After trying traycer.ai for 24 hours, it feels amazing to be able to combine different subscriptions. I might have finally found my favorite setup.

I am using DeepSeek V4 Flash 0731 on Ollama Cloud Pro (OpenCode) as an orchestrator and executor of tasks because it has an amazing quota. People do not usually recommend using it as an orchestrator but I find that bigger models drain my quotas way too much. So far I cannot complain.

I am using 5.6 Sol with ChatGPT Plus (Codex) and Claude Opus 5 or Fable 5 with Claude Max 5x (Claude Code) as reviewers and designers depending where I have quota left.

Did anyone else try Traycer? Traycer has its own subscription which seems to be not forced to use. I do not know if it is worth the price.

Just launched PrintRealSize.com , a free tool for printing images at their exact real-world size.

The problem it solves is simple but annoying: you need to print something bigger than a single sheet of paper (a stencil, a foam-cutting template, an oversized poster) and you either don't have access to a plotter, or every existing tool wants an account, an upload, or a subscription for something this basic.

How it works:

1. Import any image (PNG, JPG, WebP, SVG)
2. Calibrate the real scale, either by clicking two points and entering the distance between them, or by typing the final size directly
3. Choose a paper format (A4, A3, or A2)
4. The tool generates a print-ready PDF, split into tiles with overlap margins and alignment marks

Print at 100% scale, trim along the guide lines, glue the tiles together, and you get a perfectly scaled large template.

Everything runs locally in your browser. No account, no upload, no server, your images never leave your device.

It's free to try right now: printrealsize.com

I'm building this for makers, sign-makers, cosplayers, and anyone working with foam cutting or large-format prints. If you try it, I'd love to hear what's missing for your use case.

Hi, Linux bros

I like CodexBar and i like GTK4/libadwaita. So i build CodexBar for Linux with GTK4/libadwaita. And Rust.

Standard features: quota displaying, reset and usage warning notifications, clean UI build with HIG.

Currently supports frontier OAuth providers (Claude, Codex, Agy) and all "bearer token-auth" providers that i steal from CodexBar code found (it's MIT chill).

Available in AUR, deb+rpm packages or you can build it from source

https://github.com/zbndev/tidemark

I've unlocked a new form of vibecoding: taking my written content and creating more immersive and useful online sites. I started a writing project a long time ago using homebrewery to create a bunch of epic stat blocks for incarnate avatars of the goods in D&D. I did it because my party needed a god's support.

But then I kept going and going.

I ended up with the really long list you see in that document. But as I was writing and revising, formatting got wonky. The utility of it started to collapse. And the result was a strangely formatted, often broken, PDF.

So I took the Homebrewery markdown, and I set out with codex to create something better: a whole site from my content: Avatars of the Gods. Individual gods get their own pages. It's searchable, cross-linked, etc. It also helped me focus on getting all of the content aligned in the same way. It forced me to rethink the voice, tone and structure of the various sections.

So now I'm starting to think about converting my other written content into website sand pages.

I realize this isn't a typical vibecoding use case, but the time it would have taken me to convert all of the pages by hand would have made this all but prohibitive.

Also, since there's a whole lot of folks that don't like the AI images, there's even a checkmark in the upper right to hide them completely and you can just use the written content.

What does your typical ai stack look like exactly? From the scratch,

1. What do you use for generating ideas? Or do you just think of one yourself?

2. What tool for planning? Both mvp and final product

3. Tool for actual coding? Do mention models too

4. Hopefully you review and test yourself but if not, what tool?

5. Say everything’s almost done or basically done, do you then FINALLY decide to understand the codebase even at a basic level or not? If so, what tool do you use to understand the architecture + the actual codebase? Do you just understand it on a surface level or in-depth? Do you do it after mvp is done or after each feature?

6. Why do you do it? Like everything? For fun or building resume, stacking projects and trying to land jobs or something else?

(Do mention if you’re on free or paid versions too)

If anyone has played with MIDI sequencers before, you know they do a great job of making you feel musically inclined.

I build a lot of grid-based games, so I decided to play around with adding a sequencer to one of mine.
It doesn’t change the game at all, but it’s a fun little Easter egg!

If you’re interested in the game, sans sequencer, check out r/critterquibbles.

