docs: update diagrams-README to reflect AI normalization architecture

Updated workflow-marker-extraction diagram description to emphasize:
- AI-powered normalization for natural conversation (agents.py)
- Simple line-start fallback for explicit markers (workflow.py)
- Two-tier extraction system design

Benefits of this approach:
- Participants write naturally without strict formatting rules
- Fast AI model handles conversation → structured data conversion
- Simple fallback code when AI unavailable
- Clear separation of concerns

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

docs/diagrams-README.md

@@ -157,17 +157,17 @@ plantuml -tsvg docs/*.puml
 ---
 
 ### 10. **workflow-marker-extraction.puml** 🆕
-**Detailed flowchart** of regex-based marker extraction from discussion files.
+**Detailed flowchart** of AI-powered marker extraction with simple fallback parsing.
 
 **Shows:**
 - Comment parsing from discussion files
-- Regex pattern matching for **DECISION**, **QUESTION**, **ACTION**
-- Support for both plain (DECISION:) and markdown bold (**DECISION**:) formats
-- Structured data extraction
+- AI normalization (agents.py) for natural conversation
+- Simple line-start fallback for explicit markers (DECISION:, QUESTION:, ACTION:)
+- Structured data extraction from AI-generated JSON
 - Summary section generation
 - Marker block updates in .sum.md files
 
-**Best for:** Understanding how structured markers are extracted and why regex was chosen over line-start matching.
+**Best for:** Understanding the two-tier extraction system - AI for natural conversation, simple parsing for strict format fallback.
 
 ---
 
@@ -236,9 +236,11 @@ Patch fails → Save debug artifacts → Log error → Continue
 4. Check .git/ai-rules-debug/ for provider outputs
 
 ### Understanding Marker Extraction
-1. See **workflow-marker-extraction.puml** for regex patterns
-2. Review automation/workflow.py for implementation
-3. Test with **DECISION**, **QUESTION**, **ACTION** markers in discussions
+1. See **workflow-marker-extraction.puml** for AI normalization flow
+2. Review automation/agents.py for AI-powered extraction
+3. Review automation/workflow.py for simple fallback implementation
+4. Test with natural conversation - AI extracts markers automatically
+5. Fallback: Use explicit line-start markers (DECISION:, QUESTION:, ACTION:)
 
 ---
 
@@ -252,7 +254,7 @@ Patch fails → Save debug artifacts → Log error → Continue
 | Model Hints (fast/quality) | ✅ Complete | ai-provider-fallback.puml |
 | Vote Tracking | ✅ Complete | voting-system.puml |
 | Multi-Stage Promotion | ✅ Complete | discussion-stages.puml |
-| Regex Marker Extraction | ✅ Complete | workflow-marker-extraction.puml |
+| AI Marker Normalization | ✅ Complete | workflow-marker-extraction.puml |
 | Structured Summaries | ✅ Complete | workflow-marker-extraction.puml |
 | Implementation Gate | ✅ Complete | file-lifecycle.puml |
 | Error Handling | ✅ Complete | commit-workflow.puml |