# Choosing an AI builder for XR > Compare prompt-to-XR tools, AI-assisted engines and spatial design tools. Check device support, editable output and testing before you choose. Graspable, 22 October 2026 · Guides Source: https://graspable.dev/blog/choosing-an-ai-builder-for-xr AI builders for XR exist. The useful question is which one can build, test and deliver the experience you have in mind. A browser scene, a native Quest game, a phone AR experience and a glasses companion app have different requirements. For a description-to-project workflow, consider Graspable. For rapid Android XR experiments, look at Google's XR Blocks with Gemini. For an established native development workflow, consider Unity with its AI tools. PlayCanvas suits teams working in a browser-based 3D editor; ShapesXR focuses on spatial design and prototyping. This guide is published by Graspable. We checked the other products' official documentation on October 22, 2026. The comparisons below describe their documented workflows, not a head-to-head speed or quality benchmark. ## Start with what the audience will open Write down the device, how someone gets into the experience, and what they need to do there. - **A link opened in a headset:** check WebXR support, the available immersive modes, hands and controllers on that particular browser. - **An installed headset app:** check the engine, signing, packaging and distribution requirements for the target device. - **A link opened on a phone:** ask which tracking method it uses. Camera access, image tracking and detecting a bare tabletop are different capabilities. - **An app for AI glasses:** name the glasses. A camera-and-audio companion, a small display app and a room-scale spatial app are different products. Check the manufacturer's SDK and distribution rules. “Works on mobile” does not tell you whether a person can place something on their kitchen table. “Works on Quest” might mean a flat page in its browser. Ask to see the interaction you intend to ship. ## Which workflow fits? Distinguish an AI builder that edits your application from an asset generator or an AI character inside the finished experience. You may need all three, but a generated model or conversational character does not by itself provide the application, testing and delivery workflow. ### Describe an experience and keep an editable project A dedicated AI builder can combine a coding agent with project templates, preview, checks and publishing. Evaluate the whole loop: make the first scene, change an interaction, find a problem and repair it. A good first screenshot tells you little about the fifth change. Check whether you receive ordinary project files, which AI accounts are supported, what runs locally, and what happens when a build fails. “Export” can mean source code, a rendered video or an installed application; establish which one you need. ### Build WebXR in a cloud workspace [Replit's VR guide](https://replit.com/build/vr-app-builder) documents prompt-driven WebXR development and testing a deployed URL in a headset browser. Include it when evaluating cloud builders; do not assume a general app builder can only make flat interfaces. Compare its workflow with [Graspable's local XR workflow](https://graspable.dev/compare/replit.md) using the same scene and device. ### Create a world inside an immersive platform [ENGAGE XR documents voice-driven world creation](https://engagevr.io/build-immersive-vr-worlds-with-your-voice-generative-ai-on-engage-xr/), including generated models, images and skyboxes. Consider that workflow when the experience belongs in its platform. If you need a standalone application, establish the code, hosting and distribution requirements separately. ### Try a spatial idea quickly with XR Blocks and Gemini [Google's Vibe Coding XR workflow](https://research.google/blog/vibe-coding-xr-accelerating-ai-xr-prototyping-with-xr-blocks-and-gemini/) uses Gemini, templates and XR Blocks to build interactive WebXR prototypes from prompts. Google documents desktop simulation, public sharing and interaction on Android XR. It is worth evaluating when your immediate goal is to test a spatial idea on that platform. Check other target devices separately. ### Work inside an existing engine [Unity's AI tools](https://unity.com/features/ai) include an in-editor assistant, official coding-agent plugins and an MCP connection through its CLI. This is a practical route when your team already works in Unity or needs its native development workflow. The AI connection does not remove the need to configure the project, build target and device tests. If you already have a substantial Unreal Engine project, assess an agent against that project before moving it to another stack. Rebuilding working content just to use a different prompting interface has a cost. ### Use a browser-based 3D editor with an agent [PlayCanvas supports WebXR](https://developer.playcanvas.com/user-manual/xr/), and its [Editor MCP server](https://developer.playcanvas.com/user-manual/editor/mcp-server/) lets an external AI assistant edit projects and inspect the running result. Consider it when you want its visual editor and engine, with an agent connected to that workflow. Compare the editor, source workflow and testing tools as well as the AI integration. ### Design interactions together before implementing them [ShapesXR](https://www.shapesxr.com/product) provides spatial design, interactive prototyping and real-time presentation, with a Unity integration. It is a useful candidate for agreeing on layout and interaction in a headset before production development. Evaluate the handoff to your delivery stack as part of the choice. ## Give each candidate the same small job Use a task close to your actual product. For example: > Build a tabletop exhibit with three objects. Let me pick one up, reset its position, and open a readable information panel. Animate one object. Include a way to leave the immersive experience. Then make the same follow-up request in each tool: change the reset behavior while preserving the animation. Record the initial setup, manual repairs, result and device used. Keep time spent signing in or installing engine components separate from generation time. Before committing, check: 1. **Input:** can the intended audience use the experience with hands, controllers or touch? 2. **Tracking:** does placement stay where expected when you move? Does it need an image target? 3. **Editing:** can you change the animation, materials and logic after generation, including by hand? 4. **Verification:** do checks exercise the interaction, or only confirm that a page opens? 5. **Performance:** is it comfortable on the actual device after several minutes, with your intended assets? 6. **Delivery:** can another person open it, allow permissions, use it and exit without your help? 7. **Cost:** what covers the builder, inference, assets, hosting, engine tools and distribution? Use a headset emulator early to find mistakes. It does not establish comfort, hand-tracking quality or performance on the hardware. Keep the working project and the recording so you can repeat the test after later changes. ## Doing this in Graspable [Graspable](https://graspable.dev) is a desktop AI app builder for XR on Windows, macOS and Linux. Its agent edits project files on your computer. Web projects use React Three Fiber and WebXR, with an emulated headset, build-and-load checks and replay of configured headset tests. See [how those checks work](https://graspable.dev/blog/how-graspable-checks-its-own-work.md). Start with [React XR](https://graspable.dev/templates/react-xr.md), ask for the exhibit above, then [record a headset test](https://graspable.dev/docs/xr-tests.md). For an existing example, try [Signal Garden](https://warm-island-262.graspable.cloud/), an animated rescue film and puzzle. Its phone-browser AR mode uses an image tracking mat; it does not detect a bare table. Its headset passthrough path and the separate native phone project use different placement workflows. Native Unity, Unreal Engine and visionOS templates require the corresponding tools and target setup. Read [Native XR](https://graspable.dev/docs/native-xr.md) before choosing them. Local building with a supported AI account is free; provider usage and limits still apply. [Plans](https://graspable.dev/pricing.md) explain premium templates, publishing and Credits. ## Make the decision from the working result Choose the tool that completes your actual interaction, leaves the project editable and reaches your audience's device at an acceptable cost. If it only meets part of that brief, document the remaining work before treating a prototype as ready to ship. ## Sources - [Google Research: Vibe Coding XR and XR Blocks](https://research.google/blog/vibe-coding-xr-accelerating-ai-xr-prototyping-with-xr-blocks-and-gemini/) - [Unity: AI tools and agent connections](https://unity.com/features/ai) - [PlayCanvas: WebXR support](https://developer.playcanvas.com/user-manual/xr/) and [Editor MCP server](https://developer.playcanvas.com/user-manual/editor/mcp-server/) - [ShapesXR: design, prototyping and development](https://www.shapesxr.com/product) For a closer look at an individual workflow, see the [Graspable comparisons](https://graspable.dev/compare).