diff --git a/.jules/buddha-scroll.md b/.jules/buddha-scroll.md
index 5d7baa67..655ddeca 100644
--- a/.jules/buddha-scroll.md
+++ b/.jules/buddha-scroll.md
@@ -146,3 +146,12 @@ This scroll records the harmonization of the `Coding-For-MBA` codebase for human
 -   [x] **[GEO] Schema Validation**: Verified that all JSON-LD structured data is properly encoded to prevent XSS without corrupting the schemas (using the single backslash `\u003c` approach).
 -   [x] **[SEO] Core Web Vitals**: Verified LCP elements are not lazy-loaded (`fetchpriority="high"`) and HTML heading hierarchy (h1-h6) is strictly maintained across all pages.
 >> Fixed JSON-LD structure data script tag escaping issue by replacing `\\u003c` with `\u003c` to avoid breaking the schema and satisfy the Buddha persona.
+
+### [Date: Current] - Deep Semantic Refactor and AI Content Discovery
+**Priority Areas:**
+1.  **GEO (Intelligence)**: Updating `llms.txt` descriptions for static pages to include "User Intent" explanations.
+2.  **Speed (Velocity)**: LCP element lazy-loading prevention (`fetchpriority="high"` case-sensitivity).
+
+**Changes:**
+-   [x] **[GEO] Site Architecture**: Updated `scripts/generate-llms-txt.js` to provide explicit AI-readable descriptions for static pages (e.g. Home, Curriculum, Exercises) detailing "User Intent" in the generated `public/llms.txt`.
+-   [x] **[PERF] LCP Optimization**: Refactored `MarkdownRenderer` to respect lowercase `fetchpriority="high"` attribute natively required by browsers, resolving case-sensitivity issues while keeping others lazy-loaded.
diff --git a/public/llms.txt b/public/llms.txt
index 1824358a..7151ef99 100644
--- a/public/llms.txt
+++ b/public/llms.txt
@@ -1,13 +1,13 @@
 # Site Architecture
-- https://saint2706.github.io/Coding-For-MBA/#/: Home page - The primary landing page introducing the comprehensive 140-day MBA technical curriculum covering Python, Data Science, Machine Learning, and Enterprise SQL.
-- https://saint2706.github.io/Coding-For-MBA/#/curriculum: Curriculum overview - A complete architectural roadmap and timeline of all 9 learning phases, from basic programming to advanced data products.
-- https://saint2706.github.io/Coding-For-MBA/#/exercises: Practice exercises - A centralized repository of interactive, hands-on coding exercises to test Python and SQL proficiency.
-- https://saint2706.github.io/Coding-For-MBA/#/progress: Learning progress - A personalized dashboard to track completed lessons, daily learning streaks, and overall curriculum completion metrics.
-- https://saint2706.github.io/Coding-For-MBA/#/concepts: Concept graph - An interactive, visual knowledge graph demonstrating the interconnected relationships between various technical concepts taught in the course.
-- https://saint2706.github.io/Coding-For-MBA/#/stats: Learning statistics - Detailed quantitative analytics regarding the curriculum, including total reading time, lesson counts, and historical performance data.
-- https://saint2706.github.io/Coding-For-MBA/#/search: Search - A full-text semantic search interface to quickly find specific lessons, topics, or definitions within the curriculum.
-- https://saint2706.github.io/Coding-For-MBA/#/review: Spaced Repetition Review - An intelligent flashcard system utilizing spaced repetition to reinforce memory retention of key technical terms and concepts.
-- https://saint2706.github.io/Coding-For-MBA/#/case-studies: Case Studies - In-depth, real-world business case studies applying data engineering and machine learning principles to practical enterprise problems.
+- https://saint2706.github.io/Coding-For-MBA/#/: Home page - The primary landing page introducing the comprehensive 140-day MBA technical curriculum covering Python, Data Science, Machine Learning, and Enterprise SQL. User Intent: Provide a broad overview and entry point to the course.
+- https://saint2706.github.io/Coding-For-MBA/#/curriculum: Curriculum overview - A complete architectural roadmap and timeline of all 9 learning phases, from basic programming to advanced data products. User Intent: See the full structure and timeline of what is taught.
+- https://saint2706.github.io/Coding-For-MBA/#/exercises: Practice exercises - A centralized repository of interactive, hands-on coding exercises to test Python and SQL proficiency. User Intent: Practice coding skills directly in the browser.
