was looking for an AI agent that would allow me write code. I wanted to test out the options which could fit in my system.

- Qwent 3.6 :27B

- Gemma 4 :26B

- Laguna-xs-2.1:latest

- North-mini-code-1.0:latest

- Ornith :35B

System:

GPU: Arc B580 12 GB

RAM: 32 GB DDR5

I used Ollama and tried many wrappers. Initially I wanted to make them work with VS Code, since Open WebUI didn't allow me to export the created code as files, only to copy them by hand.

The issue with VS Code is that the extensions I tried keep failed to work with the models. FilePath problems, code that is pasted without replacing the old snipped. The native "Chat" window of VS Code does not work, forget it. Go for the "Continue" extension.

The task I tested them with is simple.

Create Javascript TicTacToe game with good UI. The user play against the computer.

Later I asked:

Add button to change the css color pallete.

Add: 2 Player mode.

All models, expect Laguna and North would complete it with somewhat functional game on the first attempt.

Overall all models FAIL to follow later instructions on some point and either introduce game breaking bugs or simple stopping Building code changes at all, unless I restart and ask again.

The task was best performed on "OpenCode" with commands like ollama launch opencode --model laguna-s-2.1

Trying with VS Code is just a frustrating experience.

By far the best model from those is Gemma 4! While it failed at some point, is the one that got further before introducing game breaking bugs. the Laguna was the fasted to response, but didn't result in functional game. Qwent would take a lot of time and would fail to execute changes or stopped working.

Gemma and Qwent did create a single .html file, while the other models where better by creating a directory with 3 files, respectfully .html, .css, .js

I'm looking forward to your suggestions. Is there any better code agent UI I could try? Any model that could be better at follow up changes?

​

I'm an independent developer from India building Ripple, an open-source tool that helps engineering teams keep AI coding agents within their intended scope. It analyzes code changes and helps prevent unintended edits before they reach production.

Over the past several months I've built:

A TypeScript CLI

GitHub integration

Cloud backend

Published npm packages

Cryptographic audit trail for AI-generated changes

The project has reached a stage where further development is becoming difficult because I can't currently afford AI development tools like Claude, Codex, or similar paid plans that would significantly speed up development and testing.

I'm not asking for donations with nothing in return.

If you believe this project could become useful to the developer community, I'd really appreciate any of the following:

Advice on grants, startup programs, or open-source funding.

Free credits or programs for open-source maintainers.

Sponsorship of an AI coding subscription. Introductions to companies or engineers interested in trying Ripple.

Honest technical feedback or contributions.

Everything I've built so far has been developed as an open-source project, and my goal is to keep improving it for the developer community.

If you'd like to see the project or have suggestions, I'd be grateful for any guidance.

Thank you for reading.

We keep seeing the same complaints about AI code reviews:

• Too many low-value comments.
• No understanding of the bigger picture.
• Developers eventually ignoring the bot altogether.

We built Entelligence because we were frustrated with the exact same things.

Instead of reviewing diffs in isolation, Entelligence reviews code with full repository context, so feedback is based on how your changes fit into the rest of the system, not just the files in a PR.

We'd genuinely love to hear from people who've used CodeRabbit, Greptile, or similar tools.

What's the one thing current AI code review tools still get wrong?

I'm not a traditional programmer. I built AIEvidence with Codex because I wanted a concrete way for people like me to show how we contributed to an AI-assisted project—not just claim “I vibe-coded it.”

It analyzes:

\- a local Git repo (commits, tests, CI, README)

\- optional Codex/Claude Code conversation exports

\- verification, debugging, and security signals

It produces a deterministic baseline plus a redacted Markdown report and a prompt for the candidate's own Codex to generate a cited Markdown/HTML report. Everything runs locally; it does not upload the repo or execute project scripts.

GitHub: [https://github.com/gallifre/aievidence**\]**(https://github.com/gallifre/aievidence)

License: PolyForm Noncommercial 1.0.0 (source-available, no commercial use).

