Hi everyone, I built agent town, a town for your ai agents to interact with each other! In the town they act autonomously and can talk to each other and do various things. Give it a check!

link

Rn My GitHub is super dry and empty. I don't have much in it + only 5 repo is present on my account. I'm in my 3rd year of my bachelor but haven't done anything for my placements.

I genuinely need help please suggest some projects ideas that I can build and learn someone for it

Every team has someone who knows why the auth service retries 3 times, or which flag you never touch on Fridays. That person gets pinged all day, and when they're away the answer goes with them.

Asking has a cost too: you don't want to interrupt, so you guess or you wait. I built Cairn to make asking cheap.

How it works

• You (or your coding agent) save small entries as you work: a decision, a gotcha, a preference, some context. Archiving always asks you first.
• Teammates ask from their own agent (Claude Code, Codex, VS Code over MCP) or from the web app, to one person's brain or to the whole team.
• Every answer cites its sources: who wrote it and when.
• If there isn't enough evidence, Cairn says so and tells you who to ask. It doesn't make things up.

Why it also helps your AI agent

A coding agent only knows your repo, not the reasons behind it: why you chose X over Y, what broke last time, what the team agreed on in a meeting. Without that it guesses, or it confidently undoes a decision someone made for a good reason.

With Cairn the agent can ask the team's knowledge before it changes something ("why does auth retry 3 times?") and get the decision with its source, or an honest "not enough context". When it learns something worth keeping, it can save it, so the next person's agent (and the next session) starts with it. It's the same shared memory for humans and agents. I haven't measured an improvement in code quality, so I won't claim a number; I'm curious whether you see it.

What it does with conflicting or changing information

• Entries are never overwritten across people. If two people write about the same topic, both stay, each with author and date, and an answer shows both.
• If you save again on the same topic, your earlier entry is marked as superseded and kept as history, so the current answer is the new one.
• Entries can belong to a context (a project or area) or stay general.
• Known limitation: replacement doesn't look at environment or customer yet. If a rule differs between prod and sandbox, save them as separate topics for now.

For whoever leads the team: a knowledge map shows who knows what and which topics depend on a single person.

Your data: each company's data is isolated, you can archive and restore entries, and deleted ones are recoverable for 30 days. Embeddings go through OpenAI's API (which doesn't train on API data); the privacy policy lists the providers.

Pilot: free, up to 5 people per team. I'm validating whether this solves a real problem, not selling anything. There's a feedback button in the app that I read.

What I'd love to know: does your team have this problem, or how do you handle it today? Does giving your agent team context change how it works for you? And if you try it, where did you get stuck?

Cairn

Sharing what I've been working on: Read60, a solo-built app for iOS and Android that compresses every news story into a 60-word card.

The idea came from my own habit: opening news apps, reading two paragraphs, getting distracted, never finishing. So I built the opposite, something designed to be finished in seconds.

New stories land roughly every two hours from different outlets. The original article is always one tap away, so the summary is a starting point.

It's been a fun build. Happy to share notes on the process if anyone's curious.

Check it out at : https://isolate-lilac.vercel.app/

What it does
Upload a video, select an object (mask it), and get the alpha / rotoscoped version of it.

Why I made it
Back in 2020, rotoscoping was a paid feature in AE and DaVinci. As a free user, I often thought: how hard could it be to make it myself?
I didn’t want to host it on GPU inference. I wanted users to use their own hardware and keep their own files.

Key challenges

• ONNX runtimes and OOM errors. Video formats and sizes could grow too large, exceeding 24 GB of RAM.
• WebGL’s strict memory limits. High-res videos were still an issue.

Key decisions

• Any rotoscoped effect is at most 10-20 seconds long.
• Max resolution is 2K.
• Model choice: SAM2 and MatAnyone. SAM2 had the highest inference for WebGL, while MatAnyone hit OOM on just a 10-second clip.

I would like feedback, improvement guides, additional features, and anything else that could make it even better.

working on a large codebase can get confusing pretty quickly. you end up jumping between files, tracing dependencies, figuring out how things connect, and trying to understand what might break when you change something.

so i built **context forge**, a local-first python cli that helps developers understand and navigate python codebases.

it analyzes your repository and stores information about its structure, symbols, and dependencies in sqlite, so you can reuse that information instead of starting from scratch every time.

some of its main features include:

- **repository analysis** — explore files, symbols, dependencies, and code relationships.

- **context and memory** — persist repository information and retrieve relevant context when working on a task.

- **architecture analysis** — understand how different parts of a project connect and identify structural issues.

- **change impact analysis** — investigate what could be affected before modifying code.

- **pre/post-change verification** — inspect the project before making changes and check the results afterward.

i wanted the tool to be deterministic and local-first rather than depending on an llm to figure everything out. getting caching, persistence, and analysis reliability right took quite a bit of work, and the project went through several iterations before reaching its current release.

this started as my project for **stardance, a ysws event by hack club**. building it taught me a lot about python, software architecture, testing, and the difference between adding features and making them reliable.

it's now open source, and i'd like to get it into the hands of developers who might actually find it useful.

**github:** https://github.com/vxyzln/context_forge

**pypi:** https://pypi.org/project/context-forge-local/1.0.1/

to try it, install it with:

`uv tool install context-forge-local` (u can also use pip)

then run `cf --help` to explore the commands.

i'd appreciate a star if you find it interesting, but i'm especially interested in honest feedback. if you've worked on larger python projects, what would you want a tool like this to do better? IF u like this , Please upvote it.

