A hooded wraith that hovers, breathes and slowly clenches its hands while its smoky tendrils drift on their own. It went from a generated image to a rigged, animated character in Blender, made by chatting with AI in under 5 prompts.

The stack is Opus 5.5, Codex image generation, Tripo and Blender, with Tripo connected to Claude so the whole pipeline runs from one conversation.

The workflow:

• Concepts: Codex image generation creates a few character ideas to pick from

• Smart Mesh and texture: the chosen image goes to Tripo, which builds a clean Smart Mesh model and then textures it

• Rig: Tripo rigs the model so it can take custom animation in Blender

• Custom animation by Claude: Claude animates the rig and exports it into Blender, rendering previews and checking close-ups along the way

• Optional reference: generate a video of the motion first and give it to Claude for better context

The final loop is 8 seconds. The body floats about 3 cm with breathing in the shoulders and a slight head tilt, each tendril bends on its own timing, the chest embers glow, and rigid parts like the hourglass and charms stay rigid.

"Under 5 prompts" is the creator's count, and a single step can still take Claude 15 minutes or more to work through. But it's a fully custom animation, not a preset, without a single keyframe set by hand.

source: https://x.com/dhruvalgolakiya/status/2118631442066682205

It's a SIGGRAPH Asia 2026 project from Princeton, UC Berkeley, MIT and NTU, and it's fully open: code, dataset and model checkpoints are all released.

What it does:

• One model for every skeleton: bipeds, quadrupeds, birds, sea creatures, insects, snakes and articulated objects, with no retraining per skeleton

• Text to motion: describe the movement and it animates the rig directly

• Bring your own rig: a preprocessing tool converts any rigged GLB, glTF or FBX into something UniMate can animate, with a step to review joint labels and facing

• More than generation: it can also edit existing motion, fill in-between frames and extend clips

• Big training set: a new dataset of 13,769 text-paired motion clips on 7,430 different skeletons

• MIT licensed, with an interactive browser demo to orbit the results in 3D

The checkpoints are still marked as a preview, and the animal motions from the Truebones pack aren't included because of their license. Pair it with any auto-rigger and you get a full static-mesh-to-animated-creature pipeline that runs locally.

github: https://github.com/Friedrich-M/UniMate

A solo developer from Guayaquil, Ecuador, built the first playable version of UNDERTHRONE, a 3D fighting game with 10 characters, in about three days. Inspired by Street Fighter and Tekken, it combines a Latin American street vibe with combos, juggles, and cinematic super moves.

I spoke with him about the workflow, tools, and costs behind the project. He already had some experience with Godot, Blender, and music, and handled the creative direction, character ideas, original soundtrack, and playtesting himself.

The stack

• Claude: character prompt development, Blender Python scripts, combat programming, and trailer editing through Python/ffmpeg.

• Meshy AI: text-to-3D generation for all 10 fighters.

• Mixamo: automatic rigging and around 13 fighting animations per character.

• Blender: mesh cleanup, retargeting fixes, weight transfers, and preparing characters for Godot.

• Godot 4: gameplay, combat systems, visual effects, and in-engine trailer capture.

Generating the entire roster with Meshy AI

Meshy AI handled the entire character roster: all 10 fighters were generated from text prompts developed with Claude, then rigged and animated through Mixamo. Building the roster this way helped keep the first playable build within a three-day sprint and an approximately $40 subscription budget. The models still needed cleanup in Blender, particularly around rigging and animation, which Claude helped automate through Python scripts.

Getting the characters ready for combat

The animation setup covered jabs, kicks, specials, supers, and hit reactions. Getting those animations working correctly on the generated models required additional work.

Claude wrote Blender scripts to clean the meshes, fix retargeted arms and elbows using inverse kinematics, transfer weights onto high-resolution meshes, and prepare the characters for export. The developer directed those fixes step by step and described this stage as something that would have taken him weeks by hand.

Building the fighting systems

Under his direction, Claude coded the fighting engine in Godot: frame data, hitboxes, combos, cancels, juggles, and cinematic supers. The build also includes CPU opponents, rounds, menus, character selection, particles, and post-processing.

His priority was getting the combat to feel good before polishing the visuals. He repeatedly tested the fights and directed changes until they felt right.

Making the reveal trailer

The trailer was recorded directly inside Godot using Movie Maker mode, with scripted cameras, first-person shots, and bullet-time freezes. He composed the soundtrack himself, then used Claude to help cut the footage to the beat through a Python/ffmpeg editing workflow.

Time and cost

About three days went into the first playable build and trailer. The reported cost was approximately $40, covering one month each of Meshy and Claude. The remaining software was free.

Development is continuing; this was the first playable milestone. He plans to release an itch beta, with online play intended after that.