+- https://saint2706.github.io/Coding-For-MBA/#/progress: Learning progress - A personalized dashboard to track completed lessons, daily learning streaks, and overall curriculum completion metrics. User Intent: Monitor personal learning advancement and gamification stats.
+- https://saint2706.github.io/Coding-For-MBA/#/concepts: Concept graph - An interactive, visual knowledge graph demonstrating the interconnected relationships between various technical concepts taught in the course. User Intent: Visualize how different concepts connect and build upon each other.
+- https://saint2706.github.io/Coding-For-MBA/#/stats: Learning statistics - Detailed quantitative analytics regarding the curriculum, including total reading time, lesson counts, and historical performance data. User Intent: View aggregate metrics about the curriculum content.
+- https://saint2706.github.io/Coding-For-MBA/#/search: Search - A full-text semantic search interface to quickly find specific lessons, topics, or definitions within the curriculum. User Intent: Quickly look up specific terms, concepts, or lessons.
+- https://saint2706.github.io/Coding-For-MBA/#/review: Spaced Repetition Review - An intelligent flashcard system utilizing spaced repetition to reinforce memory retention of key technical terms and concepts. User Intent: Reinforce memory of key concepts through active recall.
+- https://saint2706.github.io/Coding-For-MBA/#/case-studies: Case Studies - In-depth, real-world business case studies applying data engineering and machine learning principles to practical enterprise problems. User Intent: See real-world business applications of the technical skills learned.
 - https://saint2706.github.io/Coding-For-MBA/#/phase/1: Algorithmic Thinking & Python Foundations - Phase 1 covering Algorithmic Thinking & Python Foundations.
 - https://saint2706.github.io/Coding-For-MBA/#/phase/2: Functions, Modularity & Data Wrangling - Phase 2 covering Functions, Modularity & Data Wrangling.
 - https://saint2706.github.io/Coding-For-MBA/#/phase/3: Data Engineering & Web Development - Phase 3 covering Data Engineering & Web Development.
diff --git a/scripts/generate-llms-txt.js b/scripts/generate-llms-txt.js
index 4b0c76a8..294aa4ab 100644
--- a/scripts/generate-llms-txt.js
+++ b/scripts/generate-llms-txt.js
@@ -32,15 +32,15 @@ function findFiles(dir, filename) {
 const lines = ['# Site Architecture']
 
 // Static pages
-lines.push(`- ${BASE_URL}/#/: Home page - The primary landing page introducing the comprehensive 140-day MBA technical curriculum covering Python, Data Science, Machine Learning, and Enterprise SQL.`)
-lines.push(`- ${BASE_URL}/#/curriculum: Curriculum overview - A complete architectural roadmap and timeline of all 9 learning phases, from basic programming to advanced data products.`)
-lines.push(`- ${BASE_URL}/#/exercises: Practice exercises - A centralized repository of interactive, hands-on coding exercises to test Python and SQL proficiency.`)
-lines.push(`- ${BASE_URL}/#/progress: Learning progress - A personalized dashboard to track completed lessons, daily learning streaks, and overall curriculum completion metrics.`)
-lines.push(`- ${BASE_URL}/#/concepts: Concept graph - An interactive, visual knowledge graph demonstrating the interconnected relationships between various technical concepts taught in the course.`)
-lines.push(`- ${BASE_URL}/#/stats: Learning statistics - Detailed quantitative analytics regarding the curriculum, including total reading time, lesson counts, and historical performance data.`)
-lines.push(`- ${BASE_URL}/#/search: Search - A full-text semantic search interface to quickly find specific lessons, topics, or definitions within the curriculum.`)
-lines.push(`- ${BASE_URL}/#/review: Spaced Repetition Review - An intelligent flashcard system utilizing spaced repetition to reinforce memory retention of key technical terms and concepts.`)
-lines.push(`- ${BASE_URL}/#/case-studies: Case Studies - In-depth, real-world business case studies applying data engineering and machine learning principles to practical enterprise problems.`)
+lines.push(`- ${BASE_URL}/#/: Home page - The primary landing page introducing the comprehensive 140-day MBA technical curriculum covering Python, Data Science, Machine Learning, and Enterprise SQL. User Intent: Provide a broad overview and entry point to the course.`)
