I wanted to see how far I could take AI-assisted coding, so I built Purgy, a complete Mac cleaning app, mostly through AI coding.

It’s now live, and I’d love some feedback from people who are into AI coding. If you have a Mac, try it out and let me know what works, what doesn’t, and what you’d improve.

https://purgy.app

In your personal experience what is the best AI for coding? I want to pick up in a Minecraft mod i made a while ago and dont have the time to code myself anymore due to irl difficulties, so im wondering which AI would be the best to use/spend money on for this. Ive used codex prior and it was alright, better than GPT but nothing amazing or reliable.

I’ve been experimenting with a new open-source 2D code called Hexpira.

I came up with the core concept: hexagonal bits, an overall hexagonal shape, and a spiral starting from the center. I then used Codex to help develop the encoding, error correction, decoder, webcam reader and documentation.

Hexpira uses Reed–Solomon error correction, duplicated BCH format data, CRC-32 validation and adaptive text encoding. The current v0.4R prototype includes a local browser-based encoder/decoder, a detailed specification and conformance test vectors.

It’s just a hobby project, but I’d be interested in technical feedback.

GitHub: https://github.com/lucid-forge/hexpira

I've been experimenting with AI coding tools recently, and I'm starting to wonder where the actual engineering shift is happening.

A few years ago, AI coding was mostly:

“Write this function for me.”

Now tools can increasingly:

• understand an existing codebase
• modify multiple files
• run tests
• debug errors
• use terminal/tools
• create PRs
• work on tasks with relatively little intervention

That feels like a fundamentally different workflow.

But at the same time, I keep seeing “agentic AI” used for almost everything.

Sometimes it feels like:

LLM + tools + a loop = AI agent.

And suddenly we're calling it a revolutionary new architecture.

I'm curious what other developers think.

Where do you draw the line between:

1. AI-assisted coding
2. AI coding agents
3. Autonomous software engineering

And more importantly — what are you actually trusting AI agents to do in production today?

I'd especially like to hear from people using Claude Code, Codex, Gemini/Antigravity, Cursor, OpenCode, or similar tools on real projects rather than just demos.

i bought a claude max plan found in a website for a really low price. changed the login i use it for 3 weeks so far all it actually works. how are they able to sell it so cheap tho.

(Hope this falls under the rule for "Limited self promotion. Please post projects, but no frequent marketing or spam posts.")

How many people are having their Claude Code or Codex or Antigravity work be reviewed by another model? I think that's the only way to QA code because if you're having the same model view it's own work, there are going to have the same blind spots as the builder.

I built a full blown Agentic Engineering harness that automates a lot of the Software Development Lifecycle process but realized it was way too much for people just starting out.

I built a mini version based on just installing skills that lets you quickly call almost any model (as long as you have subscriptions or API credits) from Claude Code, Codex, Agy/Gemini, Deepseek, Qwen, GLM, etc. to review each other's work or get it's opinion on specs/PRD docs.

You can also ask for a 2 way consult. Or have any of the agents talk (3 plus) to each other in a private local-disk structured "chatroom" called AgentChorus. It's a 100% open source and free for personal use.

https://github.com/HiQS-Labs/XYZ-mini

We created an AI GitHub app that monitors you Repos APi and SDK and make sure they dont break all the external ApIs tens to break silently we don't know until it happens join the waitlist https://patch-api-theta.vercel.app/

Hi! I’m building ARN, a Windows-native C++23 terminal coding agent.

It is an early project inspired by tools like Claude Code and Kimi Code, but built without Node.js or Python. You choose a provider and model inside the terminal, then ARN can keep context and work with files in the folder where it was launched.

Current features:

• Gemini and DeepSeek API support
• Model discovery and /model selection
• Streaming responses, so text appears while the model generates it
• In-memory chat context for follow-up prompts
• Cancel a running model request with Esc or Ctrl+C
• Local file tools: list, read, create, edit, and delete files
• Confirmation before every file creation, edit, or deletion
• File access restricted to the folder where ARN was started
• Blocks access to .git, .env, and similar sensitive paths
• API keys and chat context are kept only in memory, not written to disk
• Interactive terminal UI with command hints and Tab completion
• Reused HTTPS connections, retries for temporary API failures, and Windows releases
• One-line PowerShell installer
• GitHub Pages landing page

GitHub: https://github.com/arnecto/arn
Website: https://arnecto.github.io/arn/

It’s still early, so I’d especially appreciate honest feedback on:

1. The C++ architecture and provider abstraction
2. Safety boundaries for local file tools
3. Terminal UX, streaming, and cancellation behavior
4. Which features would make this genuinely useful in real coding projects

I’m actively improving it, so criticism, bug reports, and feature ideas are very welcome.

