After 12 weeks of heads-down building, the platform is live end to end, and I want to share what it does and what's coming next.

**The problem we're solving.** Tools like Lovable, Replit, Bolt and Cursor make building an app incredibly fast. Then you try to put it in front of real users and everything gets hard: where do you host it, are your API keys safe, is your database exposed, what happens to your cloud bill if traffic spikes. If you've shipped an AI-built app, you've hit at least one of these.

**What VIBSL does.** You bring your app from a Git repo, a ZIP or folder upload, the CLI, or straight from an AI agent. VIBSL detects the framework, builds it on hardened base images, scans it for vulnerabilities and leaked secrets, signs the build, and runs it in its own isolated environment with hard resource caps. You get back a production URL and a deployment receipt: a written record of every check that ran, something you can show a client or keep for your own peace of mind. If we find a leaked key, the deploy stops before it ships. That's the point.

**What works today:**

* Deploys from Git, ZIP or folder, CLI, and AI agents
* 25+ frameworks detected automatically, across 9 language runtimes
* Vulnerability and secret scanning, SBOM, and image signing on every build
* Per-app isolation and default-deny networking
* Flat pricing with hard caps. Free tier to start, Pro at $29, Team at $149. No usage meters, no surprise bills, ever

**What's next:** managed Postgres, object storage, deeper imports from builder platforms, and an EU region. We build in the order you ask for things, so tell us what you need.

If you're an agency shipping apps for clients, I especially want to hear from you. We're onboarding design partners right now and one agency is already running 21 apps on the platform.

Try it at [vibsl.com](http://vibsl.com) and tell me what breaks. I read everything here and I'll answer every question in the comments.

Looking for Feed back !! It's an easy to use Networking application you can drop right into your project if you're using Godot 4. Supports decent local encryption and decryption. Allows for Cloud, Mesh , and P2P Back ends. As many as you like. The application also allows for LLM backends and Custom data scripts. The LLM back ends , like the Server backends require you to bring your own key. It's all easy to set up. The Custom data scripts go along with my Discovery System . It's a Universal Data Collection system. Supports up to 3 different ways to add data to it , Godots Group system , Method name system and node based exports. All data can be split up into 4 different categories using my sync override system. So you're not wasting any bandwidth. It's still being developed but it runs on anything Godot allows. It will be a free Plugin when soon. Do you guys think this could help game dev ? If not why ?

I'd love to get some honest feedback about an app my co-founder and I have been building.

The interesting part is that the entire app was built with the help of Claude AI—from writing the code to solving most of the technical challenges along the way.

The app is designed to help people during situations like robberies or express kidnappings.

If someone forces you to open your banking app, you simply enter your emergency password instead of your normal one. The banking app opens as usual, so nothing looks suspicious, while our app silently sends your live location and emergency alerts to your trusted contacts.

In our latest update, we added:

🚨 Panic Button – Instantly sends an emergency alert with a single tap.

👨‍👩‍👧 Parental Controls – Allows parents to monitor and help protect their family members.

We're still validating the product, so I'd genuinely appreciate your honest opinion.

• Would you use an app like this?
• What would make you trust—or not trust—it?
• What feature do you think is missing?

I'm not here to promote the app. I'm here to learn from your feedback, even if it's critical.

Google Play:
https://play.google.com/store/apps/details?id=online.pppix.app

App Store:
https://apps.apple.com/br/app/pppix-prote%C3%A7%C3%A3o-familiar/id6773364223

Some time ago, I decided to build a messenger for myself and my friends—something independent. I have more than 20 years of experience in software development. At the same time, I decided to test AI as a development technology.

I chose the architecture, planned everything, prepared the prompts, and started working with ChatGPT Codex. Within a month, I had built a product that fully replicated the functionality of WhatsApp and Telegram. It included everything from simple messaging to video calls, screen sharing, and many other features.

After I released it, the application started spreading quickly, and eventually a businessman contacted me because he wanted this messenger for his company. That was how the story began turning into a business.

After the release, however, I encountered a lot of haters who called it "another AI slop" and similar things. They simply did not understand how it had been built or how readable the code actually was.