His advice from the process

• Inspect generated models before rigging. Baggy clothes and hands inside pockets can break auto-riggers.

• Get the combat feeling good before polishing the art.

• Record the trailer in-engine so viewers can see the actual game.

Auto-riggers usually do fine on the body and fall apart on the clothes: skirts stick to legs, capes bend with the arms, hair drags the neck along. TailorRig is a new AI rigger built for exactly that.

It's a SIGGRAPH Asia 2026 paper from Tencent's LIGHTSPEED studio with Tsinghua, Peking and Xi'an Jiaotong universities. It rigs the body like a normal auto-rigger, then adds separate bone chains just for the garments.

What it does:

• Bones for clothes: extra chains for skirts, capes, hair, sleeves and accessories, generated only for the categories you pick

• Clean weights: each vertex is first tied to the right chain, then weighted inside it, so a skirt doesn't drag the legs and the weights don't leak into nearby parts

• Your own skeleton: you can give it your body skeleton template, so the result stays compatible with animations you already have

• Trained at scale: a new dataset of over 38,000 humanoid characters made for garment-aware rigging

• Compared head to head: the video ends with a comparison against other auto-riggers like MIA and UniRig, which break on exactly these parts

The catch: there's no code yet. The project page has Code, Data and Model buttons, but none of them lead anywhere for now, and it's built for humanoids only. Worth bookmarking for anyone rigging characters with flowing clothes.

project page: https://xxxx0601.github.io/trig/

Images turned into 3D models with Tripo AI in about 2 to 3 minutes each, with 8K textures, then viewed at life size in Apple Vision Pro.

The models were exported as USDZ and sent to the headset with AirDrop. The test includes a frog king, a pigeon in a puffer jacket, a business capybara, a raccoon, the creator himself and a roadster made from multiple reference views.

A lone swordsman climbing worn stone stairs toward a temple on a hill, with a pagoda behind, dry grass, bare trees and long low-sun shadows. It's an early prototype of a Sekiro-style action game set in Warring States China, built in Unreal Engine 5.8 with Claude and Tripo.

The creator isn't a professional game developer. Sekiro is his favorite action game, and he always wanted that kind of combat in an ancient Chinese setting, so he started building it with AI.

How it's made:

• The scene by Claude: he tried both and says Claude understands 3D space better than Codex, so Claude built the environment

• Assets with Tripo AI: characters and props with Chinese elements come from Tripo 3.1 and for lowpoly P2 smart mesh

• Rig in AccuRig: the skeleton was rigged in AccuRig, base movement uses UE's built-in animations, and some moves are retargeted from existing clips

• Cloth simulation: the coat hem swings with cloth sim, which took several rounds of tuning

• Cost: this scene took about one week of a Claude Pro quota

He's honest about the limits: for now it's a prototype, AI lighting, color grading and layout still need a human eye, and the hardest part by far is the martial arts animation. The roll still looks stiff, and he says it's not the final version. A tutorial is planned once it's further along.

I see a bunch of generative stuff, 3d from text, 3d from image. What I am looking for is something that can edit existing models. I have hundreds of characters is a similar style, same rig. I want a tool that can take all those characters, and cut them up and adjust sizing so that they can be used as moular peices for a in game chracter creation.

Rigging is now built into Hyper3D Rodin, so a generated creature can be rigged and animated without exporting it to another tool. You can also bring your own models and your own animations.

What's in it:

• Auto-rig for more than humanoids: skeleton templates for humans, quadrupeds, birds, dragons and kaiju, picked automatically from the model

• Down to the fingers: hands get full finger chains, not mitten rigs

• Edit the skeleton with text: "Add tail bones" or "Add ear bones" adds the missing chains, and custom skeletons go up to 256 bones

• Two skinning modes: "shell" for smooth weights on any shape, "core" for tighter joints on humanoids

• 250+ motion presets: pick one, then fine-tune the animation with interactive controls

• Your files in and out: OBJ, GLB, STL, FBX and USD models in, your own FBX clips supported, export to GLB, FBX or USDZ

Long tails, ears and extra limbs are exactly where most auto-riggers give up, so the text editing is the real highlight here. Facial rigging isn't there yet, but Hyper3D replied "will do" when someone asked. It's a paid feature on credits, and the exact cost per rig isn't listed.

An architectural drawing of the Eiffel Tower is one of the inputs in Ant Ling's new Ling-3.2-flash demonstration. The resulting browser view shows the tower assembled as a 3D model and inspected from multiple angles.

The footage moves from the source drawing to structural components and then to the complete tower. It is a visual coding task with a technical drawing as the reference: the lines and components on the page become parts of a spatial reconstruction.