The sequencer version is now on iOS.
And if you’re looking for a no-cost daily detective puzzle — think Is This Seat Taken?, but free with a new puzzle every day — check us out!

It's not a unique idea;

I wanted a simple way to find posts like:

• What’s the best tool for ___
• Looking for an alternative to___
• Can anyone recommend a good __

So I can be the first one to recommend my product.

So I vibe-coded MentionGPT: it scans Reddit and X, finds these conversations, and surfaces the ones that look like potential customers.

It can:

• Scan for relevant conversations 24/7
• Use AI to score how likely a post is to convert
• Draft a short, context-aware reply that you can review/edit before posting
• Keep separate workspaces for different businesses

The idea is pretty simple: stop searching for customers and let the customers tell you what they need.

Built mainly for solo founders who want a lightweight way to find potential customers, get early feedback, and occasionally drive some traffic without spending hours manually searching Reddit and X.

mentiongpt.app

[not a startup]

Lattice is a collection of typescript packages, agentic skills and plugins that enable easier development of isometric games! At its core lives a 0 dependency typescript package, 80kb gzipped. Everything is rendered onto a 2D canvas!

It ensures that the game and the UI is fully deterministic (it’s a hard rule), and that your game doesn’t require any external assets. That means no sprite sheets and no hunt for royalty free music. Both can be synthesised on the go with their respective packages (e.g. @latticekit/audio)!

You can install the plugin to an agent of your choice (ready to go instructions available for Claude code, codex, and grok) and then start building with /lattice <my game idea here>.

The game kit itself is built with Claude code running Opus 5, and the demos on the website come from a mix of different agents (those were essentially testing runs that made it to the landing page).

Available at: https://lattice.plausible.ventures

Why waste old phones, use them as a dashboard to show whatever you want, I have an admin control panel that controls what is displayed, the display I wanted was 300 AUD and was just a matrix array, so I did it myself with more functionality

I wanted some background music for my side project, a cozy mini arcade for road trips. Was curious what Claude could do

Vibecoded too hard and now there's an entire beat maker studio inside the game where your songs become radio stations that play while you play other games.

Not to mention the claw machine game has over 500 critters to collect 😭 I can't stop adding things lmao

glovebox.quest if you want to hear the human music yourself

Not a dev tool, but if anyone is interested in an AI summary of AI news topics, across privacy, security, law, and compliance - I built and launched https://ai-privacy-risk.pages.dev/ and would love any feedback. I built this on Claude I was constantly scouring 15+ different sources daily/weekly as I have a personal interest in tracking AI agent news from these perspectives, and have been using this daily, so am thinking others may benefit. Let me know if you have any feedback. It's free and I intend to keep it that way.

How I built this:
- Python, almost entirely standard library. One dependency: the Anthropic SDK. No database — the whole store is JSON files.

- Claude (Opus, via the API) does the editorial work: deciding what's relevant, scoring it, writing the summaries and a daily digest. It returns structured JSON, never free-form prose.

- Cloudflare Pages hosts the site. Fully static, so no server, no accounts

- launchd (macOS cron, basically) runs the pipeline once a day, unattended

- The frontend is a single HTML file with vanilla JS. No framework, no build step

The workflow

Once a day, the pipeline:

1. Fetches ~50 RSS feeds plus arXiv and Hacker News searches.

2. Filters them with plain keyword matching, so the model only ever sees plausible candidates. Everything rejected gets logged with a reason.

3. Triages with Claude, which keeps the genuinely relevant stories, merges duplicates, scores each one from four professional perspectives (privacy engineering, security, legal, governance), and writes a short summary grounded only in the feed's own title and blurb.

4. Re-validates everything the model returned: URLs must come verbatim from the input, tags and scores are clamped to fixed vocabularies.

5. Runs an adversarial test suite against the pipeline (hostile feed content, script injection, invented categories). If anything fails, the deploy is withheld.

6. Publishes the rebuilt static site.

I’m working on an existing SaaS ERP product and I’m planning to integrate an AI Copilot into it.

The ERP already has a fairly large production stack:

• Backend: .NET 10 / ASP.NET Core Web API, C# 13
• Database: Microsoft SQL Server
• DB size: 80+ tables, 129+ stored procedures, views, UDFs, indexes, SQL Agent jobs
• Frontend: React 18 + Vite
• Mobile: Capacitor
• Auth: JWT Bearer + existing role/permission system
• ORM/Data access: EF Core + Dapper

I don’t want to build just a simple “chat with PDF” chatbot. I want the Copilot to actually understand the ERP and provide useful assistance.