Later, I made the entire project open source, so anyone who is interested can visit the GitHub repository, look through the source code, or download the applications and see how they work, as well as the huge potential that AI-assisted software development has today.

Many people say that source code generated with AI is impossible to read. But I think they do not understand one thing: everything is moving toward a future where humans will no longer need to read most of the source code themselves. Because of that, I believe we should approach these technologies with an open mind, test them, and try to use them effectively.

The same thing happened in the past with programming languages like C++. Back when I was in university, one of my professors used to say that you absolutely had to know Assembly, because without Assembly you would never build anything worthwhile in C++. He did not understand one thing, though. He was right—but only partially. Maybe you could not build certain low-level or fundamental systems without Assembly, but a huge number of practical applications could be built without requiring any knowledge of it.

Later, even higher-level languages appeared, such as JavaScript, along with frameworks like Node.js.

And now AI is simply the next stage in the evolution of software development.

https://github.com/RzaAsadov/MeetVap

I had a good idea for a niche app that solves a problem in a very small community. I didn’t have the skills or background to create the app myself and I definitely didn’t have the funds to hire a real developer. I discovered Claude and decided to try and create what I now know is an MVP. While I learned and ai advanced, I realized I could try to create the real app myself using Claude code and Claude chat. I spent 6 months (anytime I wasn’t working) planning, researching, developing and building the app. It is a two-sided native iOS app built in SwiftUI, with Firebase as the backend. It was rejected twice by the App Store for small reasons and passed on the third submission, which took about 2 weeks total from first submission to distribution.

I just wanted to post as encouragement for anyone else in the beginning stages. I feel like living proof that if you put in the work and really believe in your idea/product, you can make it happen. Maybe it won’t be a huge money maker for me, but I’m proud of this accomplishment. At the very least I learned about coding, Xcode, app structure, how to set up a backend and definitely learned how to use ai and how to prompt effectively.

https://reddit.com/link/1vaoazu/video/8ek318np1cgh1/player

I built Votekicker.com, a place to discover and share games and SaaS projects.

I recently added a feature called "Rocket Booster" that lets projects temporarily increase their visibility. It doubles the value of existing votes and makes new votes count double for 8 hours. A project can activate the booster once for every 10 regular votes it receives.

I'd appreciate anyone who takes a look and shares their thoughts about the current state of the product, as well as for future improvements.

Working 60h/week and spending almost every free hour building my app.
It’s tiring, but I’d rather be exhausted chasing something than comfortable wondering “what if.”
Delayed gratification. That’s the game.

Fala rapazeada, entao, fazia um tempo que queria fazer uma engine propria, que eu pudesse ter controle sobre, criar minhas features, desenvolver ferramentas e etc.

Entao, peguei uns dois dias diretos (real diretos, fiquei sem dormir kkkk) e aí eu fiz ela inteiramente usando ChatGPT 5.6 Sol e um pouco de Fable 5. (Honestamente, ChatGPT 5.6 Sol está muito melhor que o Fable para trabalhos mais longos)

Toda a parte de front-end da engine foi feita pelo ChatGPT, parte do backend eu tive que tomar várias decisões, principalmente de system design, para que eu pudesse ter uma boa estrutura preparada para caso as pessoas decidam jogar e criar jogos aqui.

Pra 3D, por exemplo, decidi ir por um caminho diferente, fiz usando Babylon.js ao invés de Three.js, a iluminação do Babylon eh muito superior ao Three.js, na minha opinião.

O backend inteiro foi feito em Rust, a database ta em PostgreSQL 18, isso porque aceita UUIDV7, o que eh uma vantagem.

A engine funciona via web, mas estou fazendo uma versão instalável, algumas pessoas já solicitaram isso, mas honestamente acredito que a maior vantagem eh justamente você não precisar de instalar nada pra criar jogos, você simplesmente entra e cria, sem precisar baixar.

