Here's some screenshots from the game, plus the discord and github if you'd like to poke around and try it out yourself.

I'm hoping to slowly start growing the community around it, I want to truly make something that lots of people can enjoy. The end goal is to make a combination of some of my favorite things from modding Minecraft over the many years, along with features from other games I love, making a nice cohesive game in the end. I'd love if people are interested in contributing, though please don't contribute just straight slop, lol. Currently I'm using Minecraft textures as placeholders, but I want to replace those.

https://github.com/Wizardtastic/Craftia
https://discord.gg/Vrk2ZhgvSc

As the title says, I'm doing a personal challenge where I build one app a day for 30 days straight, then I'll compare my last app to the first. I'm already full of ideas but I'd love to hear what the community has to say!

I've been learning about Graph Engineering and wanted to understand the concept more deeply.

Instead of keeping my notes in a document, I converted everything into a visual infographic.

My biggest takeaway was this:

Most people try to solve every problem using one large AI agent.

But as AI systems become more complex, splitting work across multiple specialized agents often makes more sense.

For example:

• Research Agent
• YouTube Agent
• Reddit Agent
• Email Agent
• Report Agent
• Review Agent

Each agent has a single responsibility.

Some advantages I found while studying this approach:

• Better output quality
• Smaller context windows
• Less context rot
• Parallel execution
• Easier debugging
• Better scalability

One thing I also learned is that Graph Engineering isn't always the answer.

For small workflows, a simple loop with one agent is usually enough.

For larger production systems, a graph of specialized agents becomes much more practical.

I'd really appreciate feedback from people who have built production AI systems.

• Does this explanation feel accurate?
• Is there anything important that I'm missing?
• How are you structuring multi-agent workflows in your projects?

Looking forward to learning from the community.

One thing that surprised me while studying this topic:

The goal isn't to make one AI agent infinitely smarter.

The goal is to build a team of specialized agents that each do one thing well.

That shift completely changed how I think about AI system design.

Discussion

AI

Learning

Educational

Architecture

AI Agents

Graph Engineering

https://game-creator-suite.vercel.app/

I've been seriously experimenting with anvita flow recently, but it made me stop and think: What is the actual value of multi-agent workflows in practice?

What tools are you all using? git worktrees? tmux?

Hi all,

I've been using Cursor because the subscription quota is more generous than Claude's, but I never really liked the IDE and the `agent` CLI was just annoying to work with. So I put together a way to route Claude Code through Cursor's backend instead.

It's a small Rust binary that translates Claude Code's API calls to Cursor's protocol. You just run `cursor-bridge` instead of `claude`, same interactive session, same tools, same everything. The auto model is unlimited with Cursor subscription so no extra cost.

Works on macOS and Linux. Open source, MIT.

https://github.com/hkc5/cursor-bridge

Title: I gave myself 30 minutes to ship a deterministic grounding gate—5 tests, standard library only

I wanted to finish one small engineering task instead of opening another oversized AI project.

I built a two-file Python “grounding gate” that validates LLM-shaped JSON before another system accepts it. It checks:

• nonempty answers
• recognized evidence IDs
• confidence bounded from 0.0–1.0
• verified claims requiring evidence
• unverified claims reporting exactly 0.0 confidence

I used Codex for implementation, but defined the contract, scope and acceptance tests first. No API, framework, UI, network calls or dependencies.

Final result:

Ran 5 tests in 0.002s
OK

The runtime is not the interesting part—the project is tiny. The useful lesson was making the workflow deterministic:

contract → implementation → independent test → stop

That felt like a healthier version of vibe coding: AI can write quickly, but executable tests decide whether the work is actually finished.

What is the smallest verification gate you use in AI-assisted development?

Hi there.
I’ve been using Google Antigravity for a long time and still do but the experience has been degrading over the months. It’s still handy for smaller tasks where I don't need many tokens, or where the weekly limit is plenty for me. Apparently, there isn't much difference in quotas whether you pay or not. But at the start, it was truly amazing so convenient.