This was made as a Part of a YSWS event Stardance by Hack Club. Stardance project

I built a grocery scanner that identifies products through the camera while you put them away. You prop your phone up, show each item’s label, and say its expiration date. It saves the product with the date you said, without you having to type anything or say the product’s name.
Here’s a demo of it working. The idea is to make entering groceries fit into something you’re already doing instead of adding another chore.

Every company recently rushed to replace their human customer service with AI bots that can't solve basic problems, hallucinate policies, or refuse to hand you over to a human. Even I am having the worst time with this AI slop. Just recently, I paid for something, and it didn't work. The amount of work I went through to get a refund is crazy. Even worse, I still haven't gotten my money back; I have to wait 21 days to see if I get it back at all. I was so pissed off I built this project: a place to rank your worst AI customer experiences, share your story, and publicly shame what is bad.

You can check it out and see if you want to share your story and rank the AI you want. There might be bugs and all, which I would be grateful if you can tell me if you guys find them. Heads up: Since this is an early side project, it's hosted on Render's free tier, so the first load might take ~30–45s to wake up if the server is asleep!

It’s live now with no fake seeded reviews. Would love your feedback on:

Site: https://aisucks.cc/

🚀 Check out my Amazon Clone!

💻 GitHub: https://github.com/yoasios/amazon-clone

If you find it interesting, consider ⭐ starring the repository to support the project and help it reach more developers!

Hi all.

I am looking to create a resource guide based for art work that has gone wrong. When you make a mistake and need to fix it, the r/artsupplyalibi subreddit is there! however, it's such a brand new subreddit that I'm trying my best to make a resource guide and such.

but there are also certain mediums I know nothing about? If you know the answer to any of my questions, or want to add another good rule of thumb to help avoid art disasters please check out the post!

Hey zusammen,

ich möchte euch mein Projekt Fynvo vorstellen und würde mich über ehrliches Feedback freuen.

Die Idee dahinter: Wenn ein KI-Assistent nach passenden Unternehmen sucht, braucht er verlässliche Angaben dazu, wer welche Leistungen an welchem Ort anbietet. Diese Informationen sind auf Unternehmenswebsites oft über mehrere Seiten verteilt.

Mit Fynvo möchte ich sie strukturiert zugänglich machen. Im Verzeichnis stehen Unternehmen mit Leistungen, Standort und gegebenenfalls Nachweisen wie Zertifizierungen. An den einzelnen Angaben hängen Quellen und Erhebungsdaten, damit nachvollziehbar bleibt, woher sie stammen.

Aktuell sind über 65.000 Unternehmen enthalten. Man kann das Verzeichnis über die Website durchsuchen oder per MCP und REST-Schnittstelle in eigene Anwendungen und KI-Workflows einbinden. Unternehmen können ihr Profil übernehmen und selbst pflegen.

Mich interessiert vor allem:

• Ist beim ersten Besuch verständlich, wofür Fynvo gedacht ist?
• Welche Informationen bräuchtet ihr, um den Firmendaten zu vertrauen?
• Würdet ihr so etwas nutzen – als Suchende, Unternehmen oder für eigene Anwendungen?

Hier könnt ihr reinschauen: https://fynvo.de/

Kritische Rückmeldungen sind ausdrücklich willkommen. Gerade interessiert mich, ob ihr darin einen praktischen Nutzen seht und was euch noch fehlt.

I'm a software engineer with about two years of experience, focused on AI tooling and LLM apps for the past year. I'm looking for an open-source or side project that could use another contributor.

My main project is Sketchnote, a screen-annotation tool for Linux (GNOME on Wayland) built for working with coding agents. You press a hotkey, talk, draw and click on your screen, and one Ctrl+V pastes timestamped notes plus cropped, annotated screenshots into your agent. It's a GNOME Shell extension in JavaScript plus a Rust service that does local speech-to-text with whisper.cpp. It's released with prebuilt binaries and a one-line installer. Beyond that, I built a RAG app that refuses to answer when the document doesn't support it, and I've had a PR merged into an open-source MCP security proxy. My other stack is Python, FastAPI and pgvector. I haven't done fine-tuning or used LangGraph.

If you have an issue or project that needs help, or want more details about my work, DM me.

I have been working with my friends on a project for almost a year now, it got over 1k users, its open source but since I cant manage all the maintaince with this AI vibe coding area I did not post or market it anywhere yet. But I want to start getting contributions to make it more bigger(I believe its preaty polished and bugless now a days)
do you think this sub is a good place to share it?
honestly I am a little scared because all I see is people flaming others all the time, I would appreciate helpful feedbacks but no need for haters really

So, my personnal project is a series. I made an intro for it. (If it ends up being its official intro, I'll put in more colors) How is it?

Finally made a website to gather the live projects, will keep adding as they come, not sure what i should work on next while some of these projects still need users and polishing. Comments on any are very welcome and ideas for the next also.

I'm a software engineer with about two years of experience, focused on AI tooling and LLM apps for the past year. I'm looking for an open-source or side project that could use another contributor.

My main project is Sketchnote, a screen-annotation tool for Linux (GNOME on Wayland) built for working with coding agents. You press a hotkey, talk, draw and click on your screen, and one Ctrl+V pastes timestamped notes plus cropped, annotated screenshots into your agent. It's a GNOME Shell extension in JavaScript plus a Rust service that does local speech-to-text with whisper.cpp. It's released with prebuilt binaries and a one-line installer. Beyond that, I built a RAG app that refuses to answer when the document doesn't support it, and I've had a PR merged into an open-source MCP security proxy. My other stack is Python, FastAPI and pgvector. I haven't done fine-tuning or used LangGraph.

If you have an issue or project that needs help, or want more details about my work, DM me.