GPTGTA
A GPT-native top-down browser crime sandbox: tilesets, map editor, vehicles, pedestrians, collisions and mobile controls.
I build GPT-native prototypes, playable web runtimes, memory layers and post-feed internet concepts.
This site is the world map: the clear place where all projects, artifacts and canon layers connect.
Live worlds, hidden systems, save hubs, narrative engines and theory layers.
A GPT-native top-down browser crime sandbox: tilesets, map editor, vehicles, pedestrians, collisions and mobile controls.
Personal digging world, Brownling mascot layer, and the place where shared Brown Links are dug up.
A future social rediscovery platform where artifacts are buried, dug up, re-dug and tracked through provenance trails.
A GameCube/VMU-style save hub for project slots, links, ideas, prototypes and AI-native workflows.
A memory layer for loot-based games played with GPT: builds, gear, DPS, progress, run notes and continuity.
Turns AI chats and prompts into replayable anime/JRPG-style skits with characters, branches and answer cards.
An adult resolver roguelite experiment where image batches become encounter progression and run pressure.
Ambient Era Canon: coherence semantics, chromatic computing, humane AI, post-smartphone runtime nodes and physical AI.
The conceptual layer for brown links, digging instead of scrolling, buried artifacts and post-feed web grammar.
A portal domain into the bury flow where brown links can be made, shared and later dug up.
A drop/portal layer into the o-vvv-o bury system and Brown Web cluster.
A hidden commercial experiment: rentable visible ad-space as a modern persistent advertising booklet.
Dutch variant of the rentable ad-field idea: category-based visible space, not feed advertising.
A save-loading entrypoint for the LootMemory / AI game-memory workflow.
GPTGTA is the flagship build: a playable GPT-native top-down browser crime sandbox with map editor pipeline.
OldDug is the future social layer: artifact → bury → dig → re-dug → trail.
AI Memory Card keeps everything contained so ideas can live as save slots before becoming full domains.
RaynorStack is the theory layer: coherent thinking about philosophy in the AI era, coherence semantics, chromatic computing, spatial runtime interfaces, transparency, humane robotics, physical AI and the post-smartphone shift in perceived meaning.
The practical builds are not separate from the canon. They are runtime experiments: interfaces where memory, provenance, game-like interaction and ambient systems become usable.
Raynor Eissens builds AI-native prototypes, browser worlds and ambient interface systems. The work explores how AI changes memory, games, social feeds, provenance, meaning and human-computer interaction.
Instead of treating AI as a shortcut, this portfolio treats AI as a new prototyping medium: a way to discover categories, test interfaces, make worlds playable and document new grammars early.
Raynor Eissens — AI-native prototypes, browser worlds & ambient interface systems.
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