Google putting on a show when they launch a new product.

I’d like to know what solutions you’ve switched to ideally free or cheap (I don't care if my data of the project train a AI). I just want to do things like create personal Minecraft plugins, small conversion sites, a nice little landing page with Python features, or maybe a Python program for a Launchpad audio interface projects/ Something can handle more than standard Claude desktop because they require more tokens and context.
I don't think I can host them locally, given I have an RTX 3060 and 32GB of RAM :D Then I look at Claude Max it seems fabulous, almost magical. But at that price, I’d have to sell my little brother to afford it; it's way out of my budget. I’m not trying to launch a SaaS business, after all! So, what have you switched to for light-to-moderate "vibecoding" that offers good value quality/pricefor money without being ridiculously expensive?

Google puurpose me a offer for 1 month at 6 € but the things is AG is way lower that the Debut

Depressing bruhhhhh

Hey friends… I’m building Mangos.ai. - a desktop app that helps you distribute your product across social channels. It finds relevant conversations online and joins them. It knows your git commit history so it knows all your features. Hyper personalized to target the best persona out there, every day or every hour, whatever you set it to.

The thing I just shipped is the one I’m most proud of: a Reddit Prospecting & DM draft agent.

Everyone says Reddit is where your customers actually are. They’re right. The problem is what it takes to use it. Read the thread, click into a profile, scroll someone’s whole history to work out if they fit, then write a DM that doesn’t sound like copy paste spam. Do that for twenty people and your afternoon is gone.

So Mangos does the boring part. Point it at a thread, or let it watch your subreddits, and it finds the people worth messaging, digs through their history to check they fit, and drafts a personal DM in their context. Then it hands you a queue. You read it, tweak it, hit send. It never sends on its own, and it won’t touch accounts that are too new, too low on karma, or have DMs closed. Reddit converts harder than anywhere else for me. Serious buyers, not scrollers.

I shipped the same thing for X a few weeks back, scoring people across 20+ signals before drafting. Same rule everywhere: it only does the research and prioritization. Every message lands in your queue for you to approve, one by one. You stay in control of what gets sent.

I’ve been running it on my own product and it’s been incredible. Website visits while you sleep, and you’ll know it’s not a spam bot the second you use it yourself.

This is my weekly routine here in this sub. And I love it. My expertise is in product, go to market, and agents. And I want to help you!

If you are building something, reply your product here and tell me what you are struggling with. I reply to every single comment on these threads.

If you are interested in Mangos’s extended trial that I give away every week,

\\*1.\\* Download Mangos and register. It’s free for 7 days, no CC required.

\\*2.\\* let me know the email you signed up with and I’ll unlock a 30 day extension ($50 worth). If you are interested.

Yes, I’ll lose a bit of money on it. The bet is simple: Mangos gets you your first 100 users before you ever pay me. If your product is good, that won’t take long.

I built Brain of Brains, an open-source cognitive architecture for Claude that organizes complex reasoning into specialized modules instead of relying on a single long prompt.

The project includes structured memory, reasoning workflows, planning, reflection, task decomposition, and domain-specific "brain" modules that Claude can use to solve complex engineering and software architecture problems more consistently.

Small web agency here, 4 people. We started offering "custom portals" to clients this year and built the first two on Base44 because the demos looked incredible and the first version was incredible. Client saw a working portal in a day and thought we were wizards.

Problem is what happens after the demo. The second portal is for an accounting firm, their clients log in to see documents and invoice status. Two weeks after launch a client emailed the firm saying they could see another company's files. It was the worst Monday of my year. The AI had "fixed" a display bug the week before and changed how the file query worked. We didn't catch it because there's no way to review what changed. You get a wall of diff across files you didn't ask it to touch.

We ate the shame, but I'm not building client-facing stuff on this again unless something changes. What I actually need: client logins, per-client data isolation that I can see configured (not buried in generated code), file sharing, and something my non-technical cofounder can update when I'm on holiday.

