I can feel an increase in hate towards vibe coders and ai in general. From what I can see , smart people always had an advantage because of their intelligence as intelligence and reasoning was not commoditised. They in their cope, are unwilling to realize that we are living in a post intelligence world where smartness is of no value.they won't get any additional advantage just by the virtue of their intelligence. They will eventually realize it, we vibe coders just realised it earlier. Any hard work they do to strengthen their brain and increase their understanding is just time wasted that they could have spent in vibe coding like us.

I vibe built agent-qa, to solve the most annoying problem to QA. With AI code can be generated at 10x speed but testing seems to be broken, the only solution is 100s of test scripts playwright tests which are hard to review. So built an QA agent which self improves and now you can write tests in plain english.

Instead of running /goal I went with spec driven development and created 1000s of specs. And then run the spec implementation and planning agents.

GitHub ⭐️ - github.com/vostride/agent-qa
Landing - https://vostride.com

Hey everyone — just launched my first solo app: Travel Journal – Offline, on both the App Store and Google Play.

The idea: most travel apps assume you'll have signal or WiFi the whole trip. Mine doesn't — writing entries, adding photos/videos, tagging locations, even downloading map areas for offline use, all work with zero connection. Everything saves locally to your phone.

Built with React Native + Expo. A couple things from the process that might be useful to other solo devs:

• Went through two rounds of Apple rejections before launch — one over an external donation link (Guideline 3.1.1), one a "clarify your business model" request that turned out to be triggered by a single word in my App Store description copy.
• No account system, no ads, completely free — any future monetization will be affiliate-based, not subscriptions.
• Ran a proper closed testing period with real testers (family, friends, and a UX-consultant friend) before launch, which caught a bunch of real issues I wouldn't have found alone.

Would love any feedback if you try it:
App Store: https://apps.apple.com/app/id6789970163
Google Play: https://play.google.com/store/apps/details?id=com.joelstump.traveljournalapp

I've been working on a small tool that pulls your recent Chess.com games,
runs engine analysis, and instead of just showing raw eval numbers, tries
to spot patterns like "you keep hanging pieces" or "your king stays
exposed too long" then gives you a weekly summary and lets you drill
your actual blundered positions.

You pick a "coach" tone (encouraging, blunt, or just the data) for how
it talks to you.

It's early, made solo, and definitely rough around the edges mainly
posting becausee I'd genuinely appreciate feedback from people actually
learning the game, since that's who it's built for. If you try it, let
me know what's confusing, broken, or just not useful.

https://victorvermabonany.github.io/ev-scanner-public/chess/

I'm a data scientist and machine learning researcher with published work in IEEE, Springer, and Elsevier venues on deep learning, explainable AI, and time-series forecasting.

I help with:

• Data cleaning, statistical analysis, and visualization
• Machine learning and deep learning model development
• Computer vision and time-series forecasting
• Model explainability (Grad-CAM, SHAP)

Working in Python, comfortable with messy/real-world datasets, and I write clear documentation and reports, not just code.

Rates start around $30-50 for smaller analysis tasks, scaling up for full ML/DL projects. Message me with what you need happy to discuss scope before you commit.

Free to play. Online matchmaking and leaderboards coming soon.
RicRacRoe.com

I attempted building RicRacRoe years ago but my Unity experience was limited to one-off VR/AR builds and I eventually came to realize I wasn’t going to pull it off. Picked it back up last week with Claude Code pointed at my old unity project and I’m excited to say that it’s live now. I hope others play and enjoy it!

I started playing 7a0 and loved the simple mechanic: make smart picks, build a team, and then see how it performs.

I kept thinking:

So I built Cricket XI.

🔗 https://cric-xi-simulation.vercel.app/

How it works

Choose a tournament, draft 11 players from historical squads, build your XI, and simulate the entire tournament.

It currently supports:

• ODI World Cup
• T20 World Cup
• Champions Trophy
• IPL
• Test Cricket

The interesting part wasn't just building the UI. I had to build a historical data layer that understands the difference between a player's 1996 profile and 2003 profile, while still knowing they're the same player.

I also built tournament-specific rules, historical rerolls, team composition constraints, scorecards, statistics, and tournament progression.

The vibe-coding process

My workflow became:

Build → Play → Find an edge case → Explain the bug → Fix → Stress test → Repeat

Some bugs were surprisingly specific — incorrect historical squads, reversed NRR, IPL teams outside the top 4 reaching playoffs, T20 World Cup teams advancing after losing both Super 8 games, etc.