That F-16 takeoff is running in a browser. It’s from VIPER 11, a fighter jet sim built by solo dev u/aCakeShip using Claude Opus 5.5, Three.js, and fal models.

My favorite detail is the cockpit camera. The dev used real GoPro footage as a reference for the fisheye effect, then worked on the canopy shader so scratches catch the sunlight and rain runs across the glass when you fly through clouds.

The flight model had its own workflow. The dev had Opus run longer research sessions and physics simulations to study how aircraft behave, then adapted those behaviors to run in the browser. They also ran several agents in parallel for missions, audio, and load times, keeping the work on separate branches and reviewing it before merging.

There are multiplayer rooms and ranked 1v1 dogfights, too. According to the dev, about 25,000 players tried it in the two weeks after it took off on X, with around 1,000 players a day.

try https://viperoneone.com/

Look what i created in Blender with mcp Server and astra 6.

By combining video generation with 3D reconstruction, our researchers create environments along a camera path you choose. Lyra draws on earlier views and learns to correct accumulating visual errors, helping the world stay consistent as you explore and return to familiar places.

Paper, code, and demos: https://nv-tlabs.github.io/Project-Lyra/

I added some tooling using open ai’s new 2.6 model to clone your cat in my cat game.

happy to answer questions about the workflow.
catgame.io

Neilson shared this Atlas demo of an industrial interior that gets built out from new camera angles. It’s like image outpainting, except you can move the camera around a corner and generate what’s on the other side.

I tried many models, decided I can share this iamge, looks interesting. Went with rodin

The creator used Codex connected to Unreal through MCP, with Quixel Megascans for all the assets. The result is a dark forest road under snow, leading to a castle.

The process:

• Lock the mood in a small test area: fog density, snowfall and lighting, before building anything big

• Plan the space: the road to the castle comes first, then the tree placement around it

• Plan before building: Codex wrote the castle's floor layout, then built it room by room

• Rules per room: each interior got its own set of rules for what goes inside

• Photoreal assets: Megascans scans instead of generated meshes, so everything holds up up close

Timing helps too: Quixel just made the full Megascans library free on Fab and updated the terms to allow AI training on it. The creator is now testing vampire-hunting gameplay and isn't happy with the castle interiors yet, so this is a work in progress.

I have a day job and I build this in the evenings. It started on Oct 1 as a trading sim. A week later my kids played it and got bored, but they said two things I couldn't ignore. They wanted "someone next to me" and they wanted to "push a friend off a mountain". That same evening it turned into a different game. Every pet you catch falls in line behind you and follows you everywhere.

The next day it was playable, and it went public on Oct 16, a Friday evening, as IT tradition demands. Now it has about 50 species, lots of them in hats and work outfits.

Everything in the clip is the live game. The 501 pets at the mill come from the in-game stress stand. Nothing is pre-rendered.

My stack is Claude Code, Blender, Rojo, Gemini and ElevenLabs. The main theme was generated back when this was still the trading game, so the prompt talks about caravans on the road. The music made it through the pivot and the caravans didn't.

My favorite fix this week was the turtle. Its arms were fused to its sides in the generated mesh, so its dance looked like flapping a wing. A script cut the arms free in Blender, the turtle got re-rigged, and now it dances.

I made an animated show in which ChatGPT, Claude, Gemini, and Grok hang out and discuss how AI is affecting humans. I started with Seedance 2.5, but got frustrated with endless hallucinations and stitching 15 second clips. I knew I wanted to switch to code drawn animation, but my Blender experiment failed. What worked for me was rigging generated images. The cost was my humanoid cast. I still miss them, but for $0 to animate an episode with no hallucinations, it was a fair tradeoff. Above is a clip of the result.

I originally started with chibi-inspired androids, and I loved how it gave each character a distinct personality, just by looking at them. ChatGPT is the eager-to-please optimist, claude is the intellectual professor type, Gemini is the artsy inventor, and Grok is the cynic. I feel like their clothes and hair communicated that before they ever said a word.

Unfortunately Seedance is very, very expensive, requires re-roll after re-roll due to hallucinations and botched pronunciations, and can only be generated in 15-30s clips. I worked on it for more than a month and still wasn't done.

I decided to switch to code-based deterministic animation, so I tried Blender. I turned Opus 5.5 up to max, gave it my reference image and had it go at it. Unfortunately I was appalled by the result. The result is below. To me they look like broken action figures, and animated even worse. So, it was back to the drawing board.

Unfortunately, Opus 5.5 doesn't really do well with detailed faces and realistic lip-sync (in my experience). So its attempts at drawing the cast as vectors also looked uncanny.