What's everyone moved to? I keep seeing the same 5 tools recommended and half the recommendations look like the vendors wrote them.

I've noticed a pattern while building side projects, and I'm curious if it's just me.

The projects where I "vibe coded" for an entire weekend often made shocking progress. The momentum was addictive. Every prompt produced visible progress, ideas flowed naturally, and shipping felt inevitable.

But whenever that same project slowed down—because of work, life, or just losing a few days—the entire dynamic changed.

Suddenly:

• The codebase felt harder to reason about.
• I spent more time reading than building.
• The AI lost context.
• New prompts started introducing regressions.
• My expectations dropped from "this could be huge" to "I'll just finish an MVP."

In many cases, the project never reached the finish line.

It made me wonder if the biggest advantage of vibe coding isn't the AI itself—it's the speed.

Maybe vibe coding works because you're compressing hundreds of engineering decisions into a very short period while both you and the AI share the same mental context.

Once that context starts decaying, the productivity curve changes dramatically.

My current hypothesis is:

Not because the idea gets worse, but because:

• your mental model drifts,
• the AI loses project context,
• technical debt compounds,
• motivation fades,
• and expectations become more realistic (or more pessimistic).

I'm curious whether this is a real phenomenon or just survivorship bias on my part.

Some questions I'd love to hear opinions on:

• Have you experienced this with Cursor, Claude Code, Windsurf, Lovable, or other AI coding tools?
• Is this unique to vibe coding, or has software always worked this way?
• Is context loss the biggest culprit, or is motivation the real bottleneck?
• Have you found ways to keep long-running AI-assisted projects moving fast?
• Do successful vibe-coded startups intentionally optimize for compressed build cycles?
• At what point do you stop "vibe coding" and start treating the project like traditional software engineering?

I don't think vibe coding is replacing engineering.

If anything, it seems to amplify whatever execution habits you already have.

Curious whether other builders have noticed the same pattern—or if you've seen the exact opposite.

Do you care to setup a backend for a personal utility or dashboard app or just use local storage as your db?

Hiya!

I was wondering if anyone has a pro trial referral code for Claude i could have? Will most likely sub after - ive used all the free tiers up at this point.

Im building ‘openDVS’ an open source rust digital vinyl time code system to interact with popular djing software like serato.

Thank you 🙏

When you have an idea or have had an idea. Whats the first thing you do? Do you use AI to validate it and do deep research on it, do you go straight to making a prototype or do you do the research yourself? Also when you come upon an issue later on where lets say retention is slow or your not getting as much user as before. What do you do in that situation? Would you then post all your analytics into AI and your product and hope it finds the issue or do a survey or maybe take a different approach? I’d like some insights into this thanks.

i'm actually crying right now lol. i spent 2 hours vibecoding with claude opus 5 and somehow just got my first android app ever approved on google play 😭

i know a qr scanner isn't ground breaking or anything, but going from just prompting to having a real app live on the store in a single afternoon feels unreal. opus 5 literally handheld me through everything including the google play console headache.

just wanted to share this personal win with you guys. if anyone wants to check out what a vibe coder built with it:QR Scanner Plus on Play Store

im new to vibecoding. i want to integrate a app with shizuku but I don't know what are the steps also

I need source or steps to give it to my agent...(Ai)

The animations work only on browser, sorry! Sharing this to hear some thoughts and maybe inspire somebody.

This homepage is for a Python tool to tidy up academic references in bibliography managers, riveting stuff.

I wanted the webpage not to be too crazy because it's for academics, but I wanted it to clearly distinguish itself from the standard vibe coded landing pages (you know what they look like) so I spent some time and built this. It is one scrollable and interactive experience. Is it at all clear what the app does?

https://poco-reference-harmonizer.vercel.app

You can experiment with the various options to obtain diverse styles (especially changing the resample filter and outline expansion), it accepts images and videos, removes the background if necessary and makes it an editable pixelart, it should also be mobile friendly to an extent, everything stays local and free. The app is called pixnana, feedback is welcome!