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README.md

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+# Gnommo Player
+
+This project is a proof of concept for an interactive lecture player.
+
+## Reusable Player Surface
+
+The player is now organized so it can be embedded in a larger React app such as GnommoEditor.
+
+The intended host integration looks like this:
+
+```tsx
+import {
+  GlitchPlayer,
+  defaultSlideRegistry,
+  createSessionId,
+  type PresentationDefinition,
+  type VoteRequest
+} from "./player";
+import "./player/styles.css";
+
+function GnommoEditorPreview({
+  presentation,
+  onVoteCommit
+}: {
+  presentation: PresentationDefinition;
+  onVoteCommit: (vote: VoteRequest) => Promise<void> | void;
+}) {
+  return (
+    <GlitchPlayer
+      presentation={presentation}
+      slideRegistry={defaultSlideRegistry}
+      initialSessionId={createSessionId()}
+      onVoteCommit={onVoteCommit}
+    />
+  );
+}
+```
+
+The key boundary is:
+
+- the host app fetches the presentation
+- the host app provides the slide registry
+- the host app owns vote/event persistence
+- the player owns playback, timing, layout, gestures, and rendering
+
+## Why This Exists
+
+The goal is not just to make ordinary videos or ordinary slide decks.
+
+The goal is to build a pipeline for AI-assisted lecture creation, where a lecture can eventually become a normal YouTube video, but starts as a richer structured presentation format.
+
+The underlying idea is:
+
+- A creator writes a lecture script in a web-based presentation editor, similar to Keynote.
+- The creator defines a timed slide show and only decides high-level layout behavior, such as whether a slide should be square or fullscreen.
+- The creator records talking-head video segments and uploads them.
+- Those segments are stitched into a continuous lecture timeline and transcribed.
+- The spoken words become the scaffold for when slide events should happen.
+- The actual slide contents can then be generated or refined by AI using available templates.
+
+That slide content does not need to be limited to static slides. A slide may be:
+
+- a React component
+- a chart or visualization
+- an image
+- a 3D scene
+- an interactive explanatory surface
+
+This creates a new kind of lecture format:
+
+- the talking head provides narrative continuity
+- the slide layer provides rich explanation
+- the viewer can inspect, manipulate, and compare alternate variants of the same explanation
+
+## Product Vision
+
+The long-term vision is a system for authoring lectures as structured, interactive presentations first, and rendering them into linear video later.
+
+That means:
+
+- creators can use AI to help generate visual explanations
+- multiple candidate slide variants can compete for the same moment in the lecture
+- viewers can browse or interact with those variants
+- the format can later crystallize into a fixed canonical video suitable for YouTube
+
+## Why The Player Matters
+
+This player is the runtime for that format.
+
+It proves that a lecture can be represented as:
+
+- stitched talking-head video segments
+- timed slide events on a continuous timeline
+- square or fullscreen slide presentation modes
+- interactive slide content
+- variant selection and future preference learning
+
+In short:
+
+This project exists to explore an AI-assisted interactive lecture format that can begin as a live structured presentation and later become a standard video.