Major restructure: 10-part layout, nav redesign, heading fixes, CSS consolidation

Reorganized from 7 parts to 10 parts with renumbered chapters (0-36).
Redesigned chapter navigation as CSS grid cards with gradient backgrounds.
Stripped hyperlinks from headings across 49 files (80 links removed).
Removed duplicate nav arrows (775 total across 428 files).
Fixed h2/h3 line-height gap with explicit 1.3 value.
Added cover page robot animation, task registry cleanup, and misc fixes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: apartsin

.claude/launch.json

@@ -0,0 +1,11 @@
+{
+  "version": "0.0.1",
+  "configurations": [
+    {
+      "name": "book-preview",
+      "runtimeExecutable": "python",
+      "runtimeArgs": ["-m", "http.server", "8080", "--directory", "E:/Projects/LLMCourse"],
+      "port": 8080
+    }
+  ]
+}

.claude/settings.local.json

@@ -8,7 +8,10 @@
       "WebSearch",
       "WebFetch(*)",
       "Skill(update-config)",
-      "Skill(update-config:*)"
+      "Skill(update-config:*)",
+      "mcp__Desktop_Commander__start_search",
+      "mcp__Desktop_Commander__get_more_search_results",
+      "mcp__Claude_Preview__preview_start"
     ]
   }
 }