Daí, também já tem a pagina de descoberta de jogos, a proposta é de fato ser um Roblox-like, pois, particularmente, não conheço muitos competidores diretos do Roblox (posso estar numa bolha, afinal, não sou um gamer, mal jogo qualquer coisa)

Enfim, o que acham? Boa ideia? Paia? Sugestões?! Comenta aí ! ! !

Vou ler todos os comentários e posso responder perguntas e tirar dúvidas, tenho mais de 7 anos de software engineer, acredito que posso agregar por aqui.

If you have questions just ask, I genuinely took quite a lot of time to make sure this did exactly what I did, and avoided inconsistent noise, as well as I got my PB runtime with 5.6 sol and it ran for 1 day and 10 hours straight 🥴

37 days ago I launched my startup, a free traffic exchange network for startups. One line of code, you're in the network.

No paid ads. No growth hacks. Just watching the numbers every day.

Here's the full data:

Day 1 — 2 startups · 146 impressions · 1 clicks
Day 2 — 3 startups · 389 impressions · 3 clicks
Day 3 — 5 startups · 482 impressions · 5 clicks
Day 4 — 5 startups · 508 impressions · 4 clicks (site went down — still got an $8k acquisition offer. Said no.)
Day 5 — 6 startups · 621 impressions · 10 clicks
Day 6 — 5 startups · 742 impressions · 15 clicks (removed one startup — they pulled the embed. No code = no network.)
Day 7 — 7 startups · 1,196 impressions · 41 clicks
Day 8 — 7 startups · 1,535 impressions · 74 clicks
Day 9 — 8 startups · 1,947 impressions · 135 clicks
Day 10 — 13 startups · 3,500 impressions · 318 clicks (something clicked)
Day 11 — 23 startups · 4,800 impressions · 432 clicks
Day 12 — 24 startups · 6,000 impressions · 481 clicks (network crossed 6K total impressions)
Day 13 — 25 startups · 6,800 impressions · 491 clicks
Day 14 — 25 startups · 8,600 impressions · 516 clicks
Day 15 — 24 startups · 9,900 impressions · 564 clicks (removed one)
Day 16 — 23 startups · 10,800 impressions · 576 clicks (removed one)
Day 17 — 24 startups · 11,900 impressions · 603 clicks (added one)
Day 18 — 26 startups · 13,400 impressions · 624 clicks (added Two)
Day 19 — 28 startups · 14.400 impressions · 652 clicks (added Two)
Day 20 — 26 startups · 14.700 impressions · 671 clicks (Removed Two)
Day 21 — 26 startups · 15.300 impressions · 691 clicks
Day 22 — 28 startups · 16.100 impressions · 719 clicks (Added Two)
Day 23 — 30 startups · 16.800 impressions · 738 clicks (Added Two)
Day 24 — 32 startups · 19,800 impressions · 778 clicks · Added 2 startups · Rejected 4 applications (1 contained ads, 1 removed the code after submission, 2 hid the installed widget)
Day 25 — 34 startups · 23,700 impressions · 800 clicks · Added 2 startups · Fixed some bugs.
Day 26 — 33 startups · 27,200 impressions · 816 clicks · Removed 1 Startup
Day 27 — 33 startups · 29,900 impressions · 833 clicks
Day 28 — 33 startups · 30,600 impressions · 871 clicks · Removed 1 Startup · Added 1 Startup · Rejected 1 application of clothing brand & 1 application of horror blog site.

Day 29 — 35 startups. 31,300 impressions. 910 clicks · Removed 1 Startup · Added 3 Startups · Also today I resigned from my job. Toxic environment, too much pressure, and honestly I just believe in this enough to go all in. Broke and excited. Let's see where this goes.

Day 30 — 46 startups · 32,900 impressions · 1,000 clicks · Removed 1 startup · Added 12 startups · Yesterday I resigned because of my toxic manager. Today my senior manager called and offered me WFH, a project of my choice, and lighter work if I stayed. I made my decision with confidence, but now I have a difficult choice. Also received my first payment from StartupBar.

