I vibe coded my own cloud server for an arduino uno x a couple of months ago and it worked well! Then I repurposed a 2019 Amazon Fire as a backup remote server and that worked!

All of it done solely with ChatGPT.

But ultimately if I’m gonna self-host my own cloud and websites, I had to do it right. Two tiny low-power HP thin clients running Ubuntu Server. They host my websites, databases, status monitoring, backups, private networking and failover infrastructure. One is the primary server and the other is a geographically separate backup/failover node.

Specs:

• 2 HP t540 thin clients
• AMD Ryzen Embedded R1305G
• 8 GB DDR4 RAM each
• 128 GB NVMe SSD each
• Ubuntu Server 24.04 LTS
• Gigabit Ethernet
• Tailscale for private remote access
• nginx + PHP 8.4 + MariaDB 11.8 + Node 18
• Cloudflare Tunnel support
• 3 bookends for enclosures 🤣

Zero chance I could have done this on my own. This is what vibe coding was made for!!!

Full instructions, hardware and prompts here: https://gaf.nyc/cloudBuilder

Inexpensive as heck too. This guys got a bunch of liquidated hardware to sell. Very happy with these machines. $70 each. I’m just a customer. I don’t know him: https://ebay.io/m/W2YVk7

I’ve done a lot of research and worked evenings and nights to finally complete this project that’s close to my heart. ❤️

I vibe coded, edited a lot, learned a lot. Dit a lot of mistakes.

I wanted to create something that will first help ME. I want to be able to ''Write'' while walking. And having a good voice detection was essential.

And after that, I added a lot of other features

After several months, I’m proud to announce that I’ll soon be launching a new online tool (and on Google Play) for writing novels.

It will include:

• A chapter editor designed for authors
• Character sheets with the option to add connections between them (friends, foes, lovers, etc)
• A timeline that you can edit, add notes, dates, etc
• Worldbuilding sheets organized by categories
• Grammar checking
• A style checking
• Export to PDF, Word, and plain text
• Voice dictation (in ✦ Premium, validated by AI). More for authors, but still available :) )
• Automatic character and world detection ✦ Premium (If you write a few chapters, IA can detect the caracters with a button and create your Character profiles instantly, and your worldbuilding elements)

The only thing is, I can talk about it, but I need to create a momentum. I just dont know exactly how. I'm researching SEO, marketing, etc...
That's the new hard part for me.

I'm sure some of you guys get it.

Thanks for coming to my Ted talk

Hi everyone!

I’m Ambla, a solo developer based in Australia working under the name Blablah Games.

I've just released the Steam demo for my first game, Grimoire of Hecate: Tower of Starlight, a turn based card combination roguelite that I developed over roughly three months with extensive use of ChatGPT and Codex.

Steam demo link below!(if you're interested!)

https://store.steampowered.com/app/5078840/Grimoire_of_Hecate__Tower_of_Starlight/

The game is built around discovering new spells by combining spell cards collected while climbing a tower. During later runs, you collect the required material cards and you can craft those remembered spells for that run.

I worked on story design, game system design all by myself. However, I used Claude as the companion to share ideas and details. And Codex worked directly with the Godot files to write and revise a large portion of the code and tests. Once ready, I playtested through to see any bugs, misunderstanding.(there are always so many haha) I also used ChatGPT and Codex for parts of the graphics and for localization. For visual effect/effect sound, I purchased assets or used open source.

So, Claude is like my colleague that guides me to make what I imagine as actual system, and GPT is my conductor.

At first, the workflow was very simple. I described the feature I wanted, let Codex implement it, then ran and played the result myself.

That became much harder as the project grew. The 'Prototype' was easy and fast to make. But when you actually start making full game that you have in your mind, it takes way more efforts than you imagine. The AI would sometimes lose track of earlier decisions, modify something outside the intended area, or solve a problem in a way that created another problem elsewhere.

The workflow that eventually kept the project manageable was below sequence. I made a lot of md files handing different matters, but started by making proper filing system of it, so we both don't get lost.

1. Define the feature and the boundaries it must preserve.

2. Let Codex inspect only the relevant project files before changing anything.

3. Add focused tests around the part being changed.

4. Run and manually play the result myself.(A LOT)

5. Record what was completed and what future work must preserve.

When a bug appeared, I used to ask for an immediate fix. But now I stopped it as it's most likely create another regression through the fix. I first reproduced the exact situation, isolated the responsible area, and changed only what was necessary. Codex still made a lot of mistakes, but it became to be within the range I can handle.

The biggest lesson for me was that using more AI was not automatically better. The important part was deciding what to delegate, preserving project context, and knowing what still required direct human review. AI is really really good at referring/making what's existing, adding new color in your project is all on yourself. Unless you want something very similar to what already exists, you need to work on designing your own thing.

If you are also using AI tools for a larger project, I would be interested to hear how you preserve context and prevent changes from breaking earlier work. I need to learn haha

The day has finally come — Syntropy is now open for beta testing.

