
Rina
@irinatoxi • 2,847 subscribers
Building cool things with AI so you don't have to imagine them
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The most dangerous GPT-6 Astra demo I’ve seen has nothing to do with code. I typed “make me a woman” and it gave me an actual character inside Blender. Not a render. Not a concept image. A full 3D asset with a body, face, hair, materials and proportions you can rotate, inspect and keep editing. That is where this stops feeling like another cute AI trick. Character modeling is exactly the kind of work where bad anatomy, dead eyes, plastic skin and ugly hair expose every shortcut immediately. And Astra is already getting close enough that “AI can’t do real 3D character work” is starting to sound like a sentence with a very short shelf life.
Rina220,055 views • 2 days ago

Grok 4.5 just turned Blender into a conversation. Instead of manually importing assets, fixing rigs, placing armies, adjusting cameras, and debugging objects that face the wrong direction, the user simply tells Grok what to change. It builds a medieval battlefield from existing 3D assets, adds horses, knights, a castle, siege machines, trees, animation paths, cameras, and even spatial audio. The impressive part is not that it gets everything right. It absolutely does not. Models spawn upside down, characters face the wrong way, and the scene needs constant correction. But Grok keeps editing the actual Blender project instead of generating another fake 3D image and hoping nobody notices. It is replacing a suspicious amount of the boring work they had to do before the skilled part even started.
Rina1,088,846 views • 1 month ago

A scene like this could easily be a $1,000–$3,000 3D visualization job. GPT-6 Astra generated the full data-center environment inside Blender: server racks, cooling hardware, overhead piping, cable infrastructure, and a walkthrough through the finished space. That is where AI 3D gets financially interesting. You are not saving $20 on a stock image. You are potentially deleting thousands of dollars of modeling and visualization work before a client even sees the first draft. The render is cool. The invoice it kills is cooler.
Rina66,901 views • 8 days ago

The scary part about AI in CAD is not that GPT can extrude a shape. It is that it can now build a mechanism where multiple parts actually have to agree with each other. Using GPT + Autodesk Fusion MCP, this project turns into a mechanical iris assembly with a base plate, eight overlapping blades, a drive ring, a cover, mounting holes, and relationships between the components. One blade is easy. The annoying part is repeating it around the same center, keeping every pivot aligned, fitting the mechanism between the surrounding plates, and making the whole assembly stay coherent as more geometry gets added. That is where MCP starts getting interesting. GPT is no longer treating Fusion like a place to dump some 3D geometry. It is working inside the actual CAD structure, where components, relationships, repeated parts, and the assembly itself all matter. That is a much bigger deal than text-to-3D. Because once an AI agent can reliably build and modify mechanisms instead of isolated shapes, a surprisingly large chunk of mechanical CAD starts looking like something you describe, inspect, and correct rather than model feature by feature.
Rina32,398 views • 27 days ago

The scary part about AI in CAD is not that it can draw a part. It is that it can now understand a messy engineering project well enough to search it, isolate the right components, change their parameters, and reorganize the whole thing from plain English. This guy is working inside Autodesk Fusion and asks the AI to create a complex geometric structure, find specific fasteners inside a large assembly, hide everything else, change dimensions across different screw sizes, and then rearrange the hardware into entirely new layouts. No manually hunting through the browser tree. No opening fifty components one by one. No “which M12 bolt was that again?” The model is treating the CAD file less like a drawing and more like a database it can reason over and modify. That is a much bigger deal than text-to-3D. Because once MCP-style agents can reliably understand what is already inside a real engineering project, the boring half of CAD work starts looking suspiciously automatable.
Rina33,421 views • 1 month ago

This is much worse for 3D artists than another AI image generator. Claude takes one architectural reference, connects directly to Blender, and starts rebuilding it as an actual editable scene. It blocks out the buildings, matches the camera, adds materials, vegetation, lighting, and then renders the result. The interesting part is not the first generation. Claude inspects its own render, notices the composition and lighting are wrong, then goes back into Blender and keeps changing the scene. The final result is still rough. The materials look basic, the geometry needs cleanup, and an experienced artist would make it far better. But AI is no longer producing a flat image and pretending it understands 3D. It is operating the software, judging its own work, and iterating inside the real project. The “AI cannot do their actual work” argument is getting harder to defend.
Rina34,431 views • 1 month ago

The interesting part about GPT in CAD is not that it can make a shape. It is that through MCP, GPT can work directly inside Onshape and turn a plain-English description into actual CAD geometry you can keep editing. In this case, the model builds a radial mechanical part with a central hub, repeated ribs, an outer ring, and a full pattern of mounting holes, all inside the real Onshape document. There is no fake “3D-looking” render hiding the hard part. The geometry exists in the CAD workspace, can be rotated, inspected, modified, and used as the starting point for the next iteration. That changes the workflow from manually clicking through every feature to describing the structure, letting GPT build the first pass, then correcting what matters. Once MCP gets reliable enough, the boring part of CAD starts looking less like modeling and more like supervising.
Rina16,772 views • 29 days ago

AI in CAD just went from “make me a part” to “build me the damn machine.” Using Autodesk Fusion MCP, the agent is working inside a real mechanical assembly with a chassis, shafts, gears, bearings, brackets, repeated hardware, and multiple components that all have to stay aligned with each other. That is a completely different problem from generating one clean 3D object. You can inspect the assembly from different angles, isolate sections, dig into individual joints, and keep working on the same engineering project instead of starting from another prompt-generated blob. The important part is not that AI can create geometry anymore. It is that it can operate inside the structure of a real CAD project where every component depends on what is around it. Once this gets reliable, a lot of mechanical CAD starts looking suspiciously simple: describe the system, inspect what the agent built, then tell it what to change.
Rina14,154 views • 26 days ago

Blender tutorials are about to age very badly. In this demo, Kimi K3 gets two character references and a plain-English request. Minutes later, it builds the first version inside Blender. The user asks for a better horn, Kimi edits the same scene, and the character starts moving. This is not another AI tool generating one lucky image. It is working with an actual editable 3D project, then changing the geometry after feedback instead of restarting from zero. It still needs human direction, because the first result is rarely the good one. But blockouts, repetitive edits, Blender Python, and basic iteration are becoming a conversation rather than hours of clicking through menus. Kimi K3 + Blender MCP is basically turning 3D modeling into: describe it, inspect it, complain about it, and let the AI fix it.
Rina19,092 views • 1 month ago

Mechanical CAD might be one of the first jobs MCP quietly wrecks. This guy connects an AI agent to Autodesk Fusion, gives it the dimensions for a snap-fit brick, and basically stops modeling. The agent builds the actual CAD part, adds the studs, hollows the underside, calculates the wall thickness and center support, then modifies the real Fusion model when asked. Then it checks the geometry and rounds the exposed edges. This is not text-to-3D. This is AI operating Autodesk Fusion like a junior CAD engineer. If this gets reliable, memorizing every tool in Fusion starts looking a lot less valuable than knowing what the part actually needs to do.
Rina14,531 views • 1 month ago
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