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AI at a glance
AI
Adobe co-founder John Warnock created Illustrator in late 1986 to automate many of the manual tasks used by his wife Marva, a graphic designer. It was a commercialization of Adobe's in-house font development software and PostScript file format.
MD at a glance
MD
Markdown was created in 2004 by John Gruber with Aaron Swartz, but the later CommonMark effort became important because the original syntax description was too ambiguous to keep implementations aligned.
Format comparison
| Feature | AI | MD |
|---|---|---|
| File type | Vector | Document |
| Extensions |
|
|
| MIME type |
|
|
| Compression / quality | scalable | depends |
| File size characteristics | small | medium |
| Compatibility | moderate | broad |
| Editability | high | moderate |
| Created year | 1987 | 2004 |
| Inventor | Adobe Systems | John Gruber and Aaron Swartz |
| Status | active | active |
| Primary use cases |
|
|
| Common software |
|
|
| Archival suitability | good | strong |
| Metadata handling | moderate | moderate |
| Delivery profile | strong | strong |
| Workflow fit | design | exchange |
| Vector scaling | Supported | Not supported |
| Structured data | Not supported | Supported |
When to use each format
When to use AI
- illustration
- diagramming
- brand asset delivery
- Industry-standard vector format with deep feature support.
When to use MD
- authoring
- review and collaboration
- distribution
- Readable in raw plain text.
FAQs
Why convert AI to MD?
Choose MD as target when convert to Markdown when the output should remain easy to edit in plain text, store in Git, review in diffs, or feed into automated publishing systems.
What changes when converting AI to MD?
Convert to Markdown when the output should remain easy to edit in plain text, store in Git, review in diffs, or feed into automated publishing systems. It is ideal for documentation, articles, developer guides, release notes, and notes that will later be rendered into richer formats. Use Markdown when semantic structure matters more than exact page layout.
What should I review after converting AI to MD?
After conversion, review these destination checks: Open converted output in docs generators and verify behavior on real samples; Compare output against the expected depends quality profile; Feature sets vary significantly across implementations.
How can I keep quality stable in AI to MD conversion?
Run representative samples, keep settings deterministic, and monitor these risks: The simplicity that made Markdown popular also created years of portability ambiguity; Feature sets vary significantly across implementations; Validate destination compatibility before large-batch conversion.