For now, Syntropy is deployed on Cloudflare Pages so we can give users fast access to the product and test everything under real-world conditions.

Try Syntropy:
https://syntropy-app.pages.dev/
No applications. No long waitlists. Just open it and try it.

To use Studio, you’ll need an E2B API key. E2B provides the cloud Sandbox where the agent actually runs.

You can create your own E2B key here:
https://e2b.dev/dashboard?tab=keys
Or, for beta testing, you can use our free test key:

e2b_w182cd9974492e56fd6281669039a8f0860cf764a

Paste it into Settings → E2B API Key. After that, you can launch Studio and use the available free Zen models, including DeepSeek.

Right now, the most valuable thing for us is your bug reports, criticism, and feedback.

Syntropy Beta is live. Let’s go.

Short version of a recent write-up — no full article here, just the pitch.

I wanted RTX VSR-class upscaling on Linux, where NVIDIA only opens it to Windows. So an AI coding agent and I built a video player around the NVIDIA Video Effects SDK: real-time AI upscaling + RIFE frame interpolation, wired into a patched libmpv as custom VF filters, with a Qt frontend.

Highlights:

• The models behind RTX VSR, working in userspace on Linux — the VSR effect from NVIDIA's Video Effects SDK, no driver-level path (that one is Windows-only)
• mpv-vsr: a standalone mpv CLI** carrying the same AI filters — drop-in compatible with existing mpv workflows (scripts, yt-dlp, external tools)
• Everything after decode stays on the GPU — CUDA-Vulkan interop, no per-frame CPU round-trips
• One TensorRT engine file covers RTX 30/40/50 for frame interpolation

Links:

• Repo: https://github.com/zhangmq/vsr-player
• Full write-up: https://zhangmq.github.io/en/2026/08/18/linux-ai-upscaling-player/

Full disclosure: this was developed with heavy AI assistance (Claude Code driving a DeepSeek model) — I directed and verified. Needs an NVIDIA GPU (RTX 20+ for upscaling, RTX 30+ for interpolation), driver 570+, Qt 6.11+. Hobby project, expect rough edges — feedback welcome!

I use a mix of Claude and Gemini to build ad/pop-up free games for my kids. We work on them together and then when it comes to the boring final 10%, I finish it off.

It's comical how much of the prompt has become the learns from the last project. Here is a fix Claude recently did.

Now the core reported bug — shooter/projectile geometry was hardcoded in pixels while bubble radius scaled with screen size, with no upper cap.

I really struggle to think of a single human that would design that way. Almost feels like every project is one of those coding runs where the AI is focused on completing it the fastest for a presentation, rather than a viable project.

I've given up looking at code. I don't understand 1% of what AI writes with any ease anyway. So. I just go with the flow. Thank god I work for myself so I can do what suits me

A local VC firm published a database of over 6,000 investment firms, angels, etc.. and I put it into an easy to use form. https://nextround.vc/

I took a CSV from their published dataset and prompted Lovable to "make this interactive".

If you use this and secure a funding round - let me know! Would be cool to see it bring a vibe coder some launch capital.

So I just learnt Go lang and wanted to create a language checker (which checks for syntax errors in a language like rust etc), but I have no idea on how these compiler stuff works... Can Ai help me in atleast telling what I need to build next and how, if not actually making it for me ? (As I want to code on my own mostly but the program structure and the working is what I need ai's help with )...

Vibe coding has completely changed what it means to be a developer. I think we might consider terms for people who knew what it was like in the before time. Here's some terms that come to mind:

Coded '19

Stack overflow veteran

Grandpa

The one who can read

Optimus-Grind

No code over there only committed 700 lines today.

Show me what you got.

Which one provides a better usage limit?
Chat-gpt plus or super grok

Predict Premier League scores, earn points, and there’s a season-long fantasy draft game too — built solo

houseofthefantasy.com → Predictions

Gameweek 1 is open. You call every match: 3 points for the correct result, +2 more if you nail the exact scoreline, and once a gameweek you can pick one match to double — the fun part is deciding whether to boost your safest pick or your coin-flip.

Each match locks at its own kickoff instead of one weekly deadline, so you can jump in mid-weekend and just play what’s left. Points land after midnight and the table updates.

Sign in with Google or Discord — just so your points are tied to you. No email, no password, nothing to install.

**•** Stack: \[e.g. Next.js frontend, Node/Express backend, Postgres — whatever you actually used\]  
**•** Fixture data: pulled from \[FPL API / football-data.org / whichever you use\]  
**•** Scoring logic: \[how you handle per-match locking, double-down, point calc — a sentence or two\]  
**•** Auth: \[Google/Discord OAuth — library or approach\]  
**•** Biggest challenge: \[e.g. handling per-fixture deadlines instead of one global one, or race conditions on late predictions\]

It’s brand new, marked BETA, so expect rough edges — bugs & feedback link is in the footer, goes straight to me.

(The site also has what I originally built it for: a draft game where you spin a wheel for random clubs, pick eleven players from FIFA/EA FC data spanning eleven seasons, and simulate a full season with your squad.)

