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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Mika Flowers’s Oniria began as an attempt to make DEV articles feel like a place readers could explore. The turning point was practical: precise requests such as “Put this shelf against that wall, slightly left of the pavilion, rotated toward the center of the room” were difficult to translate into coordinates and prompts. Instead of refining the prompt, Flowers built a development-only marker editor inside the running 3D world, so layout could be placed visibly and saved as structured data.
Flowers describes the project in a September 27, 2026 DEV Community article. The account is a build retrospective, not an independently verified evaluation of coding agents or a measured performance study.
What Oniria is—and what it is not
Oniria: The Living DEV Library is an experiment in presenting live DEV content as a walkable 3D library. Flowers describes six rooms: Featured, New Arrivals, Topics, Creators, Search, and Archive. It is not presented as a general-purpose website editor or as a comparison of commercial level-editing tools.
The project’s architecture separates the articles from the world that organizes them. DEV supplies live content data; Sanity stores world configuration and author-defined structure; Three.js renders the environment and interactions. The reported stack also includes Next.js 16, React 19, TypeScript, next-sanity, the DEV/Forem API, Vercel, and GLB environment and architectural assets. These are details from Flowers’s account, not an independent audit of the running application.
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Flowers says the project grew from a Sanity-backed dream journal into a 3D environment and relationship map. The initial abstract spatial graph became visually crowded. Moving to six recognizable destinations made the content easier to approach as a place: readers could imagine browsing topics, creators, recent arrivals, or an archive rather than interpreting a dense diagram.
Why prompts stopped being enough
A natural-language instruction can convey intent without specifying an unambiguous position in a 3D scene. “Slightly left” depends on the viewer’s orientation; “toward the center” depends on the room’s shape and the object’s rotation. Flowers found that resolving such requests through configuration, coordinates, screenshots, and repeated prompts was cumbersome.
As Flowers put it, “A model can satisfy the semantic meaning of a request while completely missing the visual intention.” A shelf might be in a plausible place according to a prompt while still blocking a route, facing the wrong way, or looking wrong in the rendered room. The response was not another wording trick: “The solution wasn’t a better prompt. It was a better tool.”
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How the in-world marker editor works
Rather than arrange every object by editing coordinates outside the scene, Flowers added a development-only spatial authoring workflow. While walking through the live Three.js environment, the author can place markers at the intended locations of objects or zones. Each marker records:
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- A district identifier
- X, Y, and Z position
- Yaw, width, and depth
The marker is saved as a libraryLayoutMarker document in Sanity, then consumed by the renderer. This gives the layout a persistent, editable representation while keeping the placement process tied to the visible world. Sanity’s documentation describes Studio as an open-source, real-time collaborative content workbench with developer-defined content models and a customizable editing environment; that context helps explain why structured documents can hold world-authoring data, but does not independently validate Oniria’s implementation.
Flowers gives one example marker: label R1-P04, room slot 1, district latest, x 13.687, y 0, z 11.998, yaw 0, width 4.5, and depth 0.72. Those are values from a particular authored marker, not recommended settings or performance measurements.
The important workflow difference is that placement becomes inspectable and repeatable: the author can stand in the scene, see what a placement does in context, save its defining values, and let the renderer use them. The article describes that process for Oniria; it does not establish that the editor is a public feature or a general-purpose tool.
What the build taught Flowers about 3D authoring
Make authored assets the visible source of truth
Flowers says a model generated procedural wall geometry even though the request was to use supplied wall assets. The later approach made authored GLB walls visible in the scene while retaining primitive geometry for invisible collisions and structural helpers. The memorable instruction was: “DO NOT GENERATE YOUR OWN ASSET FOR THE WALL.” The distinction matters: simple geometry can be useful behind the scenes, but it should not silently replace the asset the author intends people to see.
Judge the rendered result, not just the implementation
A washed-out scene initially looked to Flowers like a problem caused by overlapping lights and bright materials. Continued investigation led to UnrealBloomPass and its threshold as a larger contributor in this particular case. That is Flowers’s debugging account, not a universal diagnosis for washed-out Three.js scenes. The broader practical lesson is to inspect the final render and trace the image pipeline rather than assume the first plausible cause is the actual one.
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Spend detail where interaction happens
Flowers reports that early large shelf fields and remote cover textures brought flicker, unnecessary texture work, excess geometry, weaker GPU performance, visual clutter, and harder navigation. The response was level of detail based on distance and use:
- Nearby shelves: retain covers, readable metadata, and interactions.
- Mid-distance shelves: simplify their appearance.
- Distant structures: reduce them to architectural mass.
Flowers summarizes the approach as “Full fidelity only where interaction matters.” The article gives no GPU model, frame rate, benchmark, or controlled before-and-after measurement, so these are reported design observations rather than quantified results.
Inspect existing architecture before changing it
In a Living Shelves example, Flowers says an agent inspected the existing architecture and found that a capacity restriction—not a missing reusable architecture—was the obstacle. That episode illustrates why understanding the current system can be more useful than immediately replacing it. It remains a single account and does not establish how often agents find or miss such constraints.
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Let prototypes teach you—even when you discard them
Flowers describes abandoning several project directions along the way and argues that cheap exploration made it easier to learn from ideas and move on. That is a personal conclusion about this build, not a measured claim that prototypes always improve productivity.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the account establishes—and what it leaves open
Flowers’s article, dated September 27, 2026, offers a detailed account of the project’s design decisions and workflow. It does not independently verify the application, repository behavior, performance, or coding-agent claims. The article labels the live project and demo video “TBA,” so it does not establish a publicly available working demo. Its most concrete contribution is the described shift from prompt-driven placement to an in-world authoring workflow whose spatial markers are saved as structured Sanity documents.
Sanity’s Studio documentation explains the platform’s developer-defined content models and customizable editing environment. Separately, Sanity’s Guest Author Program terms dated May 18, 2026 list bounties of $250 for short-form content and $500–$750 for long-form or video content, subject to pitch, acceptance, and program conditions. Those terms say nothing about whether Flowers applied, qualified, was accepted, or was paid.
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