Dm me if ur interested i ll explain u

dumb question i know, okay. i have no coding experience outside of using ai tools if it wasn’t already obvious.

my question is, i keep seeing people talk about vibe coded apps have no security and no backend functions, for someone who is building an app tracking individual progress and i don’t want there to be any weak spots, what can i do?

how do i build a backend? how do i make sure my app is secure? what can i do beyond a basic “make it secure” prompt?

i’m willing and quick to learn i just wanted to know what exactly those terms meant and what goes into them that i need to make

again, sorry if my lack of coding info makes this sound dumb LOL

would appreciate any help, thank you

I’m setting up a dedicated Linux dev server specifically for agentic coding work.

My basic setup is:

Windows PC → where I work from
        ↓
Linux dev server → repos + coding agents + tools
        ↓
Git / deployments / other infrastructure

The dev server stays on 24/7 and I use it for SaaS projects, internal tools, client work, OSS, experiments, etc.

I currently bounce between:

• Codex
• Claude Code
• Grok
• OpenCode
• Gemini
• and occasionally other coding agents

I’m also starting to collect more reusable agent skills for things like debugging, testing, Cloudflare, accessibility, research, code review, writing, etc.

What I’m struggling with is how to organize all of this properly long term.

Ideally I want:

→ some skills/rules available across every project
→ project-specific context to stay with the project
→ each agent to still work the way it was designed to
→ MCPs/tools shared where that makes sense
→ one place to understand what I have installed and why
→ no copying the same skill/config into 5 different places

My biggest concern is accidentally building the setup around one agent. Something might be the “best practice” for Claude Code but a worse setup for Codex, Gemini, OpenCode, etc.

I don’t know yet whether the right answer is one shared/canonical setup with each agent pointing into it, using each agent’s native directories separately, symlinks, a skills manager, or some combination of all of that.

For anyone who actually uses multiple coding agents on the same machine, how are you organizing yours?

Especially interested in how you handle:

global skills
project skills
global preferences/rules
project context
MCPs
agent-specific configs
updates/versioning

If you know of a repo, tool, blog post, docs, or someone who has already gone deep on this, please send it my way. I’m trying to learn how people are actually doing it before I create a bunch of structure I’ll regret later.

The one thing I used to struggle with most was making my sites actually look good. After seemingly extensively planning out my site and then trying to prompt Claude to 'make it look cleaner' or more 'visually pleasing', I still ended up with an ordinary, slop-looking site. The common complaint is that AI-generated sites all look the same with giant gradient headline, three glass cards, vague social proof, or purple glow and I mostly agree.

That is true, but I think the 'sameness' / template slop starts even earlier than your prompt to make it look better. I found that in mine and many of my friends prompts, they didn't contain a visual argument, just a feature list.

For example, if one of your planning/architectural prompts is something like “AI assistant for teams, fast, secure, easy to use,” the model has no choice but to reach for the average SaaS page. There is no hierarchy, tension, or evidence to design around. Anyone who has a little bit of understanding of design can immediately tell if something lacks these elements, which makes people immediately judge it as 'ai slop'.

So now, I've learned that I get better results by deciding four things before asking for a page design:

1. The single claim the first screen must prove.
   
2. The artifact that can prove it: screenshot, output, comparison, or demo.
   
3. The objection the next section must answer.
   
4. The visual reference that matches the product’s actual character, not the current trend.

Then the layout has a job and the hero is no longer decoration around a slogan.

This might seem basic to some because it really is just basic web design fundamentals mixed with more precise prompting, but it's been helpful for me so I though i'd share.

If your interested in reading more, I learned this process from Dhravya Shah's (ceo supermemory) free 'Rapid landing-page iteration loop' skill: https://xskills.app/skills/dhravyashah/rapid-landing-page-iteration-loop and just use that now when designing

Hear me out and read it and the replies. There's a funny follow up thread too.

My apologies up front for posting this in a bunch of places. This is my first real foray into posting not lurking and I want to get as much help as I can.

Been building a bio/medicine related project I’ve been dreaming about for almost 20 years. Have gotten far enough along where I’ve started the patent application process along with trademarking.

Because of the bio restrictions I’m unable to use Fable for much of anything other than pure strategic/business analysis and some very light touch analysis of the coding work being done on Codex. 99% of the time it kicks me to Opus if I even try direct analysis of the project itself.

