Enhance documentation formatting and structure for clarity

- Added detailed question formatting guidelines to AGENTS.md for main section and FAQ questions.
- Updated FAQs section headers in multiple talk documents to ensure consistent markdown usage.
- Improved overall organization and readability of the documentation, aligning with established formatting standards.

Author: jxnl

docs/talks/AGENTS.md

@@ -40,6 +40,31 @@ All talk titles follow a **catchy, conversational format** designed to grab atte
 - **Code examples**: Where applicable, include implementation details
 - **Performance metrics**: Specific numbers and improvements mentioned
 
+## Question Formatting Guidelines
+**Main Section Questions**: Use proper markdown headers for navigable sections:
+```markdown
+## Why is accurate document parsing so critical for AI applications?
+## How should you evaluate document parsing performance?
+## What are the most challenging document elements to parse correctly?
+```
+
+**FAQ Section Questions**: Use bold emphasis within FAQ content:
+```markdown
+## FAQs
+
+**What is document ingestion in the context of AI applications?**
+
+Document ingestion refers to the process of extracting...
+
+**Why is accurate document parsing so important for AI applications?**
+
+Accurate parsing is critical because...
+```
+
+**Key Distinction**: 
+- `## Question?` = Main section headers (navigable, structured content)
+- `**Question?**` = FAQ emphasis (within content sections only)
+
 ## Key Topics Covered
 - **"Why I Stopped Using RAG for Coding Agents (And You Should Too)"** - Nik Pash (Cline)
 - **"The RAG Mistakes That Are Killing Your AI (Lessons from Google & LinkedIn)"** - Skylar Payne
@@ -63,6 +88,8 @@ All talk titles follow a **catchy, conversational format** designed to grab atte
 ## Formatting Standards
 - **Consistent H1 titles**: Match YAML frontmatter exactly
 - **Proper markdown structure**: Use ## for main sections, ### for subsections
+- **Question headers**: Use `## Question?` format for main section questions (NOT `**Question?**`)
+- **FAQ sections**: Use `**Question?**` for emphasis within FAQ content sections
 - **Bold key takeaways**: `**Key Takeaway:**` format for main insights
 - **Blockquotes for quotes**: Use `>` for speaker quotes
 - **Bullet points**: Use `-` for lists with **bold** labels

docs/talks/extend-eli-document-workflows.md

@@ -189,7 +189,7 @@ As AI capabilities continue to advance, the companies that will benefit most are
 
 ---
 
-# FAQs
+## FAQs
 
 ### What is document automation and why is it important?
 

docs/talks/fine-tuning-rerankers-embeddings-ayush-lancedb.md

@@ -168,7 +168,7 @@ This is why having a range of options - from lightweight models like MiniLM to m
 
 **Key Takeaway:** Model selection should be driven by your specific constraints and requirements, not just raw performance numbers. Consider the entire system when making these decisions.
 
-## FAQs:
+## FAQs
 
 ## What are re-rankers and why should I use them?
 Re-rankers are models that improve retrieval quality by reordering documents after they've been retrieved from a database. They fit into your pipeline after retrieval and before the context is provided to an LLM, helping to ensure the most relevant documents appear at the top. Re-rankers are particularly valuable because they don't disrupt your existing pipeline—you don't need to re-ingest your entire dataset, making them a low-hanging fruit for improving retrieval performance.