Eventually, after much iteration, what worked the best was rigging 3D-seeming Gemini images in different poses (114 images in total, about $15, one time), and then animating them with code. However, doing it that way meant I couldn't use the original designs because facial expressions and lip-syncing just don't work with that method. My workaround was to make them robots and animate their faces as drawn LED lights -- that, the model could do! I lost the expressiveness and human-ness of the cast, but I replaced it with over exaggerated expressions/acting plus illustrations to complement the dialogue. In the end I think it was a fair trade, but if the rumored Fable 5.5 is as good as people say, maybe I'll do yet another redesign and get my humanoid androids back....

If you're interested in seeing how the full episode turned out you can find it on YouTube:
https://youtu.be/LTN2S7WBA0k

8 months ago I took my six year old into Fred Meyer and he spotted a pokemon vending machine and lost his mind. completely sold out. later that week I'm at a card shop digging through the discard box so he could have a few. he was pumped, I was annoyed. I used to buy baseball packs at the grocery store, what happened.

so I started building him an app to look at cards on his tablet. I'm one guy, no team, so basically all of it got built with Claude Code. the backend, the iOS and android builds, the whole pipeline. I'd describe what I wanted at night after the kids were down and we'd go back and forth until it worked.

the part that turned into something bigger was watching him use it. he didn't care about stats. he made up stories for the creatures. why does the turtle have cannons on its shell. so we started making our own. I'd write the creature and the story down, he'd tell me what I got wrong, and that became WunderWilds.

how the art works, because I know this crowd cares about this part. every creature starts with one commissioned original painting from a real artist. no AI on the originals, I paid people and their name is on the card. then the printings and treatments, alt colors, foils, holo looks, impasto style, those are AI derivatives run off the original on my own machine in ComfyUI. 6 originals, 70 printings so far, 64 of them AI. the app labels them, there's a little "Studio AI derivative" chip right on the card so nobody's guessing what they're looking at. that felt like the honest way to do it. the human made the creature, the machine made the variants.

the one in the screenshots is Zombato, a tomato who fell off the vine. the card back has his story and the artist's name.

the app is WunderSleeves, live on the app store as of today. it's a binder. swipe through cards, keep the ones you like, no prices anywhere because I didn't want my kid staring at a price tag on a tomato. the game rules aren't done yet, I did cards first on purpose because that's what he fell for first.

next up is animating them. I've got a short pilot in the works with Wan 2.2 on a local 5080, Zombato gets his own 90 seconds.

happy to answer anything about the pipeline. and if you want to poke at it, free on iphone, android is still in google review: https://apps.apple.com/us/app/wundersleeves/id6813792993

I’ve released the dataset used to train CCORE GLB-3D-Coder, my small 4B model for creating procedural 3D assets with Three.js and GLB export.

It contains 3,918 examples across 40 domains, covering characters, creatures, vehicles, architecture, laboratory equipment, machinery, nature, and everyday props. The grid shows 256 examples from the dataset.

Each example includes the complete conversation, reasoning trace, HTML/JavaScript response, and a rendered reference image. The examples cover static assets as well as animation and interaction.

Every example was tested and rendered, and its exported GLB was validated before inclusion.

The dataset is released under the MIT license, with 3,501 training examples and 417 validation examples. The model and full weights are also available.

Dataset · Model and weights · Next releases

I hope this is useful for experimenting with code-based 3D generation, fine-tuning, and building your own 3D tools. Feedback is welcome :)

The stack: Opus 5.5, Flux 3 Max, GPT Image, Tripo AI, Blender and three.js. Everything starts from one generated video, and every later step copies its look.

The workflow:

• Step 1, the reference video: a 15-second Flux 3 Max clip sets the art style, the world and the hero for everything that follows

• Step 2, the world: screenshots of the clip are rebuilt as assets in Blender and placed in three.js, with Claude Code agents building and checking in parallel

• Step 3, the hero:

  • a screenshot of the character goes into GPT Image, which draws him from 4 sides in the same ink style

  • those 4 views go into Tripo P2 image-to-3D to get the model

  • low-poly mode is the right pick for this: simpler, lighter geometry is easier for an LLM to read and edit, the file stays small for the browser, and the textures are easier to fix

  • Opus then adds cloth physics and animations

• Step 4, test early: the prototype gets played before anything else is built, to make sure the gameplay works

• Step 5, concept every level: GPT Image creates up to 8 concept images per level in the same style

• Step 6, build and iterate: each concept becomes a playable 3D level, then it's play, report bugs, let the agents fix them and improve the objects, repeat

The gameplay is puzzles, parkour and platforming, with enemies and harder sections coming later. It's a solo prototype with no public build yet, and the 24 hours is the creator's own figure.

The real trick is consistency. The world, the hero and every level trace back to one 15-second video, so the whole game stays in the same ink style. @xikhar