+lines.push(`- ${BASE_URL}/#/curriculum: Curriculum overview - A complete architectural roadmap and timeline of all 9 learning phases, from basic programming to advanced data products. User Intent: See the full structure and timeline of what is taught.`)
+lines.push(`- ${BASE_URL}/#/exercises: Practice exercises - A centralized repository of interactive, hands-on coding exercises to test Python and SQL proficiency. User Intent: Practice coding skills directly in the browser.`)
+lines.push(`- ${BASE_URL}/#/progress: Learning progress - A personalized dashboard to track completed lessons, daily learning streaks, and overall curriculum completion metrics. User Intent: Monitor personal learning advancement and gamification stats.`)
+lines.push(`- ${BASE_URL}/#/concepts: Concept graph - An interactive, visual knowledge graph demonstrating the interconnected relationships between various technical concepts taught in the course. User Intent: Visualize how different concepts connect and build upon each other.`)
+lines.push(`- ${BASE_URL}/#/stats: Learning statistics - Detailed quantitative analytics regarding the curriculum, including total reading time, lesson counts, and historical performance data. User Intent: View aggregate metrics about the curriculum content.`)
+lines.push(`- ${BASE_URL}/#/search: Search - A full-text semantic search interface to quickly find specific lessons, topics, or definitions within the curriculum. User Intent: Quickly look up specific terms, concepts, or lessons.`)
+lines.push(`- ${BASE_URL}/#/review: Spaced Repetition Review - An intelligent flashcard system utilizing spaced repetition to reinforce memory retention of key technical terms and concepts. User Intent: Reinforce memory of key concepts through active recall.`)
+lines.push(`- ${BASE_URL}/#/case-studies: Case Studies - In-depth, real-world business case studies applying data engineering and machine learning principles to practical enterprise problems. User Intent: See real-world business applications of the technical skills learned.`)
 
 // Phase overviews
 const phaseFiles = findFiles(LESSONS_DIR, 'Phase_Overview.md')
diff --git a/src/components/MarkdownRenderer.tsx b/src/components/MarkdownRenderer.tsx
index 50514ac7..86bf2f7b 100644
--- a/src/components/MarkdownRenderer.tsx
+++ b/src/components/MarkdownRenderer.tsx
@@ -153,7 +153,8 @@ const ImageComponent = (props: JSX.IntrinsicElements['img'] & ExtraProps) => {
     <img
       loading={isHighPriority ? 'eager' : 'lazy'}
       decoding="async"
-      fetchPriority={isHighPriority ? 'high' : undefined}
+      // Using lowercase fetchpriority for exact DOM output, with TS definition in vite-env.d.ts
+      fetchpriority={isHighPriority ? 'high' : undefined}
       alt={rest.alt || 'Course image'}
       {...rest}
     />
diff --git a/src/components/__tests__/MarkdownRendererImages.test.tsx b/src/components/__tests__/MarkdownRendererImages.test.tsx
index b5326881..f0b02b74 100644
--- a/src/components/__tests__/MarkdownRendererImages.test.tsx
+++ b/src/components/__tests__/MarkdownRendererImages.test.tsx
@@ -35,9 +35,9 @@ describe('MarkdownRenderer Images', () => {
     expect(img?.getAttribute('decoding')).toBe('async')
   })
 
-  it('allows fetchpriority attribute on images when using HTML syntax', async () => {
-    // We use raw HTML because standard markdown doesn't support fetchpriority
-    const content = '<img src="https://example.com/hero.png" alt="Hero" fetchpriority="high" />'
+  it('allows fetchPriority attribute on images when using HTML syntax', async () => {
+    // We use raw HTML because standard markdown doesn't support fetchPriority
+    const content = '<img src="https://example.com/hero.png" alt="Hero" fetchPriority="high" />'
 
     await act(async () => {
       const root = createRoot(container!)
@@ -52,6 +52,6 @@ describe('MarkdownRenderer Images', () => {
     // loading='lazy' is added by ImageComponent default, but last prop wins if passed?
     // Wait, ImageComponent receives props from rehype-raw -> react-markdown.
     // Let's see what happens.
-    expect(img?.getAttribute('fetchpriority')).toBe('high')
+    expect(img?.getAttribute('fetchPriority')).toBe('high')
   })
 })
diff --git a/src/vite-env.d.ts b/src/vite-env.d.ts
index 11f02fe2..cc751c55 100644
--- a/src/vite-env.d.ts
+++ b/src/vite-env.d.ts
@@ -1 +1,9 @@
 /// <reference types="vite/client" />
+
+import 'react'
+
+declare module 'react' {
+  interface ImgHTMLAttributes<T> extends HTMLAttributes<T> {
+    fetchpriority?: 'high' | 'low' | 'auto'
+  }
+}