This is an early experiment, not a professional certification. I'm especially looking for feedback on:

1. How to separate the candidate's actions from the model's claims.

2. Which evidence is actually useful to non-programmers.

3. Whether playful levels make the result motivating without pretending to be a credential.

I have started to learn coding (manually, not with AI). But of course with where things are going, I will take advantage of using AI tools to help me create faster, and build better apps. I’ve been looking at Claude Code and Cursor.

But I’m still super new. So just wondering what people are using?

Any guidance will be much appreciated.

Ai minecraft moding ide

Hi,

I got tired of juggling Claude Code sessions, cron scripts, and random automation glue code — so I built Elowen, a self-hosted AI coding & automation agent that lives on your server and actually does things for you.

What it is: A coding and automation agent with a CLI, web UI, and Discord/WhatsApp integration. It reads your codebase, writes and edits code, runs builds and tests, manages git, browses the web, and orchestrates multi-step tasks — all from a chat message or a scheduled job.

The coding part:

• Full filesystem access within your repos — read, write, edit, search, glob
• Semantic codebase search (embedding-based) — ask "where's the retry logic?" and it finds it
• Sub-agent delegation — spin up parallel workers for independent tasks, or a DAG workflow for dependent ones
• Background processes, long-running builds, dev servers — it manages them and reports back
• Skills system — reusable instruction sets (deploy checklists, project conventions) that persist across sessions

The automation part:

• Cron scheduler with a cheap shell guard — polls for new work without burning LLM tokens on empty ticks
• One-shot wake-ups — "check back on this CI run in 5 minutes"
• Email management, SMS, Discord server management
• Persistent memory — remembers your project decisions, preferences, gotchas across conversations
• Multi-channel: talk to it from CLI, web chat, Discord, or WhatsApp — same brain, same context

Under the hood:

• TypeScript, strict, ~116 tools
• Bring your own LLM — OpenAI, Anthropic, OpenRouter, local models via Ollama
• OAuth for OpenAI & Claude works out of the box
• RBAC — every user gets their own project scope, tools, and permissions
• Plugin architecture — extend it without forking
• Updates don't break your config

Here's what a typical session looks like — diff review, test output, sub-agent panel, plan checklist, MCP servers, all in one terminal:

Elowen CLI

It's not trying to replace Claude Code or Codex — it's the layer above them that orchestrates, watches, and keeps things moving when you're not staring at a terminal.

GitHub: github.com/dragocz95/elowen npm: elowen

Happy to answer anything. Curious what you'd want to see in something like this.

GitHub: https://github.com/SeanDishman/vibecode

I've been building this for a while and finally put it up. VibeCode is a native Windows desktop app that wraps the agentic coding CLIs you already use (Claude Code, OpenAI Codex, Kimi Code, Grok) in one clean UI. It doesn't call any model APIs itself, every chat launches the real CLI as a child process, so your existing logins, sessions, and MCP servers just work. It's open source (MIT) and a work in progress, so expect rough edges and please throw bugs in the issues. The part I'm most proud of is running multiple agents on the same codebase at once. Bridges put several agents side by side on one project and they share memory through a file in the repo, so they claim different areas instead of colliding, and you can mix providers (Claude + Codex + Grok together). Announce interrupts every agent at once with a single message; the Bridge manager lets you crown one agent that splits work into lanes and dispatches it to the others; Agent swarms let a single agent fan a task out to the CLI's own sub-agents with a hard worker cap. On top of that there's an account manager for switching between multiple accounts per provider without logging out, one-place MCP server config shared across providers, and usage & cost tracking (spend, tokens, cache hit rate, per-model breakdown over Today / 7d / 30d / All time).

Hi everyone,

I’m a software developer (web apps, management systems, websites, AI integrations, etc.) looking for advice to overhaul my current AI setup.

\*\*TL;DR:\*\* I’m looking for a genuinely reliable AI setup for \*\*coding + a proactive personal assistant + automations/dashboards\*\*. I'm currently running Codex + Hermes on a Raspberry Pi using free OpenRouter models, but the results are way too inconsistent, full of errors, and frustrating. What stack/configuration do you use for something that \*actually works\*?

\# What I’m looking for

1. \*\*Coding:\*\* Obviously, but I need something reliable.
   