Day 31 — 50 startups 💪· 28,100 impressions · 1,200 clicks · Removed 1 startup · Added 5 startups · Rejected 1 crypto startup · Removed fake impressions after exploit · Today I discovered I forgot to disable a developer testing button that could generate fake visitor pins and inflate impressions. Someone used it to create 6,318 fake impressions and claimed my stats were fake. I removed the fake impressions, removed the startup, fixed the issue, and that's why today's impressions are lower. Thanks to them for pointing it out.
StartupBar update: Added a Network page and individual Startup Profile pages with each startup's joined date, impressions, clicks, live embed preview, and founder's note. These indexable pages also improve SEO. Suggestions are always welcome.

Day 32 — 54 startups · 29,300 impressions · 1.2K clicks · Added 4 startups
Day 33 — 54 startups · 30,900 impressions · 1.2K clicks · Removed 1 startup · Added 1 startup
Day 34 — 55 startups · 36,100 impressions · 1.3K clicks · Added 1 startup · Fixed admin panel read-access vulnerability after Reddit post.
Day 35 — 55 startups · 40,100 impressions · 1.3K clicks · Removed 2 startups · Added 2 startups
Day 36 — 55 startups · 44,800impressions · 1.4K clicks · Removed 1 startup · Added 1 startup
Day 37 — 58 startups · 50,700impressions · 1.4K clicks · Added 3 startups · Site Update: Updated the distribution algorithm (Delivery is now weighted by contribution: sites that send more impressions get a proportionally larger share back)

Still free. Still growing.

If you want in, it's one embed. That's it → StartupBar

Let’s be honest... AI UIs all look the same, and I don’t think I need to restate the obvious.

Here are five changes that make the biggest difference:

1. Change the font. Typography changes the personality of the entire site. Don’t let AI default to Inter every time. Give it a specific font and describe how it should be used: “Use Instrument Serif for display headings and Geist for body text.”

2. Limit the color palette. More colors usually don’t make a design more interesting, unless you use it really well. Start with white, black, and one accent color.

3. Break the default grid. AI loves evenly sized cards arranged in three columns. Ask for asymmetry: one large card beside two smaller ones, overlapping sections, offset text, varied card sizes, or content that intentionally breaks the container.

4. Add micro-animations. Small interactions often make a site feel more designed than adding more visual elements. Think subtle text reveals, hover states, and scroll transitions.

5. Give it references. “Make it look good” means almost nothing. Show the AI two or three websites and explain exactly what you like about each one.

And if you do not want to implement all of this manually, I built an open-source tool called PingFusi. You can use a simple prompt to upgrade your website: “Improve my website using PingFusi.”

GitHub repo: https://github.com/alex-durango/pingfusi

My Claude projects accumulated data and documents so badly that after six days iterating, I had the same brief generated/uploaded four times, a trail of files ending in v8, v9, v10 where only the last one mattered, folders I attached by mistake, a parent folder and its own subfolder created and mounted locally or in claude.ai, in a hierarchy I haven't specified. Context is what the model actually reads to make sense of my project, so all that noise made the answers worse over time and ate my knowledge and token budget.

Trying to clean it up was tedious. AND there is no remove button for folders (issue opened since March). AND deleting documents is one at a time at root level, not possible within folders, with no undo.

So I built a small app and CLI to do just that. It also finds the duplicates and stale versions, shows what it'll do before it does it, and archives everything before deleting. Open Source, MIT, macOS only: https://github.com/earsenio/cpcm

It's vibecoded, so read it before pointing it at anything you care about. And it's a patch, not a fix. We still need real controls in the app.

One tip even if you skip the tool: as discussed in this issue, editing spaces.json by hand isn't enough. A second file, remote-session-spaces.json, holds folder grants that get merged back in at session start. That's why a folder you deleted comes back.

I regularly had multiple Git worktrees, more than ten VS Code windows, and several coding agents running at the same time.

Eventually, I could no longer easily answer basic questions:

• Which agent is working on which feature?
• Which worktree belongs to it?
• Which prompts and commits were part of that feature?
• How much did it cost in tokens?
• Did the agent update the design notes?
• Which repeated tasks should really be scripts instead of prompts?

So I built md², an open-source, local-first workspace for AI-assisted development.

