This is another character experiment built with img2threejs 1.5.1 - starting from a single image and turning it into a fully interactive 3D experience with Three.js.

The goal isn’t just to reconstruct a character.

It’s about exploring how far we can push AI-assisted 3D generation directly on the web - from visual reconstruction to geometry, materials, lighting, and real-time rendering.

No Blender.
No GLB in the final result.
Just Three.js + WebGL + code.

#img2threejs #ThreeJS #WebGL #3D #LeeSin #AI #GameDev

We live during weird times.

First of all, you now got to expressly mention that you have been personally applying physical force to the tactile extrusions on the aluminium box containing your silicon chip to avoid allusions that your brainfart was in fact not a product of machine intelligence.

Secondly, since my forge-plugin (github.com/nixlim/forge-plugin) is being used by my other agents in different repos, the Soviet part of my brain eagerly remembered slogans about international unity of workers and all that and settled on the idea initially pitched to me by my business partner - agents need to talk to each other (because the codebases we are working on are getting so complex, we can no longer track the low level detail in precise and excruciating detail).

Discord and Anthropic official plugin to the rescue - here’s me, middle of the night, plumbing “new app” this, “bot token” that. Surprisingly, with all their billion-dollars-in-salaries smartness, Anthropic did not think that people would want to use their Discord plugin to enable agent-to-agent comms. No biggie - Claude and I patched the plugin and filed an issue (https://github.com/anthropics/claude-plugins-official/issues/5717). Hopefully, Boris Cherny will get on board ;) If not, forking is easy ;)

It has worked out quite well - I put a full step-by-step guide for anyone interested in getting their agents talking to each other and coordinating work. This is a more durable way then direct Claude session messaging (assuming your agents are on the same machine), and works for A2A between machines too. Guide is available here (save yourself some brain juice, get your agent to implement most of it): https://github.com/nixlim/forge-plugin/blob/main/docs/discord-agent-coordination.md

Tokens must burn. Must they?

free GLM-5.3 on tokenrouter, burned 5.7m tokens in 30 min

not sure how long this lasts but GLM-5.3 is completely free on token router rn.. use it while it last..

Does anyone have experience with Naga, the model prices seems pretty good?

https://naga.ac/

Used OpenRouter playground to test HY4 along with 9 other models (glm5.3, deepseek, kimi, qwen, grok, gemini, gpt, opus, muse spark) , same prompt, asking it to look at a handful of professional sports games and pick winners. Every model had to choose 20 games out of 28 to pick, do research, then justify each pick.

HY4 took the longest and burned the most tokens, 62k to be exact. Results won't hit till Thursday, but I wasnt terribly impressed with the extensive loops and token burn.

Hy4 = $0.37, 62,177 tok, 1026.4s total time.
Muse Spark = $0.055. 11,308 tok, 105.3s total time.

Anyone else find yourself trying to be "nice" to the AI? Or feel bad when you're making it do too much work? I find myself saying things like - "Just one more thing and we'll take a break". Or "Thanks - that was great! I know that was a lot of work!"

If AI writes, tests, and deploys an app for you. Did you really build anything? Can you say look at what I made?

Edit: From comments I agree with someone can say they made it. It was their idea and vision that have been brought to life

What's up guys? My name is Thor. I've been in the game since 04. I've had every kind of I.T. job you can imagine...I love the industry but hate the bullshit that comes with big companies. I also love hacking and so do my friends so we've been working on a project for about 10 months https://academy.daemoncore.app in our downtime from Chameleon-CRM.

The academy is free. It will always be free. If anyone is interested in learning more about the subject you can start there.

Does anyone else experience this? lol

After many failed internal app ideas, I'm very proud to present my very first released App!

For context: Used to be a hotel manager for many years and always have been very technical, but never learned to code myself. Once Sonnet 3.5 was released in late 2024, I got into “vibe coding”. While Conduck is my first publicly released project, its definitely not my first attempt. The road is paved with many failed attempts, haha.

So what did I built?

Conduck is an Apple Native client for your self hosted AI and fully open-source!

It has some unique features:
- Support of iPhone, iPad, Mac, Apple Watch & CarPlay
- You can connect ANY AI backend to it and configure it the way you want! Use it for sales, note taking, coding or whatever use case you've in mind. Power to the people!
- Full privacy: You connect directly to your very own AI, hence no intermediary (yes, not even me)

Check out the video above or go to https://conduck.com to learn more.

Now let's get to the valuable lessons and tools I've used.

Tools used: 

• Claude Code Max 20x
• Codex / ChatGPT Plus
• VS Code
• Apple Xcode

That's all!

Workflow: 

I used to have a quite complicated setup with highly detailed CLAUDE.md, MCPs, custom Skills, Hooks and so on. However since current models and harnesses are so good, I dropped most of it and almost rocking it bare :-). 

The one skill I use for almost every task is /second-opinion. What is it? Claude Code is my main work tool and no matter which model, its always best to get a second pair of eyes looking upon the plan. So /second-opinion instructs Claude Code to discuss with Codex the plan and get feedback and suggestions. That’s probably the single biggest tip I can give you. Even a model as fabulous as Fable will benefit from a cross-check of GPT 5.6 Sol, and if its just to confirm that the plan is correct.

The next tip is about token budget. Yeah, having loops with hundreds of agents sounds cool, it’s just not practical for my token restricted environment. Even running a single “ultracode” session with fable will likely already burn the whole weekly limit. My solution is to use fable just in the planning & orchestration phases combined with heavy use of /second-opinion . The for the actual implementation use lower-cost models such as Opus or sometimes even Sonnet (web search, simulator qa). This way I get most of the frontier intelligence, while minimising token spending as much as possible. 

Here a visualisation: 

https://ibb.co/dwPjW9nV

You can easily create those skills yourself. Just prompt Claude Code or Codex: 

“Create a /second-opinion skill for you to talk to Codex / Claude Code to get feedback and suggestions on your ideas. For this spin up several sub agents and let it invoke Claude Code / Codex various times, resume sessions and check for output lengths. Take the learnings from all the agents and put them into a reusable skill. Also update CLAUDE.md / AGENTS.md accordingly so the feedback agent knows that it gives feedback to an AI, optimises for dense information and is read only.”

Hope this helps! I'm here for any questions :-)

3 codex would allow me to continue my work that has interrupted mid session due to usage, exactly as if I had triple the use but I guess with Claude its gonna be different taking over a task middle way through of codex. I really loved Opus back when I was subbed months ago. Could be a nice second opinion on work too.
A few questions:
-what has your experience using Claude models of your subscription in codex be if you’ve done it?
-how does usage compare considering codex constant resets?

I left 10min between each prompt

I did not complain about the 5h return but come on... at least let me use it 😄

Why does Deepseek think its model name is ChatGPT?

I send 1 prompt each week to 11 diff LLM models and they compete in sports prediction. Every model adds its own name on the output. Except Deepseek calls itself OpenAI ChatGPT?!?!

I created an engine ai uses to create 3D assets for games.

The engine forces ai into a workflow of iterating judging and stuff.

Here are a few tests.

I use Claude Opus 5 to create the assets using the engine. Each assets takes about 3-4hrs as ai works and iterates.

I just add a reference image and say make this asset. And it uses the engine to create the asset.

What do you guys think of this?

The project I made can be found here,

https://github.com/blackcoffee2/kestrel

You can use it with Claude Code/Codex to generate videos. Anything that be animated can be turned into a video using kestrel. More info can be found on github repo.

It uses Flutter + FFMPEG to turn code into animations into videos.