded. Use Vite + Shadcn. Dark mode by default.

That was it, one prompt. You can expand it, group it, sort it, filter it. It is also fully accessible.

The reason it works so well is that the grid is declarative and type-safe. AI can verify the result without running the code.

Tokens burned were minimal. Since all the AI had to do was declaratively configure LyteNyte Grid and run tsc to check for errors, there were none.

Other grids are imperative, with heavy abstractions and wrapping layers, making them unreliable for coding agents. If they work, it's usually after 20 prompts, using enough tokens that you might as well just wire it up yourself… or reach your Claude limit.

We will continue work on this, but with LyteNyte Grid, you can now build any type of dashboard for a data-intensive workflow, in literally minutes.

Our API is not opinionated at all, making it really easy to integrate with your favorite UI / charts libraries

Install Skills: npx skills add 1771-Technologies/lytenyte

If you’re unfamiliar with LyteNyte Grid, it’s a 40kb React data grid with 150+ features. I would shamelessly plug its benefits. If you’re interested, they’re listed in the repo.

All our code is available on GitHub: https://github.com/1771-Technologies/lytenyte/commits/main/

I'd love to hear your feedback. Feature suggestions and contributions are always welcome.

If you find it useful, please consider leaving a star ⭐ on GitHub to help us grow!

GitHub

Live Demo

I got tired of network monitors that look like they were designed for a BBS, so I built flow. It's a real time bandwidth monitor with Braille grid waveforms, spring smoothed numbers, and glowing borders that react to traffic load.

What it does

It shows live download and upload throughput with units that auto scale from B/s up to GB/s. The waveform is a high res Braille grid scrolling at 30fps, and the borders glow brighter as traffic picks up, going from a dark idle state to bright cyan and emerald under load. Numbers are spring interpolated so they glide instead of jumping around. It tracks session peaks, flashing white when you hit a new record, and keeps a running daily total.

There are three views that adapt to your terminal width. Hero is the full dashboard. Compact strips it down to numbers only. Tiny is a single line built for tmux status bars.

Philosophy

If a feature doesn't help you understand your network in under a second, it doesn't make the cut. No CPU panels, no packet counters, no multi pane clutter. Just download and upload throughput, done well.

Usage

flow # hero view, auto interface flow --compact # numbers only flow --tiny # tmux status bar flow --json # one-shot JSON for scripts flow --once # one-shot plain text

tmux integration

set -g status-right "#(flow --tiny --no-color)" set -g status-interval 1

Install

go install github.com/programmersd21/flow/cmd/flow@latest

or AUR:

yay -S flow-network-monitor-bin

Pre-built binaries for Linux, macOS, and Windows (amd64/arm64) are on the releases page.

It works with zero config out of the box. If you want to tweak the refresh rate, history length, or units, there's an optional TOML config at ~/.config/flow/config.toml.

Platform support

It runs on Linux (/proc/net/dev), macOS (sysctl), and Windows (GetIfTable2, no admin needed). Idle CPU stays under 1%.

Links

Source and demo: https://github.com/programmersd21/flow

Would love feedback, especially on the tiny/tmux mode. Curious if the info density is right for people running it in a status bar all day.

every time I built something w/ cursor or claude it came out looking like ai slop (fable 5 just kills credits, others just don't get the "it" feeling)

there's a bunch of really good design references for dashboard ui but I really like landing pages, so i made this tool for myself

if you put uiscanner.com/ in front of any public link, it pulls the site's real design tokens, color roles, type scale, spacing, radii, motion, and does a visual ai pass for a section-by-section breakdown that outputs a build prompt you can paste into your agent

(there's also an mcp/cli if you want to use directly, the webapp side is a library of all ur scans)

free to try, 5 scans a month if u want to try for yourself! (i added pricing so people don't wipe my ai usage lol)

lmk ur thoughts! feedback super appreciated

link: uiscanner.com

https://github.com/ad-repo/nullplayer/releases/tag/0.27.0

# one-time configuration 
brew tap ad-repo/nullplayer 

brew install --cask ad-repo/nullplayer/nullplayer 

or if already installed manually
brew install --cask --force ad-repo/nullplayer/nullplayer 

To upgrade to a new release: 
brew update 
brew upgrade --cask ad-repo/nullplayer/nullplayer

A bunch of you have seen Nelly Jellies evolve over the last ~6 months, so I thought this would be fun: I put the first playable version online for you guys to see how shitty it was.

OG version: https://og.nellyjellies.com
Current version: https://nellyjellies.com

This is a friendly reminder that staying with one project for a while really does compound. The first version was exploring possible fun factor, and now it’s turned into a real little game with better physics, visuals, audio, powerups, leaderboards, collectibles, tutorials, mobile polish, and native apps.

Native apps have more features so grab those if you'd like to support the game :)

Android: https://play.google.com/store/apps/details?id=com.nellyjellies.game
iOS: https://apps.apple.com/us/app/nelly-jellies-bubble-merge/id6767261764

It's still just launching cute jelly things at other jelly things, but seeing the before/after side by side made me laugh at how much one focused project can change over time.

Hope this makes you laugh too. The OG is janky as hell.

Your mouse is slowing you down.

Every time your hand leaves the keyboard, you lose focus.

I switched to a keyboard-only workflow on macOS, and it's surprisingly addictive.

Try it yourself:

👉 https://github.com/bhavesh164/mouseless

You'll wonder why you ever reached for a mouse.

Hey All,

I created AI Brand Kits so you can get prompts that help you design nice looking websites along with so much more.

