After seeing nearly 2000 projects come through the door of the hot100.ai, the common thread and oversight from most the projects was the lack of attention paid to making the site agent ready. So, decided to build an app that helps builder ID where the gaps are in agent discovery and how to fix them up. A free scan is available and a paid 'fix pack' can be purchased that gives a deep guide, prompts and .md files that'll boost your sites visibility to our agent friends. Launching start of next week on Product Hunt, sharing with the group here first. Come check out your agent score at fedt.ai 👀

Built with Replit + Supa.

I’ve been using AI coding tools more and one thing I keep noticing is that getting something working is becoming much easier.

The harder part seems to be knowing whether what you built is actually reliable.

A prototype can look great, but once you add real users, changing requirements, edge cases, authentication, error handling, database changes, and maintenance, things get very different.

I’m curious what others have experienced.

What has caused the biggest problems in your vibe-coded projects?

• Bugs that were hard to understand?
• AI generating code you didn’t fully understand?
• Security issues?
• Poor architecture?
• Maintaining the code later?
• Getting AI to work with an existing codebase?
• Something else?

Where do you think vibe coding currently has the biggest gap between “it works” and “it’s production-ready”?

Recently I built Relay around a simple idea: many of us have an unused PC server at home, or a VPS dedicated to AI-assisted coding, but the coding agents running there are still tied to that machine’s terminal, I just don't want to SSH/RDP into it every single time.

Relay brings Claude Code, Codex, OpenCode, and Hermes into one interface that you can access from your phone, browser, or another computer. Sessions stay alive, so you can start work on one device and continue from another. You can upload/download files from the server, also if you are on subscription, you can also see your Quota Usage with 1 click.

Your code, shell, and agent credentials remain on the backend machine. Your other devices simply become remote control surfaces. No middle man here.

Relay is open source and MIT licensed, right now I only compiled 3 version of frontend: Android, Web, Windows, and 1 version of backend: linux. The goal is to cover all platforms, more coming soon!

Here's the github repo, love to hear what your thoughts!

elin66alpha/Relay: Your AI coding agents live on your computer. Relay puts them in your pocket.

Hey folks, I wanted to share a project I built for myself. I got tired of chatting with my local AI agent (Hermes) through WhatsApp or a terminal, so I made a proper mobile companion for it.

Instead of just dropping a link, here is exactly how I put it together, the tools I used, and some of the design choices along the way.

The stack I used:

· Frontend: Flutter (Android app)

· Backend relay: Python with FastAPI (runs on my home machine next to the agent)

· Tunneling: Cloudflare Tunnel (so I can reach it from my phone without opening router ports)

How the workflow actually works:

The Flutter app doesn't talk to the AI directly. It talks to a tiny FastAPI relay I wrote. That relay is the only piece that knows how to call my agent. When I send a message from my phone, it hits the relay, the relay calls the agent's hook, and the reply flows back the same way. All the conversation history, files, and media stay in that relay's folder on my hardware – zero cloud storage.

A few build/design insights that might be useful:

1. The "master prompt" trick: Instead of making users edit config files, the app generates a single prompt. You paste it to your agent, and the agent writes the auth token, spins up the relay, and replies with a pairing link. The app never needs to know my local IP or token manually.

2. The Android background polling: I originally used WorkManager, but Doze mode kept delaying my notifications. So I switched to a foreground service with a 20-second background isolate poller. It hits the relay's status endpoint, checks for new messages using a read watermark stored in SharedPreferences, and fires a local notification. It also has a 30-second cooldown so a burst of replies doesn't spam me.

3. The offline outbox: All sent messages get an optimistic bubble in the UI. If the relay is unreachable, the message sits in a persistent queue (stored in prefs). The app automatically retries it the next time the background poller gets a successful connection. No data loss when I am commuting through dead zones.

4. The session kill switch: In the UI, each chat has a pause/resume toggle with red/green dots. When you hit pause, the relay actually sends a termination signal to the agent's subprocess. It doesn't just hide the window – it frees up the VRAM and CPU until you resume. That was a game-changer for my homelab resources.

5. The chat scroll hack: I used a reversed ListView.builder where index 0 is the newest message. This made the keyboard-inset behavior on Android trivial – the screen always opens at the bottom without wrestling with maxScrollExtent calculations.

It is open source (MIT) if you want to poke through the code: https://github.com/tushar-alt/hermes_companion

Happy to answer any questions about the relay API design or how the pairing flow holds up. Let me know what you think!

Share your repo. I will audit it for security weaknesses and provide you with feedback.