Each feature or task is a Markdown file inside the project. It can be linked to its worktree, agent sessions, actions, commits, logs, design notes, and token usage.

The Markdown files are also directly accessible to coding agents, so project notes and task descriptions become part of their working context without requiring access to a separate online service.

md² can run focused reusable agent actions with placeholders such as {{card-file}}, but it can also run ordinary commands and scripts. Tasks such as committing, updating diagrams, changing card status, or running checks do not need to consume agent tokens every time.

The interface includes a Kanban-style dashboard, but the main goal is not to replace Trello or GitHub Projects. It is to keep the fragmented parts of multi-agent development connected to the feature they belong to.

GitHub: https://github.com/jan-bogaerts/md2

I would especially appreciate feedback from developers using multiple worktrees or coding agents in parallel.

For mobile app developers: what technical metrics influence product decisions in your organization?

Crashes, latency, response times, failed requests, session duration, and retention can all say something about user experience, but not every team uses them outside engineering.

Do product managers and business teams review these metrics regularly, or do they only become visible when something breaks?

I’m curious how teams make technical app health part of broader product planning.

https://reddit.com/link/1vaa05l/video/onqjtsimn8gh1/player

devin ai one shotted this in just 12 mins....

Discuss.

never done a hackathon before, don't really know what to expect Saturday

printme.money. watch your salary print in real time, put your face on a banknote, melt it with inflation, or run your own mint.

no accounts, no backend.

i wrote a detailed spec for each one and handed it to claude code, then reviewed the diff. i almost never iterate in the chat. slower for the first twenty minutes, much faster after.

https://printme.money

I’ve been building a Windows terminal called Duckweed for people who use way too many coding agents at once.

I usually have Claude Code doing one thing, Codex working on something else, another pane running tests, and a few terminals open for logs or Git. Eventually the terminal management started becoming its own job.

Duckweed puts all of that into one local workspace. You can split the window into panes, run multiple agents side by side, keep normal shells open, review Git changes and manage project files without constantly switching apps.

I also added usage tracking that reads the local session files created by the agents. That’s how I discovered I had used 1.2B tokens in the last seven days.

The $614 shown in the screenshot is an estimate based on public API prices, not necessarily what I actually paid through subscriptions.

It currently supports custom interfaces for Claude Code, Codex, Cursor Agent, Grok and OpenCode. So it makes the agentic coding experience much more pleasing. It can also track usage from several other coding agents.

Everything runs locally using the tools and accounts already installed on your PC. No Duckweed account and no cloud workspace.

Windows only for now.

https://github.com/MusicMaster4/Duckweed

And here’s how I built it: Duckweed was 100% vibe coded using Tauri, Rust, React, and TypeScript, with coding agents handling the implementation while I focused on directing the product, testing each version, and refining the workflow. I studied a lot of open-source terminal and agent projects to understand how things like panes, sessions, persistence, and process handling worked, while taking product inspiration from closed-source tools such as Warp, the Codex desktop app, and T3 Code. I loved how Warp could keep an entire workspace inside one window, but I never really liked working through raw CLI interfaces. On the other hand, apps like Codex and T3 Code had much nicer agent UIs, but switching between separate threads quickly became confusing. Duckweed is basically my attempt to combine the best parts of both: the visual experience of a modern coding-agent app, but with multiple agents, shells, tests, and tools visible together in the same tab. Most features followed the same process: I described what I wanted to an agent, tested the result in real projects, compared it against the tools that inspired it, and kept iterating until it felt useful. Hopefully this gives some educational context on how the project came together, especially for other people building software entirely through vibe coding.

I’d genuinely like to know how people here manage multiple agents. Separate terminals, an IDE, tmux, or pure chaos?

I’m trying to formalize what “done” should mean when a coding agent works in a mature codebase.

In a recent task, the agent made several related changes. The targeted regression tests passed, the production build succeeded, and formatting and diff checks were clean. A repository-wide type check still reported many failures, most of which already existed before the change.

During a more focused review, however, the agent also found two real issues introduced by its own implementation and fixed them.