.nojekyll

@@ -0,0 +1,221 @@
+# Book Configuration
+
+This file contains all book-specific details for the textbook production pipeline.
+The pipeline skill (`textbook-chapter`) and its agent definitions are generic and
+reusable across any textbook project. This file is the only place where content
+specific to THIS book lives.
+
+When adapting the pipeline for a different book, create a new `BOOK_CONFIG.md` in
+the new project's root directory with the same sections below.
+
+## Book Identity
+
+- **Title**: Building Conversational AI using LLM and Agents
+- **Subtitle**: A Practitioner's Guide to Large Language Models
+- **Target Audience**: Software engineers with basic Python, familiar with APIs and JSON; basic linear algebra (vectors, matrices, dot products)
+- **Output Format**: HTML chapter files linking to shared stylesheet `styles/book.css`
+
+## Visual Style
+
+- **Illustrations**: Warm, colorful, cartoon-like illustrations generated via Gemini API
+- **Application Examples**: Teal/green color scheme
+- **Bibliographies**: Card-based layout (`.bib-entry-card`)
+- **Epigraphs**: Humorous quotes attributed to "A [Adjective] AI Agent/Model/etc."
+
+## Chapter Map (Current Structure)
+
+All agents that need to reference other chapters (Cross-Reference, Bibliography,
+Narrative Continuity, etc.) use this canonical chapter map. This is the ACTIVE structure
+on disk. All agents should use this until migration to the proposed structure is complete.
+
+```
+Part 1: Foundations (part-1-foundations/)
+  00: ML & PyTorch Foundations         module-00-ml-pytorch-foundations
+  01: NLP & Text Representation        module-01-foundations-nlp-text-representation
+  02: Tokenization & Subword Models    module-02-tokenization-subword-models
+  03: Sequence Models & Attention      module-03-sequence-models-attention
+  04: Transformer Architecture         module-04-transformer-architecture
+  05: Decoding & Text Generation       module-05-decoding-text-generation
+
+Part 2: Understanding LLMs (part-2-understanding-llms/)
+  06: Pretraining & Scaling Laws       module-06-pretraining-scaling-laws
+  07: Modern LLM Landscape             module-07-modern-llm-landscape
+  08: Reasoning & Test-Time Compute    module-08-reasoning-test-time-compute
+  09: Inference Optimization           module-09-inference-optimization
+  18: Interpretability                 module-18-interpretability
+
+Part 3: Working with LLMs (part-3-working-with-llms/)
+  10: LLM APIs                         module-10-llm-apis
+  11: Prompt Engineering               module-11-prompt-engineering
+  12: Hybrid ML + LLM                  module-12-hybrid-ml-llm
+
+Part 4: Training & Adapting (part-4-training-adapting/)
+  13: Synthetic Data                   module-13-synthetic-data
+  14: Fine-Tuning Fundamentals         module-14-fine-tuning-fundamentals
+  15: PEFT                             module-15-peft
+  16: Distillation & Merging           module-16-distillation-merging
+  17: Alignment, RLHF & DPO           module-17-alignment-rlhf-dpo
+
+Part 5: Retrieval & Conversation (part-5-retrieval-conversation/)
+  19: Embeddings & Vector DBs          module-19-embeddings-vector-db
+  20: RAG                              module-20-rag
+  21: Conversational AI                module-21-conversational-ai
+
+Part 6: Agentic AI (part-6-agentic-ai/)
+  22: AI Agents                        module-22-ai-agents
+  23: Tool Use & Protocols             module-23-tool-use-protocols
+  24: Multi-Agent Systems              module-24-multi-agent-systems
+  25: Specialized Agents               module-25-specialized-agents
+  26: Agent Safety & Production        module-26-agent-safety-production
+
+Part 7: Multimodal & Applications (part-7-multimodal-applications/)
+  27: Multimodal                       module-27-multimodal
+  28: LLM Applications                 module-28-llm-applications
+
+Part 8: Evaluation & Production (part-8-evaluation-production/)
+  29: Evaluation & Observability       module-29-evaluation-observability
+  30: Observability & Monitoring       module-30-observability-monitoring
+  31: Production Engineering           module-31-production-engineering
+
+Part 9: Safety & Strategy (part-9-safety-strategy/)
+  32: Safety, Ethics & Regulation      module-32-safety-ethics-regulation
+  33: Strategy, Product & ROI          module-33-strategy-product-roi
+
+Part 10: Frontiers (part-10-frontiers/)
+  34: Emerging Architectures           module-34-emerging-architectures
+  35: AI & Society                     module-35-ai-society
+```
+
+**Note:** Part 2 contains module-18 (Interpretability) and Part 6 contains module-23
+(tool-use-protocols) alongside the legacy module-23 (multi-agent-systems). The canonical
+module-23 is `module-23-tool-use-protocols`; the legacy `module-23-multi-agent-systems`
+directory should be removed or merged into `module-24-multi-agent-systems` when convenient.
+
+## Proposed Structure (Pending, v3)
+
+The following restructuring has been proposed but NOT yet executed on disk. Agents should
+continue using the Current Structure above until migration is complete. This section
+exists to document the plan and guide the Structural Architect (Agent #19) when the
+restructuring is approved.
+
+**Key changes (v3, based on competitive analysis of 11 books and 6 courses):**
+- AI Agents get their own dedicated Part (Part 6) with 4 chapters
+- Interpretability moves from Training to Understanding (it explains models, not trains them)