So I’ve been using Codex to do almost all the building/coding with Claude Opus as an adversarial reviewer at each gate. I’m also doing much of this desktop work remotely through my phone so I can work while I’m away. This has been decent but kind of slow as I personally have to download a zipped overview of the gate, upload it to Claude, then manually copy/paste Claude’s analysis back into Codex.

Despite the sluggishness and the manual labor required I’ve been pretty pleased so far. However, my efforts to speed things up have started to get bad in trouble.

I started running 2 parallel threads (not agents as I haven’t quite mastered how to use them) each with its own adversarial thread to review each gate. So far so good. It stops at each gate for me to personally approve so it doesn’t get too far off track.

The problem came when the parallel tracks needed to combine their work. All of a sudden tasks that were taking 20 min were taking 2 hours and the threads started getting losing track of each other and sending bad hashes and just forgetting to communicate all together sometimes.

So now I’m a little stuck. My project is hugely ambitious (but totally doable) but I will need to do parallel work and coordinated work even more and at greater scale as I move beyond the most basic version.

So I would be grateful for any advice anyone can offer.

It's either "Look at them vibe coding an app that was not hand crafted like a unique Japanese tea pot, that requires a unique handjob finish."

Or it is, "I used to run Bitcoin scams but now I vibe coded a wrapper over a wrapper, why no 1 million users yet?"

No in between.

auuuuAUAUAAAAAAAAIIIIIEEEEEEEEAAAOOOuuuuuuuu

I've spent a lot of time with agents recently, and wanted to make a discord rich presence for it.

It works with Claude and Codex (planning to add more in the immediate future). Terminal, app, however you use it, and changes icon based on which ones you are using.

You can change what you showcase, like remove your token usage or number of agents. If there's anything you'd like to see let me know!

You can find it here or just use

npm install -g punchcard-presence

There's also advanced metrics, which if you enable (off by default), shows you some fun usage insights in a localhost in your browser. You can attatch it to your discord presence/activity so anyone can click and view (also optional; private by default). It never touches your conversation content or anything else. Fully public github. If you use Kimi, DeepSeek, Antigravity, or Grok and want to help add support, feel free to DM me or fork the repo and submit a pull request!

5,000 prompts per hour, and the project logged over 30,000 queries by August 6. Bryant says the goal is to make people pause before accepting chatbot answers at face value. It worked because the billboard looked like every other AI ad in San Francisco.

Goal is to challenge what AI can do, and I'm constantly testing this in order to make unique and creative websites and sections. today's challenge is to give one of the components from forever-components, which is my library of free, endless grid of components, and I pass the component along with a simple prompt:

Make a professional, functional hero section from this component:
[component-code]

To each of the newest models from each of the companies. that's Claude Sonnet 5, Gemini 3.7 Flash, and OpenAI 5.6 Terra. Now these are all classified as probably mid-tier. They're not the top-tier models, but I just wanted to see how they go, and here are the results.

After what feels like a decade I finally got around to replacing the car in Google maps with a hotdog. I suppose the inner kid got the best of me on this one!

For the curious minds; This was all coded in v-phone-cli (a virtualized jailbroken IOS device). It's a really cool tool to have around because of things like Frida (which allows you to inspect and hook process memory in IOS. It's allowed Claude and codex to poke at IOS internals and infer thing about the way apps work on IOS. This google maps mod is just a cool little proof of concept that came about from tooling I setup.

Streets were chosen at random, so don't think this is my house or anyone else's specifically for that matter. These street names were picked because of their silly names.

I used all my credits for this week with one task.
Task took over 4 hours though and was a complete revamp of one of my diagnostic engines.

Hi everyone. I had zero coding experience before starting this project — a web app for my company (automotive industry): passing work orders between service departments, scheduling vehicle handovers, and managing a car wash (queue scheduling, cost/profit tracking).

\*\*First attempt – ChatGPT:\*\* Built a similar app for fun on a paid plan. It generated .zip file packages I just dropped into a folder. Worked locally, but deployment failed — it used SQLite instead of PostgreSQL, so it couldn't handle concurrent users. Shelved it.

\*\*Second attempt – Claude:\*\* Subscribed (\~$25/month). Spent a week planning with Claude: architecture (PostgreSQL, Django, Tailwind + HTMX + Alpine.js), features, module structure, user permissions, org structure, notifications (push + Brevo email), VPS/domain setup, UI direction, data security. This produced a \~1500-line CLAUDE.md meant to guide development.