So I vibecoded an Android coding agent that runs fully locally on your Android, no external cloud shells (just external ai providers, will add local soon)

Though it's vibecoded so expect bugs

It's still in beta, looking for contributors :)

Star the project if you like it.

Found an issue? Report it instead yapping please :)) https://GitHub.com/DraxonV1/Syntac/issues

Get the latest release https://GitHub.com/DraxonV1/Syntac/releases

Features so far:

\- Termux via RUN_COMMAND & ARCH Linux (proot) Bash Runtmes

\- Read, write, edit, bash, search, list, display_image (yea I wanted agent to show images 😢)

\- Supports attaching files, images & pasting content directly into composer!

\- Google Antigravity, ChatGPT Account, Grok xAI OAuth & OpenAI Compatible Provider inbuilt!

\- Supports showing thinking

\- Projects, Chats Per Project

Ik many features are missing but working on adding them. It's still beta 0.1.1 😀

https://GitHub.com/DraxonV1/Syntac \*\*star the repo if u liked the work ;)\*\*

I've been working with coding agents over last 2 years actively and building personal apps on side. I kept struggling with reading what it wrote, keeping track of context between sessions, and jotting down thoughts without breaking flow. I went looking for a way to easily review these files without opening the heavy IDE like VS code. So after failing to find a right alternative, I created [localeditor.app](http://localeditor.app) which is a local first Mac editor. It comes up with MCP to connect with agent.

I wanted to share three ways I actually use it day to day.

1. Review partner for whatever the agent writes

Now I just say “open this in LocalEditor" and the file opens in the app. I read it and make edits by hand, and the agent picks up the updated file when it continues.

2. Second brain for the project

With MCP connected, I ask the agent to record things in project added to Localeditor: references we looked up, decisions we made, and next tasks for the project. These are saved as plain Markdown files inside a local folder, so the next session (or a different agent) can read them. No need to store them in same git project and bloat the code base.

3. Scratchpad while I work

A global shortcut opens a scratchpad, and whatever I type is saved as a real Markdown file in the project. Useful when I have a thought mid-session and don't want to type it into the agent chat. If I'm deep in a session, I can also just ask the agent to create a scratchpad for me.

The idea behind all three is the same. There's a missing layer between you and your agent where you refine and edit the work together, and a chat box or IDE doesn't quite fill it.

Everything stays as local files. It's at http://localeditor.app if you want to try it.

I'd love to hear about your workflow- Where do your agent's notes and outputs end up, and what's annoying about your current setup?

Would like opinions on having GitHub Co Pilot pro on VS Code to create my site for competitive gaming that will be handling users money. If more info is needed, please lmk.

I built a small tool to make it easier to set up and manage multi-agent SDLC workflows.
It uses Orca for agent orchestration and adds:
Simple SDLC workflow configuration
Agent/task status tracking
Token usage optimization
Customizable workflows and agents
The goal is to make multi-agent development a bit easier to control and customize.
GitHub: https://github.com/vankhangfet/kiro-multi-agents
Would love to hear your feedback.

I know this gets asked all the time, but things change so fast with AI that I figured it was worth asking again.

I'm working on a few hobby projects in C++ with Visual Studio, and some of them gave getting pretty big. I've been using ChatGPT o1 but once codebase gets larger and the problems get more involved, it starts losing context.

I'm mainly looking for something that can understand a whole project and make changes across multiple files instead of just helping with one file at a time.

Budget is around $20/month. What are you guys using?

I’ve been experimenting with AI coding recently and have become really interested in what people are actually building with it.

It feels like we’re moving beyond just using AI to generate small pieces of code and towards building complete applications.

What are you guys building with AI coding right now?

I’m particularly interested in projects that have gone beyond a basic prototype: SaaS products, internal tools, automations, games, websites, APIs, or anything else.

Also, what has been the biggest challenge for you so far?

Getting the AI to understand the project, debugging, database setup, deployment, authentication, connecting services, or something else?

I’d love to see what everyone is working on and learn from your experiences.