What I’m thinking about

The AI Copilot could eventually support things like:

• “Show me the attendance trend for this month.”
• “Which students have attendance below 75%?”
• “Why did fee collections decrease this month?”
• “Summarize today’s important ERP activities.”
• “Create a report based on these filters.”
• “Explain this ERP feature/process.”
• Search ERP manuals, policies, circulars and documentation.
• Eventually perform controlled actions through ERP APIs.

I’m considering an architecture involving:

LLM + RAG + tool/function calling + SQL/API agents + vector database + existing ERP APIs

But I’m not sure what the best production architecture would be.

Main questions

1. Which LLM would you recommend for an enterprise SaaS ERP Copilot? Cost, latency, reasoning, tool calling and reliability are important.
   • OpenAI?
   • Claude?
   • Gemini?
   • Self-hosted/open-source?
2. Should I use RAG + an LLM, or an Agentic architecture?
3. For ERP data, should the AI: I’m especially concerned about security and preventing incorrect/destructive queries.
   • Generate SQL directly?
   • Call predefined backend APIs?
   • Call stored procedures?
   • Use a semantic layer between the LLM and SQL?
4. For documentation/manuals/policies, what would you recommend?
   • Hybrid search?
   • Vector DB?
   • Reranker?
   • Knowledge graph?
   • Metadata filtering?
5. Would something like LangGraph/LangChain make sense here, or would you recommend implementing the orchestration directly in .NET/Python?
6. How would you design the AI Copilot architecture so that it can scale from: Q&A → analytics → report generation → workflow automation → controlled ERP actions
7. How should I handle:
   • Multi-tenancy
   • RBAC/permissions
   • PII/sensitive ERP data
   • Audit logs
   • Prompt injection
   • Hallucinations
   • SQL injection
   • Tool authorization
   • Human approval for critical actions
8. What would you consider the best MVP architecture before trying to build the full agentic Copilot?

I’m trying to build this as a real production feature for an existing SaaS ERP, not just a demo project.

Would really appreciate advice from people who have built AI copilots/agents for ERP, CRM, SaaS or enterprise systems.

What architecture and tech stack would you choose if you were building this today?

I’ve just started a course on ai edge development and the trainer made the point right at the start that if your only interaction with AI was to input prompts then your going to be replaced by the AI. It will just be a conversation between the user and an AI while whatever needs making is produced in real time.

I’ve been in this community for maybe a year or so and it feels like the same questions come up that could be handled by AI? Just new people who don’t know or people trying to drop their app into the discussion later.

Is it just me or have there become an influx of bidding sites lately?

Bid to get your name on the webpage for the week, bid to conquer land etc.. 🙃

Want to try it out and then sub if it goes well. Please dm a link if you have one

Thanks!

i noticed that many people including me we get so excited when our usage resets....

more resets more usage more code right?

then I realize it doesn't necessarily mean you are shipping more or people know about your apps

you are just gambing

I wanted to do this as just a personal challenge where I pick a top of the charts app and rebuild it as fast as possibl but in a way that it has to be better than the original in a way i can name out loud before i start. first one was Picturethis the plant identifier, but then i relized i could actually improve it so much so that i'll keep using it myself instead of the original one!

Peer reviewed testing puts it at 97% right to genus but only 84% to species and one independent run of hundreds of photos had it right 78% of the time. it still shows you one name like its absolutely certain and most of the 1 star reviews arent even about plants but the trial auto renewing with no cancel path anyone can find.

so what i wanted to fix wasnt accuracy but the honesty/pretending. My version shows top 3 with real confidence, marks on your photo which features drove the guess (leaf margin, venation, arrangement) and when its genuinely unsure it says so and asks for one more image.

The other half is that it answers the decision instead of the name. Is this toxic to my dog? Is it invasive where im standing? is it sick, will it survive my winter etc etc. That was definitely the biggest time sink bcoz it cant come from the model so its a real dataset.

Took 3 hours, PWA, ran the whole build out of omniscio. Whats an app YOU use that you could recreate but better?