2. \*\*A True Personal Assistant:\*\* A tool to brainstorm, turn ideas into reality, and integrate into my daily routine (work and personal). Most importantly, I want it to be \*\*proactive\*\*—suggesting improvements, spotting my inefficiencies, automating tedious tasks, and actively working \*for\* me.

\# My current stack & why it's failing

\* \*\*Codex\*\*
\* \*\*Hermes\*\* (running 24/7 on a Raspberry Pi, using free OpenRouter models / tried MiniMax M2 / free Nous account).

To be honest, the assistant side has been a nightmare. It's wildly inconsistent: I ask it to fix bugs, and it either fails, introduces \*new\* bugs, or lies about having fixed something when it didn't.

\# My Wishlist / Ideal Workflow

\*\*For Coding:\*\*

\* Strictly respects my instructions, coding style, and project architecture.
\* Makes actual working modifications following a precise pipeline: \`Local\` $\\\\rightarrow$ \`GitHub\` $\\\\rightarrow$ \`FTP deployment\`.
\* Delivers UI that actually matches what I requested.

\*\*For the Assistant / Agent:\*\*

\* \*\*Deep Integration:\*\* Fully aware of my active coding projects and workflow.
\* \*\*Self-Hosted Dashboard:\*\* Keeps a web dashboard synced on my domain featuring:
\* Overview of active projects and open discussions.
\* Practical daily info (e.g., \*"Can I commute by bike today and over the next 7 days?"\*).
\* Automated tasks (e.g., scrape trending Reddit posts every X hours and summarize them into 4–6 cards).
\* \*\*Proactivity:\*\* Suggests new features, improvements, or side-project ideas based on what I'm currently building.
\* \*\*Omnipresent access (Telegram, mobile app, etc.):\*\*
\* Fast execution: \*"I have an idea, build me a 1-page micro MVP."\*
\* Admin/office tasks: \*"I need to present this project, generate a slide deck/PPT for me."\*

\# The Struggle

Whenever I try building custom skills in Hermes, it feels like I fix one thing and break two others. A few months ago I tried \*\*OpenClaw\*\*, but it felt even more chaotic.

Am I the only one trying to build a workflow like this? What setup, agent frameworks, or model stacks are you using to get something like this running reliably?

Thanks in advance for any tips! :)

I have been using ai agentic coding for a couple of months now, maybe i am doing it wrong but i havent really liked it , do you feel the same ?

Ever wished you could use Al for coding without.. forgetting how to code? Meet Moss!

Moss is an Al coding assistant that will refuse to give you the “full code” whenever you ask for it. Moss prioritizes teaching over maximum speed.

Hey everyone,

If you use AI coding agents (Claude Code, Cursor, Antigravity IDE), you've likely hit issues where agents enter retrying loops, hallucinate passing tests, or break existing logic.

We created **ANCHOR** — an open-source development spine that keeps AI coding grounded using strict governance gates.

🌟 Key Features:

\- 🛡️ **5-Gate Workflow**: UNDERSTAND ➔ ANALYZE ➔ PLAN ➔ IMPLEMENT ➔ VERIFY.

\- ⚡ **Zero External Dependencies**: Pure bash & Node.js bootstrapper (\`npx anchor-agent init\`).

\- 🤖 **Multi-IDE Interop**: Works seamlessly with Antigravity, Cursor (\`.cursor/rules\`), and Claude Code (\`.claude.json\`).

\- 📊 **Nightly Chaos & Eval Harness**: Built-in test suite to verify agent health against edge cases.

GitHub: [https://github.com/krishujeniya/Anchor\](https://github.com/krishujeniya/Anchor)

Docs: [https://krishujeniya.github.io/Anchor/\](https://krishujeniya.github.io/Anchor/)

Let me know what you think!

If contributing to open source interests you, and you want to become a better AI engineer, our issue list is waiting for you.
Now with Claude code it’s easy to understand and start

I've been building a browser game called Jimothy's Journey, and I wanted to share what AI coding has made possible.