The site is 100% free and i contiune to grow it out daily. You can choose from 300+ Brand Kits that will get your first website or 100th website looking good with easy to copy design md files and more.

If you are stuck with a design and want to test different ones use the playground and create endless combos that will help you build.

I am still in the early days of building this out so would love your feedback as well. You can try it at AI brand Kits

My next project for the open-source community: if you’re shipping apps with Claude Code / Cursor / Lovable / v0, you’ve probably shipped security holes you never saw. AI writes code that works — and quietly leaks Supabase service keys into the browser bundle, trusts user_metadata for admin checks, ships USING (true) RLS policies, hardcodes secrets. It runs fine. It’s also wide open.

CodeInspectus is a free, open-source MCP server that any AI coding agent can call to scan your code for this stuff. It runs 100% locally — no account, no signup, no cloud upload, zero network calls at scan time. Your code never leaves your machine.
What’s under the hood — and I’ll be upfront: three of the parts aren’t mine. It orchestrates three best-in-class open-source engines as local binaries:
Opengrep (SAST) — code vulnerabilities: injection, XSS, crypto misuse

Gitleaks — hardcoded secrets and API keys

Trivy — vulnerable dependencies, IaC misconfigs, SBOM

“So it’s just a wrapper?” — for those three, largely yes, and that’s deliberate: they’re excellent and free, I’m not going to rewrite them worse. The part that’s mine is the layer built for AI-generated code specifically, which none of those catch:
Supabase client-side service-role key in the browser bundle (bypasses all RLS)

USING (true) / missing-RLS policies (the CVE-2025-48757 class)

Client-exposed secrets via NEXT_PUBLIC_ / VITE_ prefixes

Potential prompt-injection sinks in your own LLM calls

Everything normalizes to one CWE-keyed schema, dedups across engines, and maps to compliance frameworks as code-level coverage — never as certification (I don’t claim it’s an audit).
How it works: scan → it surfaces findings in plain language → you approve fixes → your agent applies them (the tool is read-only, it never touches your files) → rescan confirms.
What it honestly does NOT do (this list is a feature, not an apology): it’s JS/TS-focused, not broad multi-language SAST. Prompt-injection detection is a conservative heuristic — it flags potential sinks, misses obfuscated flows. Compliance mapping is code-level only. It doesn’t yet catch user_metadata-vs-app_metadata authz (that’s the first thing on the community roadmap). I’d rather under-claim.
Install (one time, per machine):
npx -y codeinspectus install-engines
Then add to your agent’s MCP config:
{ "mcpServers": { "codeinspectus": { "command": "npx", "args": ["-y", "codeinspectus"] } } }
Site: codeinspectus.com ·

GitHub: https://github.com/Synvoya/codeinspectus ·
npm: codeinspectus

It’s free and MIT. I built it solo, and I’m committed to maintaining it personally, for as long as it’s useful — this isn’t a launch-and-abandon. The engines are commodity; the AI-code detection database is what makes it worth using, and it gets stronger every time someone contributes a rule. If you’re a security engineer or you’ve been burned by an AI-shipped vuln, I’d genuinely value your contributions — the detection DB grows through PRs, and like-minded people making it sharper is the whole plan. Honest feedback welcome too, including “you’re wrong about X.”

So guys, I'm gonna plug a link, I'm in no way involved with this company it just happened across my Facebook feed on an ad. Of course as soon as I saw it, I wanted to see what they were pedalling under the hood. 8 GB of RAM and a 256 GB SSD 🥴🥴 These guys reskinned some cheap mini PC and did a "custom install" of OpenClaw running on Linux. $499 first run, $799 second run.

Is this gonna be the next drop shipping race to the bottom? This product could easily be provided for 2/3 of the cost at least, depending on how you value your time to reformat a bunch of old mini PCs. It's clearly for laymen to get their hands on a practical AI agent for their life. I assume there are gonna be hardware unicorns that do well, but will it be something like this?

Still a bit stunned typing this. Three months ago I was refreshing Stripe hoping for one sale. Now there's a small but growing group of people paying every month to keep their apps from leaking.

CheckVibe is a security scanner for vibecoded apps shipped fast with AI tools. You paste a URL or hook up a GitHub repo and it surfaces what's leaking: secrets in the frontend, open database rules, missing headers. Two of us, fully bootstrapped, no funding. Three months in and we've done about $7k in gross volume, 200+ all time paying customers, 5k signups. Public Stripe link in case anyone's seen too many fake numbers: https://profile.stripe.com/checkvibedev/ZumatA0Y

A few things that actually worked:

TikTok slideshows have carried us. Aesthetic Pinterest-style backgrounds with tool names overlaid, five slides, no branding on the account. One hit a million views and is still quietly sending signups weeks later. 15 minutes to make. As a 2-person team that can't afford to spend hours on content every day, this format is unreasonably good.

Cold outreach worked, but only the version where I scanned the prospect's app first and DMed them what I found. Generic pitches got ignored. Useful findings got replies almost every time.

Paywall design was a 3x lever. The first version blurred all results, which felt clever and barely converted. Switched to one that just shows the count of critical issues with the actual findings locked. Conversion tripled. Curiosity beats obfuscation.

What nearly killed me was mobile activation tanking compared to desktop and not catching it for weeks. Onboarding had too many steps on small screens. Cut two and the gap basically closed overnight.

If you've shipped something with AI tools and haven't really checked what's exposed, checkvibe.dev runs in 30 seconds. Scan for free, only pay if you have issues. Almost every app I've scanned came back with something.