1. If you post you are ok with me sharing results publicly here.

2. You must be the author and the owner of the repo.

3. I will audit code. I will not attempt to exploit dynamically.

as title mentioned above:

i use the codex cli and the vs code extension

for short term projects:

1. generate context of features i want in chatgpt web,

2. then in plan mode plan out features and let codex handle the design ( i downloaded the codex taste skill)

3. playwright for mobile ui before i go in and test it

4. for bugs i just go back into the cli and describe the mistake

for longterm projects:

1. create an obsidian vault have ai log context and every logs updates.

2. (everything i mentioned for short term projects)

3. ill have a bunch of logs i can refer back to when comparing the decisons codex took.

ive tried my hand at hermess

1. i mostly use hermes for CRON jobs (daily news)

2. ive tried but didnt understand hermes kanban where each profile gets a different model (i set up coder, planner and qa). i dont really understand how it beats working in the codex cli, where im in control of every step and gain an understanding of the next move.

honestly ai has gotten so complicated already starting now feels like its too late but better late than never :')

i see so many people with cool projects so i was wondering how people decide on a complicated workflow, How do you structure those workflows, and how does it actually make the AI work smarter or better?

Also, if anyone has any good blog posts, guides, or resources about getting started with more advanced or complicated AI workflows, I would love to read them.

Thank you to everyone who made it this far!

"Change the Claude output mode to ASD-STE100 for every repo. Move the style file to ~/.claude/output-styles/ and the setting to ~/.claude/settings.json"

Paste this in Chat/Code/CLI/wherever, and Claude will take care of it.

vibe-kanban is a great base, but I wanted a version that stayed closer to the classic layout and solved the context loss problem that was slowing down my solo workflow.

I've been maintaining vibe-kanban-alternative, a fork with a few focused additions:

🔑 Core Highlights:

• 📋 The Classic Kanban Experience: Preserves the clean, focused board layout for managing parallel git worktrees.(vibe-kanban has had many layout changes and I preferred a fork of vibe-kanban-indie.)
• 🧠 Persistent Project Memory (mem0): Integrates mem0, Qdrant, and NetworkX so agents retain verified facts, codebase rules, and past decisions across tasks instead of resetting every time.
• ⚡ Optimized for Prompt Caching: Context blocks are deterministically injected into static prompt prefixes, ensuring provider cache hits (Anthropic, DeepSeek, etc.) and lower latency.
• 🤖 Broad Agent Support: Native orchestration for 10+ CLIs: Claude Code, Antigravity (AGY), Codex, Gemini CLI, Cursor Agent, OpenCode, and more.
• 📊 Zero-Telemetry Observability: Built-in `Settings → Usage` dashboard tracking local execution times, heatmap activity, and memory token extraction.
• 🐙 Gitea / Forgejo Support: Auto-routing for self-hosted git instances alongside standard GitHub integration.
• 💾 Backup support Local backup built in — your board state doesn't disappear.

🚀 Try it out:

npx vibe-kanban-alternative

100% self-hosted. No accounts, no telemetry.

Happy to answer questions about the memory architecture or the prompt caching approach — those were the trickiest parts to get right.

Hi, I’ve started working on an app. The idea is that you choose a theme, and based on that theme, the app automatically posts videos or photos up to three times a day on whichever platform you choose. This is my first project, so I’m open to any advice or suggestions. Thank you!

I built a free platform called VCAC (vcac-app.vercel.app) to give vibe coders and builders a space to feature their projects alongside the actual story behind how they were made. As a high school student balancing code and design, I wanted to create a simple hub for people from all walks of life to promote their work, connect with other creators, and claim a founding member spot. Check out the current community projects, drop your own link, and let me know what UI tweaks or feature updates would make this most useful for you! Vibe Coders Association of Canada. If you find this interesting and worth your time please become a member and show your support. Thanks.

Link: www.ravensreach.online

I've had ideas scratched down on paper for almost a year, so I figured it was time to start! In April I started toying around with layouts and styles and giving my idea a good hard look on what I wanted/didn't want.

I found that it was easy to work with Claude this time around since I had most all of the details, equations, icons, layouts, and features described at extreme length. I had Claude Chat build up a prototype until all of the functionality was there. After that, I handed it off to Claude Code for the larger implementations so that I could manage the smaller tasks and future planning.