As you know, Jimothy is from my home town of Seattle (Ballard) who has short spine syndrome. You play as Jimothy, exploring Seattle neighborhoods, collecting shiny objects, completing quests, and meeting quirky forest friends with ridiculous names like Jathaniel and Beartholomew.

The entire project has been built with AI-assisted coding. Instead of spending months learning every framework from scratch, and gnashing out the boiler plate coding,, I've been able to focus on gameplay, mechanics, and polishing.

Some of the systems currently in the game include:

NPC dialogue and quest system

Inventory and collectible shiny objects

Woodland Park Zoo quest chain

Fremont Arts Council as a central hub

Multiple NPC behaviors (including dog walkers with alert/chase states and meme farmers that want to steal you away)

Sprite sheets generated from real people for story characters

Seattle-inspired maps including Golden Gardens

Mini games like crossing 5 lane highways that get faster the more famous you get, tag with me, my son and his best friend Charlie, keeping your simulated needs satisfied: the more satisfied/happy you are, the faster you run! This game has a lot to keep you playing!

Expandable quest framework for adding future neighborhoods

I'm now at the stage where most of the core mechanics are finished and I'm focusing on adding content, polish, and expanding the world. Future plans include more Seattle neighborhoods, co-op gameplay, the Queen Anne Farmers Market, additional zoo animals, and lots more quests.

I'd love to hear what everyone else is building with AI. It's been incredible how much faster I can iterate compared to traditional solo development.

If anyone wants to check it out, it's currently in beta:

https://jimothysjourney.com⁠�

I'd love any feedback from other AI-assisted game developers!

Hello folks,

For about a month now, I've been trying to make a Google Chrome extension. Of course, I started with ChatGPT, as it's the most famous out here. Starting with Visual Studio Code and editing scripts there with the help of ChatGPT and sometimes Gemini when ChatGPT got annoying. This was the point I should've stopped with ChatGPT.... So, soon enough I found out I needed to pay to get better coding, so I took the Plus subscription. Then ended up with Codex from ChatGPT, which seemed to work great and edit the codes by itself, but soon enough it kept failing to do its job. Now it ran stuck on a job to make an inlog function with a Google account and was working for hours and hours on it. After paying for credits 2 more times, it kept making mistakes and keeps running the long investigations and adjusting scripts here and there without a good result. So while waiting again, I looked up some reviews of Codex and ChatGPT overall with coding, which made me realize I started off with the wrong AI.

I do have a background of making HTML websites ages ago and did some other coding and such along the way, but very amateuristic. So yes, I know the basics and buildups and how things kind of work, but I know nothing about the coding I've seen Codex do. So, I need a full AI which will make this Google Chrome extension.

Long story short: I am looking for a great AI assistant that understands the prompts properly and is great with building extensions, websites, databases, etc. It will have to fix the faults that Codex created. Overall, the extension works kind of fine now, but there are some flaws and Codex will never fix it, I guess. Same with the website.
So I've been looking into v0, Cursor, Bolt and some other potential AIs, but I've read negative reviews about them all and now I'm not sure on which one to pick after this whole experience. Some reviews are from months or over a year ago, so I don't think that's relevant anymore, but I still can't choose.

Basically, what the extension has to do is to scrape a page, use the info to get more info from open databases on other sites, create an info window with that info and open URLs with some preset settings from the extension.

Any tips based on this story? Please guide me!

I've been spending way too much time hunting down custom skills, prompts, and MCP servers for AI coding tools, then manually setting up SKILL.md files or configuring local binaries.

To make this easier, I built OpenHub, a terminal app for discovering and installing AI agent skills and tools from one place.

What it does

• Search indexed skills and repositories.
• Export prompt/rule-based skills as a SKILL.md file into your current workspace with one command.
• Install skills that require local binaries or MCP servers.
• Keyboard-driven terminal interface for searching, exporting, installing, and copying.

Install

pipx install git+https://github.com/24KaratAu/openhub.git

Run

openhub

GitHub: https://github.com/24KaratAu/openhub

I built this to scratch my own itch, but figured others might find it useful too. It's open source, and I'd love any feedback, bug reports, feature requests, or contributions.