Marcin: /* 7. The Problem Scope Can Be Narrowed */

2026-04-06T12:39:24Z

7. The Problem Scope Can Be Narrowed

← Older revision		Revision as of 12:39, 6 April 2026
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	* This is a much smaller and more tractable problem space		* This is a much smaller and more tractable problem space

			=Links=
			*[[Local Server Image Upload Size Spec for Live Cloud Editable Documents]]

Marcin at 12:38, 6 April 2026

2026-04-06T12:38:46Z

← Older revision		Revision as of 12:38, 6 April 2026
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	https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e		https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e

			= Why This Is Now Achievable =

			== 1. Real-Time Collaboration Is No Longer a Research Problem ==

			Previously, this was the hardest part:

			* Operational Transform (OT) or CRDT design
			* Conflict resolution
			* Cursor syncing
			* Offline/merge behavior

			Now:

			* Libraries like Yjs and Automerge provide:
			** Shared data structures
			** Real-time sync
			** Offline-first behavior
			** Awareness (who’s editing what)

			Impact:

			* You no longer build the collaboration engine—you plug it in

			== 2. The Browser Became a Serious Application Runtime ==

			Previously:

			* Canvas/WebGL were immature
			* Performance was inconsistent
			* Input handling (drag, resize, selection) was painful

			Now:

			* Stable Canvas/WebGL stacks
			* High-performance rendering
			* Mature UI ecosystems (React, etc.)

			You can build:

			* Slide canvases
			* Object manipulation (resize, rotate)
			* Zoom/pan editors

			Impact:

			* The visual editor layer is now straightforward engineering, not experimental

			== 3. Editor Frameworks Exist (You Don’t Start From Zero) ==

			Previously:

			* You had to write:
			** Selection models
			** Cursor logic
			** Document trees

			Now:

			* Rich-text and structured editors exist (ProseMirror, Slate)
			* Canvas editors (Fabric.js, Konva) handle object manipulation

			Impact:

			* You assemble instead of invent

			== 4. AI Removes the Integration Bottleneck ==

			This is the biggest shift.

			Previously:

			* Integrating all components took weeks or months
			* Debugging edge cases was slow and manual

			Now AI can:

			* Generate working scaffolds
			* Wire Yjs into an editor
			* Build drag/resize behavior
			* Implement undo/redo stacks
			* Handle serialization (JSON ↔ UI)

			Impact:

			* What used to be hard engineering glue work is now mostly automated

			== 5. Cloud/Backend Complexity Collapsed ==

			Previously:

			* You had to design:
			** WebSocket servers
			** Sync layers
			** Persistence models

			Now:

			* Yjs providers (WebRTC, WebSocket)
			* Firebase/Supabase-type backends
			* Serverless infrastructure

			Impact:

			* Backend is no longer a primary blocker

			== 6. Open-Source Examples Exist (Huge Accelerator) ==

			You are no longer guessing architecture.

			There are working systems you can study:

			* Collaborative editors
			* Whiteboards
			* Slide tools
			* Notion-like systems

			Impact:

			* You start from patterns, not theory

			== 7. The Problem Scope Can Be Narrowed ==

			This is subtle but critical.

			Google Slides is hard because it tries to be:

			* Universal
			* Fully featured
			* Backward compatible
			* Enterprise-grade

			You do not need that.

			For OSE, the likely needs are:

			* Structured slides tied to ideas/build systems
			* Embedded editing in wiki
			* Export capability

			Impact:

			* This is a much smaller and more tractable problem space

Marcin: Created page with "https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e"

2026-04-06T12:01:12Z

Created page with "https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e"

New page

https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e

Towards Viable Google Slides in Open Source - Revision history

Marcin: /* 7. The Problem Scope Can Be Narrowed */

Marcin at 12:38, 6 April 2026

Marcin: Created page with "https://chatgpt.com/share/69d3a033-ca24-8331-98ea-093fbcf0c01e"