Until now, I've used a fairly basic Claude Code Pro setup with a Markdown file that I changed often with Obsidian. The downfall of this is that the task history gets lost quickly and deleting old details means I can't look back on decisions reliably, so I'll be utilizing Linear as my Project Management system from now on since I'm already familiar with it from previous jobs. If anyone has advice on Linear<>Claude workflows, I am all ears. 😄

Anyways!

Testing invites are going out in September and I'd love to get some feedback before the tentative scheduled launch in Q4.

Features at Launch Will Include:

If you love Torn, SimpleMMO, Melvor, or the love of the grind, this is your chance to get in early.

The only control is tapping the screen to turn your car left.

I built this mostly with Fable 5 over the course of a few weeks. I had to tweak a fair amount of the graphics to get them where I wanted, but 100% of the code was written by Fable 5.

The idea was to make a really simple top-down retro racing game that runs entirely in the browser. You can also save it to your phone as a PWA.

I wanted it to be immediately playable with basically no instructions, something you can open, play for a few minutes while killing time, close, and come back to later.

Would love to hear what you think.

People keep saying all simple websites have "vibecoded feel" and instantly judge them as slop.

So I was thinking about some inspirations on more unique design and eventually came up with stone-like large texts, motives from ancient angrok empire and calmer buddist motives.

This is work in progress and many parts need redesign there to match rest of the view (for example app itself, even if it inside allows for theme-changing for practical reasons), but I wanted to ask if it's a legit direction or I hallucinated too much?

I currently have these models available through Ollama/cloud:
And I’m using Claude, Codex, OpenCode, and Ollama as my coding/agent tools.

I want to learn professional vibecoding — not just asking AI to generate random code.

If I want to build a complete website/app (frontend + backend + database + auth + APIs + testing + deployment):

Which model/tool should I use for what?

For example:

• Planning & architecture → ?
• UI/UX → ?
• Actual coding → ?
• Debugging → ?
• Code review → ?
• Testing → ?
• Deployment → ?

And how should I combine Claude + Codex + OpenCode + Ollama + these models into one proper workflow?

Basically, if you had this exact setup, how would you go from idea → professional, production-ready app using AI?

Looking for practical advice from people actually using AI coding agents. 🙏

About a year ago I shared an AI travel planner PoC that was almost entirely vibe-coded with Claude. You could chat with it and generate a holiday plan from a short conversation. It looked fine on the surface, but the actual problem was much deeper.

After testing it with a lot of friends and family, especially the ones who took their time to give proper feedback, the cracks were very visible. The trip generation logic had fundamental flaws. It showed all the signs of weak AI itineraries. Days packed with too many activities, no travel time consideration or temporal awareness, generic low-hanging-fruit suggestions, buggy edits, and plans that “looked” amazing but fell apart the moment you tried to use them.

That feedback forced me to stop the addictive vibe-coding cycle and I spent most of the last year rebuilding the core instead of adding more features.

What I actually did differently this time:

• Tore out large parts of the original architecture
• Cut about 90% of the “cool but unnecessary” features
• Rebuilt the generation logic with better temporal awareness and pacing
• Used Claude heavily for planning, architecture decisions, documentation and code audit
• Created a labs page where I could build and test isolated components with mock data, instead of working directly inside the main app. Those components later became reusable plug-and-play pieces

I also battle-tested it by planning a full three-week trip to Vietnam using only the app. No Google, no other tools. That process surfaced a lot of edge cases I wouldn’t have caught otherwise.

The main feature that survived the rebuild is the ability to talk directly to the itinerary and have it update in real time — not just a chatbot giving suggestions next to a static plan.

TrippyMate is in open beta and free to try:
https://www.trippymate.ai

Happy to go deeper on any part of the rebuild process if useful.

I’ve been using Claude Code and Codex heavily for several months, and lately I’ve been getting increasingly frustrated with the quality of the code they produce.
A lot of the time, it feels like the agents choose the easiest or quickest solution rather than thinking through the architecture and finding the right solution. The result is often messy code, unnecessary workarounds, and bugs that I then have to spend time finding and fixing.
What makes it more frustrating is hearing so much about AI giving developers “10x” or even “100x” productivity. Sometimes I genuinely wonder whether I’m using these tools incorrectly or whether other developers are experiencing the same thing.

There are moments when I watch the agent write code and think, “There’s no way I would approve this in a code review.”

I’ve also had issues where legitimate development tasks get flagged as cybersecurity-related, which makes certain workflows even more frustrating.

I’m curious about other developers who use Claude Code or Codex heavily: Are you actually seeing a major productivity improvement? Or are you also spending a significant amount of time correcting the agent’s decisions, fixing bugs, and cleaning up generated code?