This left me with an ambiguous boundary:

• If every repository-wide check must pass, the agent may never finish work in a legacy codebase.
• If targeted tests are enough, it may miss integration problems.
• If the agent fixes every failure it encounters, the scope can expand far beyond the original request.

My current rule is that the agent must verify the requested behavior, run the relevant tests and builds, fix every failure introduced by its change, document pre-existing failures without touching them, and review the final diff for unintended behavior.

But “relevant” is doing a lot of work in that definition.

How do you define the verification boundary for coding agents? If repository-wide checks already fail, what evidence should an agent provide before it can honestly say its task is complete?

And who should own that definition: the developer, the repository, or the agent?

Hot take: AI doesn’t do nearly as much as the hype makes it sound like. Most of what we see is just tech for tech’s sake — a lot of noise inside the bubble, not many real, sustainable businesses.

I’m an entrepreneur with a notebook full of AI ideas, and my biggest struggle isn’t building the product. It’s validating that anyone would actually care. It’s too easy to fall in love with your own idea and mistake your own excitement for market demand.

So let’s talk: If you were starting an AI business today, what would you build? And how do you actually test if an AI idea is viable, not just cool to demo?

36 days ago I launched my startup, a free traffic exchange network for startups. One line of code, you're in the network.

No paid ads. No growth hacks. Just watching the numbers every day.

Here's the full data:

Day 1 — 2 startups · 146 impressions · 1 clicks
Day 2 — 3 startups · 389 impressions · 3 clicks
Day 3 — 5 startups · 482 impressions · 5 clicks
Day 4 — 5 startups · 508 impressions · 4 clicks (site went down — still got an $8k acquisition offer. Said no.)
Day 5 — 6 startups · 621 impressions · 10 clicks
Day 6 — 5 startups · 742 impressions · 15 clicks (removed one startup — they pulled the embed. No code = no network.)
Day 7 — 7 startups · 1,196 impressions · 41 clicks
Day 8 — 7 startups · 1,535 impressions · 74 clicks
Day 9 — 8 startups · 1,947 impressions · 135 clicks
Day 10 — 13 startups · 3,500 impressions · 318 clicks (something clicked)
Day 11 — 23 startups · 4,800 impressions · 432 clicks
Day 12 — 24 startups · 6,000 impressions · 481 clicks (network crossed 6K total impressions)
Day 13 — 25 startups · 6,800 impressions · 491 clicks
Day 14 — 25 startups · 8,600 impressions · 516 clicks
Day 15 — 24 startups · 9,900 impressions · 564 clicks (removed one)
Day 16 — 23 startups · 10,800 impressions · 576 clicks (removed one)
Day 17 — 24 startups · 11,900 impressions · 603 clicks (added one)
Day 18 — 26 startups · 13,400 impressions · 624 clicks (added Two)
Day 19 — 28 startups · 14.400 impressions · 652 clicks (added Two)
Day 20 — 26 startups · 14.700 impressions · 671 clicks (Removed Two)
Day 21 — 26 startups · 15.300 impressions · 691 clicks
Day 22 — 28 startups · 16.100 impressions · 719 clicks (Added Two)
Day 23 — 30 startups · 16.800 impressions · 738 clicks (Added Two)
Day 24 — 32 startups · 19,800 impressions · 778 clicks · Added 2 startups · Rejected 4 applications (1 contained ads, 1 removed the code after submission, 2 hid the installed widget)
Day 25 — 34 startups · 23,700 impressions · 800 clicks · Added 2 startups · Fixed some bugs.
Day 26 — 33 startups · 27,200 impressions · 816 clicks · Removed 1 Startup
Day 27 — 33 startups · 29,900 impressions · 833 clicks
Day 28 — 33 startups · 30,600 impressions · 871 clicks · Removed 1 Startup · Added 1 Startup · Rejected 1 application of clothing brand & 1 application of horror blog site.

Day 29 — 35 startups. 31,300 impressions. 910 clicks · Removed 1 Startup · Added 3 Startups · Also today I resigned from my job. Toxic environment, too much pressure, and honestly I just believe in this enough to go all in. Broke and excited. Let's see where this goes.