+- Data Engineering for LLMs added as new chapter (per LLM Engineer's Handbook, Chip Huyen)
+- Structured Output made explicit in APIs chapter title
+- Multimodal stays as its own topic (not merged into Part 2; requires Part 3-5 knowledge)
+- Applications grouped by pattern (4 chapters: code, knowledge, enterprise, creative)
+- LLMOps made explicit in Production chapter
+- LLM Security made explicit in Safety chapter
+- Voice/speech AI included in Conversational AI (given book title)
+
+```
+Part 1: Foundations (6 chapters, unchanged)
+  00: ML & PyTorch Foundations
+  01: NLP & Text Representation
+  02: Tokenization & Subword Models
+  03: Sequence Models & Attention
+  04: Transformer Architecture
+  05: Decoding & Text Generation
+
+Part 2: Understanding LLMs (4 chapters, +1: Interpretability moved here)
+  06: Pretraining & Scaling Laws
+  07: Modern LLM Landscape (incl. reasoning models, SLMs, on-device)
+  08: Inference Optimization (incl. caching strategies, edge deployment)
+  09: Interpretability & Mechanistic Understanding [MOVED from Part 4]
+
+Part 3: Working with LLMs (4 chapters, +1: Data Engineering added)
+  10: LLM APIs & Structured Output (incl. JSON mode, function calling)
+  11: Prompt Engineering & Advanced Techniques
+  12: Hybrid ML + LLM Architectures
+  13: Data Engineering for LLMs [NEW] (pipelines, quality, curation, governance)
+
+Part 4: Training & Adapting (5 chapters, Interpretability moved out)
+  14: Synthetic Data Generation
+  15: Fine-Tuning Fundamentals
+  16: Parameter-Efficient Fine-Tuning (PEFT)
+  17: Distillation & Merging
+  18: Alignment: RLHF, DPO & Preference Tuning
+
+Part 5: Retrieval & Conversation (3 chapters, unchanged)
+  19: Embeddings & Vector Databases
+  20: RAG (incl. long-context vs. RAG tradeoffs, GraphRAG)
+  21: Conversational AI (incl. voice/speech-to-speech, real-time)
+
+Part 6: AI Agents (4 chapters, dedicated Part)
+  22: Agent Foundations, Protocols & Tool Use (MCP, A2A, AG-UI, ReAct)
+  23: Agent Memory, Planning & Reasoning (test-time compute, MemGPT/Letta)
+  24: Multi-Agent Systems (orchestration, debate, swarm, simulation)
+  25: Agent Applications (code agents, browser agents, scientific agents)
+
+Part 7: Multimodal & Applications (5 chapters)
+  26: Multimodal Models (vision, audio, cross-modal, document AI)
+  27: Code & Development AI
+  28: Knowledge & Search AI
+  29: Enterprise AI Applications (healthcare, legal, finance, customer service)
+  30: Creative & Education AI
+
+Part 8: Production & Strategy (3 chapters)
+  31: Production Engineering & LLMOps (experiment tracking, CI/CD, monitoring)
+  32: Safety, Security, Ethics & Regulation (LLM security, red teaming, EU AI Act)
+  33: Strategy, Product & ROI
+
+Capstone:
+  34: Toward AGI (ARC-AGI benchmarks, scaling debate, emergent capabilities, alignment)
+```
+
+**Total: 35 chapters across 8 Parts + capstone**
+
+**Migration checklist** (to execute when approved):
+- [ ] Rename directories and files on disk
+- [ ] Update all cross-references and navigation links
+- [ ] Update the Current Structure section above (replace with this proposed structure)
+- [ ] Update CROSS_REFERENCE_MAP.md with new section numbers
+- [ ] Update CONFORMANCE_CHECKLIST.md book-specific sections
+- [ ] Run Controller sweep to verify no broken links remain
+- [ ] Create new chapter directories for: 13 (Data Engineering), 34 (Toward AGI)
+- [ ] Split current Ch 25 (LLM Applications) into Chs 27-30
+- [ ] Renumber current Ch 14-28 to new numbering scheme
+
+## Relative Path Rules
+
+- Same part: `../module-XX-name/index.html`
+- Different part: `../../part-N-name/module-XX-name/index.html`
+
+## Batch Partitioning (for parallel agent runs)
+
+When running agents across the entire book, partition by Part for parallelism:
+
+- Batch A: Part 1 (Chapters 0-5, 6 modules)
+- Batch B: Part 2 (Chapters 6-9 + 18, 5 modules)
+- Batch C: Part 3 (Chapters 10-12, 3 modules)
+- Batch D: Part 4 (Chapters 13-17, 5 modules)
+- Batch E: Part 5 (Chapters 19-21, 3 modules)
+- Batch F: Part 6 (Chapters 22-26, 5 modules)
+- Batch G: Part 7 (Chapters 27-28, 2 modules)
+- Batch H: Part 8 (Chapters 29-31, 3 modules)
+- Batch I: Part 9 (Chapters 32-33, 2 modules)
+- Batch J: Part 10 (Chapters 34-35, 2 modules)
+
+## Example Epigraphs by Chapter Theme
+
+These are book-specific humorous epigraph examples. Each chapter gets one epigraph
+attributed to a fictional AI persona using the "A [Adjective] [AI Role]" format.
+
+- Tokenization: "I spent three hours debugging a Unicode error. Turns out the model
+  thought an emoji was four separate tokens. It was, technically, correct."
+  *A Tokenizer Who Has Seen Things*
+- Attention: "They told me to attend to everything. So I did. Now I am 8 heads,
+  none of which agree with each other."
+  *An Attention Head With Existential Questions*
+- Fine-tuning: "I was a perfectly good base model. Then they showed me 10,000
+  customer support transcripts and now I cannot stop being helpful."
+  *A Reluctantly Aligned Language Model*
+- Scaling laws: "More data. More parameters. More compute. At some point you stop
+  asking 'will it work?' and start asking 'can we afford the electricity bill?'"
+  *A Mildly Concerned Cluster Administrator*
+- RAG: "I used to hallucinate confidently. Now I hallucinate with citations."
+  *An Unusually Honest Neural Network*
+- Agents: "They gave me tools, memory, and the ability to plan. I immediately
+  got stuck in an infinite loop. Just like the humans, really."
+  *A Self-Aware ReAct Agent*