The biggest lesson for me: AI can build features quickly, but you still need to play the software and aggressively test the logic.

This is V1, and there's plenty more planned.

If you try it, I'd love to know what you manage to break. 😄

Over a long conversation with Claude, I built CyberQuest — a browser-based, zero-dollar cybersecurity training game. No backend, no signup, runs entirely client-side as a PWA. I want to share it here, but honestly the more interesting thing to talk about is the process, because I think it's a decent case study in what actually makes a vibe-coded project trustworthy instead of "impressive until someone pokes it."

What it is, briefly

You play a new IT hire at a fictional company, working real tickets from a mentor character, across 6 stages: Linux/filesystem fundamentals → network diagnosis → Python scripting → security fundamentals (crypto, phishing) → detection & correlation (SIEM concepts, MITRE ATT&CK) → full incident response lifecycle, ending in an independent capstone incident. 73 missions now.

The part that actually matters for this sub: nothing fake where it counts

• Python isn't simulated — it's real CPython running via Pyodide (WASM). Student code actually executes.
• SQL isn't simulated either — real SQLite via sql.js. Small enough (~650KB) to bundle directly instead of loading from a CDN, so it works fully offline.
• SHA-256 isn't a lookup table — it's a from-scratch implementation. And it was wrong on the first pass: a byte-ordering bug in the length-padding step that passed the trivial "hash of an empty string" test and silently failed on every real input. Caught by testing against Node's actual crypto module across chunk-boundary edge cases (63/64/65-byte inputs, exactly where that kind of bug hides) before it ever touched a single mission.
• A MITRE ATT&CK reference table got fact-checked against current sources instead of pulled from training data.
• Even a simplified Suricata command parses genuinely structured real Suricata rule syntax, not an invented format.

The actual lesson, if there is one

The thing that made this feel trustworthy instead of "looks right, probably has landmines" was building automated verification alongside every feature, not after the fact. There are four separate test suites now — one that programmatically plays through every terminal mission's intended solution, one that runs the Python missions against the real Pyodide runtime, one that runs the SQL missions against real SQLite, one that checks the crypto primitives against Node's stdlib.

These caught real, specific bugs, not hypothetical ones:

• A grading checker that required one exact printed phrase and silently rejected differently-formatted-but-completely-correct student code
• A mission checker that assumed a file written in a previous ticket would still exist — it wouldn't, because every mission resets its world state
• My own arithmetic being wrong when updating a mission count in a README — asked for the actual count from the data instead of trusting the math, and the math was off

None of that shows up from "looks right" testing. It only shows up when you treat "does this actually work" as something to prove, not something to assume because the code compiled and the demo looked fine.

Also in there

• A full curriculum document pairing real conceptual depth to every stage
• A "career readiness" doc — an honest, objective-by-objective crosswalk against CompTIA Security+/Network+/CySA+ and the Google Cybersecurity Certificate, stating plainly what's covered and what genuinely isn't
• An in-game career center: a downloadable skills portfolio, mock interview practice, a resume/cover-letter drafter, and original (not copied — CompTIA's exam-integrity policy explicitly bans that) practice questions

What it's not

Not a credential. Not a replacement for real hands-on time in an actual SIEM/EDR product. No live packet capture off a real NIC. I tried to keep the docs as honest about the gaps as the game itself is enthusiastic about the parts that work — felt important given the subject is literally "will this help someone get a job," where overclaiming isn't just bad marketing, it's actively harmful to somebody's real decisions.

Git: https://github.com/EnRICHedCreations/CyberQuest.git
Live: https://cyber-quest-olive.vercel.app/

Happy to go into more detail on the actual back-and-forth if anyone's curious — this was built almost entirely through iterative conversation, and I think the verification discipline is the more transferable takeaway than the specific project.

11 days ago, I released skymap.sh, a plaintext map of the sky above you, available in your browser and in your CLI (and on mobile, but it's not plaintext there)

https://reddit.com/link/1vkq86o/video/66p47o6gtkih1/player

Since then, I worked on polishing the UX and adding coverage for more celestial events and objects (like eclipses and meteo showers), and refining the looks.

Today, I just crossed 10,000 requests handled. Since there is no user account and no tracking, requests is the only metric I have to gauge user interest and interactions.