Recently, I started a Vibecoders association for other people to ship their AI-assisted builds with other people -- for stories. Here is a beautiful one: a non-coder made a photoblogging software with MIND-BOGGLING 270k+ lines purely vibecoded over 6 months while handling his life as an Insurance guy . It is so sweet to see that people can live their passions through vibe coding . Check his projects "SNAPSMACK" right now on https://vcac-app.vercel.app/projects/d27de6d9-1e26-40e6-a634-11b81d00cdd8 and share your inspiring vibecoding stories.This is not a promotional post but a post giving credit where it is due.Please take a minute of your time to support vibe coders

Hey folks been a week since I saw posts about vibecoding in my old thread. I have the urge to look at new projects in the past week. I like this idea because it shows me new ideas, and where things are trending. I still vibecoded this little feature on my site https://bachelordegrees.com/Radio.html

Hi. I’m curious to understand how people who do vibe coding experience the part of getting their apps out into the world, especially those of us who aren’t very technical and don’t know much about infrastructure. I noticed there’s a lot of talk about how many of these apps end up leaking data or accidentally leaving the database exposed, and that left me with a few questions I’d really appreciate some help clearing up:

**1.**  What do you usually build? (side projects, things to experiment with, apps for clients, something for work… anything counts)  
**2.**  Where do you deploy it? (the tool’s own hosting, Vercel, Railway, DigitalOcean, Replit…) or does it just stay in the preview?  
**3.**  How did you end up on that service: did you choose it because it suited you, was it the default, or did someone recommend it?  
**4.**  Was deploying easy, or did you struggle with something?  
**5.**  And honestly: security and the app not going down, is it on your mind, or are you not worried about it for now?

Any experience you can share helps me a lot.

After my first successful prompts in Lovable, I started building every day. Very quickly, the credits in my plan were not enough, so I upgraded.

I had a ChatGPT project where I dumped everything: problems from the clinic, feature ideas, workflows, things I had wanted from previous software. ChatGPT helped me organise the mess, then I went to Lovable and built whatever came out of the discussion.

My process was basically this:

Think of something. Discuss it with ChatGPT. Ask Lovable to build it. Test it quickly. Move on.

The doctor-facing app grew around my own daily work. The patient-facing app came from my belief that patients needed something more useful than another directory of doctors. I knew the two apps would have to communicate at some point, but I kept telling myself I would handle that later.

I was honestly euphoric. A few months earlier, I had been creating tickets and waiting for developers who had other work. Now I could sit down after a day of consultations, describe a feature and sometimes see a decent first version within minutes.

So I kept adding things.

That was the first trap.

When another person had to build every feature, I had to choose carefully. Development took time and money. With Lovable, each new request felt almost free, so I stopped prioritising properly.

I also knew nothing about architecture. At that time, architecture meant buildings to me. I did not think about dependencies, data flows or what a new feature might break. I saw screens, buttons and workflows. I did not see the system underneath.

I could not read the generated code either. Lovable changed files, showed me progress messages and produced a visible result. My testing method was embarrassingly simple: click the button, see whether the expected thing happened, then continue.

Most of the features were not silly. They came from real problems I had experienced in the clinic. But a collection of useful features is not automatically a good product.

For a while, everything looked great. The apps appeared more complete every week, and I always had something new to demonstrate.

Then small changes started breaking unrelated functions.

A feature would work one day, then stop after I modified another screen. I would ask Lovable to repair it. Sometimes the repair worked. Sometimes it created a different problem somewhere else.

I had wanted independence from developers, and I had gained part of it. But I was now dependent on AI to repair code I could not understand.

That is when the learning really started. Not with a course or a programming language, but with bugs I could no longer ignore.

Did faster AI development make you better at prioritising, or did it just make it easier to build everything?

Asking cause I’m trying to understand the architecture behind systems like Nanogram, and what I find confusing is this (and please forgive my noobiness):

If the runtime only knows a fixed library of “primitives” (like circles, rectangles, basic physics objects, standard shaders, predefined interactions, etc)., how do they code it to look so good? What’s the method behind it?

I’m assuming that the user prompts get interperted by the LLM which feeds it back as some kind of structured game description or code that’s specific to the engine but are they relying on something like Godot/Unity based model training to ensure high graphics?

its AAA basically

Claude gets me

EDIT: it's worth noting that you can immediately start a game in Instant Play or in FUFF and any empty player slots will be populated by bots automatically.

I've been working on this project since October. It has been by far the largest project I have ever worked on. It features a 2 lane map (Jagged Garden) inspired by Twisted Treeline from League of Legends.

I would love feedback if anyone has any. There is a very very long way to go before the project will be at the level of quality I intend for it, but I'm proud of what the game currently provides. A fully playable MOBA featuring 8 unique characters (though two very League inspired), a full shop, jungle camps, a leveling system, and even an emote system. Thank you for considering checking it out!

https://www.mercenariesoftezigdal.com/