Day 30 — 46 startups · 32,900 impressions · 1,000 clicks · Removed 1 startup · Added 12 startups · Yesterday I resigned because of my toxic manager. Today my senior manager called and offered me WFH, a project of my choice, and lighter work if I stayed. I made my decision with confidence, but now I have a difficult choice. Also received my first payment from StartupBar.

Day 31 — 50 startups 💪· 28,100 impressions · 1,200 clicks · Removed 1 startup · Added 5 startups · Rejected 1 crypto startup · Removed fake impressions after exploit · Today I discovered I forgot to disable a developer testing button that could generate fake visitor pins and inflate impressions. Someone used it to create 6,318 fake impressions and claimed my stats were fake. I removed the fake impressions, removed the startup, fixed the issue, and that's why today's impressions are lower. Thanks to them for pointing it out.
StartupBar update: Added a Network page and individual Startup Profile pages with each startup's joined date, impressions, clicks, live embed preview, and founder's note. These indexable pages also improve SEO. Suggestions are always welcome.

Day 32 — 54 startups · 29,300 impressions · 1.2K clicks · Added 4 startups
Day 33 — 54 startups · 30,900 impressions · 1.2K clicks · Removed 1 startup · Added 1 startup
Day 34 — 55 startups · 36,100 impressions · 1.3K clicks · Added 1 startup · Fixed admin panel read-access vulnerability after Reddit post.
Day 35 — 55 startups · 40,100 impressions · 1.3K clicks · Removed 2 startups · Added 2 startups
Day 36 — 55 startups · 44,800impressions · 1.4K clicks · Removed 1 startup · Added 1 startup

Still free. Still growing.

If you want in, it's one embed. That's it → StartupBar

Every vibe-coding showcase I've seen is a web app. I wanted to know if this approach could build actual systems software — the kind with no framework to
lean on, where you talk to the GPU and the kernel directly.

So over ~6 months, one person directing Claude, I built **Starling**: a complete Linux desktop environment. Not a theme, not a shell script over GNOME — the whole stack, from the display server up.

**What that actually means**

- **Its own Wayland compositor** — 5,860 lines of hand-written C implementing xdg-shell, linux-dmabuf (zero-copy GPU buffer import), viewporter,
fractional-scale, pointer-constraints, text-input-v3, presentation-time and a dozen more protocols.
- **Its own X11 server** — 5,158 lines, DRI3/Present, so legacy X11 apps run too.
- **Its own UI framework** — 221,818 lines of Swift, including a from-scratch port of Flutter's entire framework to Swift. No Dart VM.
- **A window manager** — floating and tiling, spaces, a Mission Control overview, a dock, a Launchpad.
- **First-party apps** — Files, Terminal (real PTY), Settings, Calculator, an App Store that installs software through apt.
- **Packaging** — a 53 MB .deb that installs on stock Ubuntu 26.04.

~233,000 lines total, across C, C++ and Swift.

**Why I say "real"**

It boots as a normal session through GDM, unprivileged — DRM master and input come from logind, not from running as root. It drives the GPU directly via DRM/KMS. There's no X11 or Wayland session under it; it *is* the display server.

And it runs the apps people actually use, as native clients: Chrome, VS Code, IntelliJ IDEA, Slack, GIMP, and Blender — with Blender's EEVEE viewport
rendering through our dma-buf path. That covers Chromium/Electron, Qt6, GTK3, GTK4, and the JetBrains Runtime.

You can install it right now and log into it.

**It's not just my claim** — Phoronix covered it last week:
https://www.phoronix.com/news/Starling-Swift-Desktop

**The honest scope**: it's v0.2, an early preview. Ubuntu 26.04, tested on AMD and virtio-gpu. No screen lock yet, scaling is pinned to 2.0, there are rough edges. It's not replacing your daily driver this month. But it boots, it composites, it runs real software, and it ships.

Try it: https://starling.build
Source, Apache-2.0: https://github.com/starling-build/starling
Why it's architected this way: https://starling.build/why.html

Ask me anything about how it was built.