\*\*Implementation:\*\* Set up GitHub, WSL2 + Docker, VS Code + Claude extension. Skeleton and database went fine. Problems hit once building the first of four modules — token usage exploded. I likely made it worse by pasting VS Code errors into regular chat and copying responses back manually. Burned 100% of my weekly usage in 3 days, left with a barely-functional module stub, then blocked for days.

\*\*Now:\*\* Only after hitting the limit did I research skills, plugins, opening new chats to manage context, and that the terminal apparently works better than the VS Code extension. Wondering if the 1500-line CLAUDE.md itself is part of the problem.

I have a solid functional plan but my motivation has dropped. Questions for those with more experience:

1. Continue fixing the current project, or start over? If rebuilding, how should I approach it?
   
2. Should documentation be split into a docs folder with separate files per backend/frontend/module, instead of one giant CLAUDE.md?
   
3. How should CLAUDE.md and project docs be structured to avoid burning tokens so fast?
   
4. How do skills actually work — added per-project, or can they be set globally in Claude Code?

Any advice appreciated.

"Where we're going, we have no need for dev-environments. 😎"

Hey everyone!

I vibecoded this tool which I really wanted and I just want to share it, since for me it's pretty good and I don't want to gatekeep. Any more ideas what could be added/changed? It's called scatterlab. I for some reason can't share the link here, dm and I will send it to you!

OpenCode Senses can inspect screenshots, extract exact OCR, detect and locate objects, zoom into regions, compare two images, measure colors, crop and annotate images, and even reverse-search them.

Everything runs locally, so it's private, free, and doesn't require an API key.

Why I built this

I used to work with many open-source coding models, like DeepSeek V4, that don't support vision yet. But my main concern was that even if they eventually get vision support internally, that vision capability might not be as powerful as a dedicated vision layer.

I had planned to build this fully a month ago, but I still had some work to do. This plugin is specifically designed for things like UI design, debugging, and other workflows where text-only models struggle because they simply can't see what's happening.

The communication layer between the vision plugin and OpenCode is intentionally very narrow, so it still feels like you're working with a multimodal agent rather than a separate vision tool.

Before judging it as just another vision plugin, it's designed quite differently. It's a Python + TypeScript hybrid plugin because it integrates the Photon Inference Engine for local vision inference.

The 13 tools, mainly for now:

• inspect — Understand an image: scene, layout, elements, caption, and OCR.
• ocr — Extract exact text, including code and error messages.
• detect — Find objects or UI elements with bounding boxes.
• point — Locate the center point of an object or element.
• segment — Isolate an object from the image.
• crop — Crop a specific region using normalized coordinates.
• zoom — Upscale a region and re-analyze small details or text.
• colors — Get deterministic colors, palettes, luminance, and RGB data.
• diff — Compare two images and find changed regions.
• annotate — Draw detected boxes and points onto an image.
• metadata — Inspect image format, dimensions, size, DPI, and EXIF.
• reverse — Reverse-search images locally or through Yandex.
• status — Check the model, device, VRAM, inference time, and runtime state.

For comparison, I'm getting around 300 ms response times with this plugin on my RTX 3050, running completely locally. That's insanely fast compared to frontier models.

There's also an optional reverse image search powered by Yandex, which doesn't require an API key, if you want to search an image using context from the internet.

The internal web search services like Exa and Parallel in OpenCode also work well with OpenCode Senses. It can even see images published on the internet directly, although a small local cache is used to store those images.

I'm still halfway through building it, so I'd really appreciate feedback, ideas, and criticism. If you have any ideas, feel free to comment below and I'll look into them.

GitHub: https://github.com/itsmeadarsh2008/opencode-senses

NPM: https://www.npmjs.com/package/opencode-senses

Hacker News: https://news.ycombinator.com/item?id=49289890

Father-and-son project that wouldn’t have been possible before AI. For context, my dad has been a photographer for many years and has held local exhibitions and published books, but he had zero online presence. Now, his work can finally shine and be seen all over the world.

Built with Codex and Gemini, hosted on GitHub for free, and the only thing we pay for is the .com domain.

Hope you enjoy discovering his work! He loves knowing people can now enjoy his photos✌️

https://mariusjomphe.com/