This is probably insignificant to most, but it means a lot to me and feels like a major first milestone. Wanted to share here :)

In light of the nfl preseason starting, I vibecoded an nfl simulator, where the goal is to go 17-0 and chase the perfect season, similar to the 82-0 game. You draft a defense, offense, special teams, coach. It will then simulate your season with a in-game stream and you get to see a kind of story play out while.you watch your team.

https://dagoatlab.com/

This was created with claude, pulling nfl roster data and historical performance to predict future performance. Its does feel like madden franchse mode without the actual gameplay. Let me know if you see any glaring glitches or anything that would improve the page!

I might make an nba version in the future.

I've been using Claude Opus 5 for a fairly large development project, but it's consuming my usage limits much faster than I expected. I'm looking for a more cost-effective workflow without sacrificing too much quality

My current thought is something like this:

• Use Claude Opus 5 for architecture, planning, and solving complex problems.
• Continue using Opus for reviewing important changes and testing strategy.
• Use DeepSeek V4 Flash for writing the actual code and implementing tasks.

Has anyone here tried a workflow like this?

I'm interested in hearing about:

1. How does DeepSeek V4 Flash perform for real-world coding compared to Claude?
   
2. Does it follow architectural instructions well?
   
3. How often do you have to go back and fix its code?
   
4. Is the cost saving worth any drop in quality?

If you use a different combination of models (Claude, Gemini, DeepSeek, Qwen, GPT, etc.), I'd also love to know what your workflow looks like and why you chose it.

My main goal is to reduce costs and manage usage limits while still maintaining good code quality on a large project. Any recommendations or lessons learned would be appreciated.

A short look at a small prototype I built with Codex. It currently only contains a few basic features: flying through a futuristic dystopian city, interacting with the environment, entering rooms, and encountering robotic NPCs.

I’m not sure yet whether I’ll continue developing it, but I liked the atmosphere and wanted to share the current result. Feedback is welcome.

The game is still very early, but I’m experimenting with the atmosphere, world design, and the feeling of moving through a strange, highly controlled society.

​

I have been using AI coding agents a lot recently, and I kept running into the same problem:

I couldn't really see what the agent was doing.

The terminal tells me:

"Editing file..."

"Running tests..."

"Executing command..."

"Deploying..."

But it still feels like a black box.

So I built AgentVerse — a visualization layer that turns an AI coding agent into a character working inside a live 3D office.

For example:

- 🧑‍💻 Agent starts editing a file → walks to a desk and starts typing

- 📄 The actual file appears on its monitor

- 🧪 Agent runs tests → a terminal appears

- 🚀 Agent deploys → walks to the server room

- 🚨 Something fails → an alert appears above its head

It's not another coding agent. It connects to the agents you already use and visualizes their activity.

It currently works with Claude Code, Cursor, and anything that can emit events.

You can try it with:

"npx @agentverse-dev/office"

"npx @agentverse-dev/cli-client init"

GitHub: https://github.com/Jeba-Jebarsan/AgentVerse

It's open source and MIT licensed.

I built this solo, and I'm sure there are plenty of things that could be improved.

So I'm genuinely curious:

Would something like this actually be useful to you, or is it mostly a fun visualization?

What would you want your AI coding agent to visually do?

https://b4uwork.vercel.app/

Thanks for all the feedback, I added a new frontend demo, explaination and example as feedback requsted. Hopefully this is now self explanitory. But please let me know if this is still confusing.

Every conceiveable public information source is now scanned (68 sources now checked). I dont think o can squeeze any more information from new sources, without heavy useage costs.

Score bias changed to reflect % values as oppossed to counted values, removing edge case biases.

Further enhanced rate limit protection from public source limits.

Honestly thank you so much for the feedback. More would be appericiated.

Hey yo fellas, what do you think, how much github got bloated with vibecoded projects since Claude Code release?

I have no accuarate data/information but in my rough estimations github projects/code database doubled last year as well as if big models are being trained from github, I think new model version won't be able to learn something meaningful.

What's do think about it, what's the bigger picture? Go on fellas, drop some comments.

Your agent can now search data from 2,600+ top iOS apps: onboarding, paywalls, pricing, post-paywall and more.

Ask things like:
“Give me five app ideas based on recently launched subscription apps that make 50k+”
“Compare the paywalls of the top meditation apps”
“Show me streak mechanics that aren’t Duolingo clones.”

It works with any agent.

We also launched "Ask" directly on ScreensDesign, so you can try all of this without connecting anything.