johnxie · johnxie · Feb 24, 2026 · Feb 24, 2026 · Feb 24, 2026 · Feb 24, 2026
diff --git a/tutorials/README.md b/tutorials/README.md
@@ -17,11 +17,16 @@ Use this guide to navigate all tutorial tracks, understand structure rules, and
 <<<<<<< HEAD
 | Tutorial directories | 188 |
 | Tutorial markdown files | 1705 |
-| Tutorial markdown lines | 632,794 |
+| Tutorial markdown lines | 738,367 |
 =======
+<<<<<<< HEAD
 | Tutorial directories | 188 |
 | Tutorial markdown files | 1705 |
-| Tutorial markdown lines | 632,794 |
+| Tutorial markdown lines | 738,367 |
+=======
+| Tutorial directories | 188 |
+| Tutorial markdown files | 1705 |
+| Tutorial markdown lines | 738,367 |
 
 ## Source Verification Snapshot
 
@@ -38,6 +43,7 @@ Repository-source verification run against tutorial index references (GitHub API
 - JSON: [../discoverability/tutorial-source-verification.json](../discoverability/tutorial-source-verification.json)
 - Script: [../scripts/verify_tutorial_sources.py](../scripts/verify_tutorial_sources.py)
 >>>>>>> origin/main
+>>>>>>> origin/main
 
 ## Content Structure Patterns
 

diff --git a/tutorials/copilot-cli-tutorial/01-getting-started.md b/tutorials/copilot-cli-tutorial/01-getting-started.md
diff --git a/tutorials/copilot-cli-tutorial/02-authentication-and-access-policies.md b/tutorials/copilot-cli-tutorial/02-authentication-and-access-policies.md
diff --git a/tutorials/copilot-cli-tutorial/03-interactive-workflow-and-approval-model.md b/tutorials/copilot-cli-tutorial/03-interactive-workflow-and-approval-model.md
diff --git a/tutorials/copilot-cli-tutorial/04-models-experimental-features-and-autopilot.md b/tutorials/copilot-cli-tutorial/04-models-experimental-features-and-autopilot.md
diff --git a/tutorials/copilot-cli-tutorial/05-mcp-and-lsp-extension-points.md b/tutorials/copilot-cli-tutorial/05-mcp-and-lsp-extension-points.md
diff --git a/tutorials/copilot-cli-tutorial/06-github-native-context-workflows.md b/tutorials/copilot-cli-tutorial/06-github-native-context-workflows.md
diff --git a/tutorials/copilot-cli-tutorial/07-installation-and-update-channels.md b/tutorials/copilot-cli-tutorial/07-installation-and-update-channels.md
diff --git a/tutorials/copilot-cli-tutorial/08-production-governance-and-team-rollout.md b/tutorials/copilot-cli-tutorial/08-production-governance-and-team-rollout.md
diff --git a/tutorials/copilotkit-tutorial/01-getting-started.md b/tutorials/copilotkit-tutorial/01-getting-started.md
@@ -8,6 +8,9 @@ parent: CopilotKit Tutorial
 
 # Chapter 1: Getting Started with CopilotKit
 
+Welcome to **Chapter 1: Getting Started with CopilotKit**. In this part of **CopilotKit Tutorial: Building AI Copilots for React Applications**, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
+
+
 > Set up CopilotKit in your React application and create your first AI copilot with basic functionality.
 
 ## Overview
@@ -653,4 +656,51 @@ Now that you have a basic copilot running, let's explore how to make your app co
 
 **Ready for Chapter 2?** [Reading App Context](02-app-context.md)
 
-*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+
+## What Problem Does This Solve?
+
+Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for `text`, `className`, `todo` so behavior stays predictable as complexity grows.
+
+In practical terms, this chapter helps you avoid three common failures:
+
+- coupling core logic too tightly to one implementation path
+- missing the handoff boundaries between setup, execution, and validation
+- shipping changes without clear rollback or observability strategy
+
+After working through this chapter, you should be able to reason about `Chapter 1: Getting Started with CopilotKit` as an operating subsystem inside **CopilotKit Tutorial: Building AI Copilots for React Applications**, with explicit contracts for inputs, state transitions, and outputs.
+
+Use the implementation notes around `copilotkit`, `react`, `note` as your checklist when adapting these patterns to your own repository.
+
+## How it Works Under the Hood
+
+Under the hood, `Chapter 1: Getting Started with CopilotKit` usually follows a repeatable control path:
+
+1. **Context bootstrap**: initialize runtime config and prerequisites for `text`.
+2. **Input normalization**: shape incoming data so `className` receives stable contracts.
+3. **Core execution**: run the main logic branch and propagate intermediate state through `todo`.
+4. **Policy and safety checks**: enforce limits, auth scopes, and failure boundaries.
+5. **Output composition**: return canonical result payloads for downstream consumers.
+6. **Operational telemetry**: emit logs/metrics needed for debugging and performance tuning.
+
+When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
+
+## Source Walkthrough
+
+Use the following upstream sources to verify implementation details while reading this chapter:
+
+- [View Repo](https://github.com/CopilotKit/CopilotKit)
+  Why it matters: authoritative reference on `View Repo` (github.com).
+- [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)
+  Why it matters: authoritative reference on `Awesome Code Docs` (github.com).
+
+Suggested trace strategy:
+- search upstream code for `text` and `className` to map concrete implementation paths
+- compare docs claims against actual runtime/config code before reusing patterns in production
+
+## Chapter Connections
+
+- [Tutorial Index](index.md)
+- [Next Chapter: Chapter 2: Reading App Context - Making Your App State Visible to AI](02-app-context.md)
+- [Main Catalog](../../README.md#-tutorial-catalog)
+- [A-Z Tutorial Directory](../../discoverability/tutorial-directory.md)
diff --git a/tutorials/copilotkit-tutorial/02-app-context.md b/tutorials/copilotkit-tutorial/02-app-context.md
@@ -8,6 +8,9 @@ parent: CopilotKit Tutorial
 
 # Chapter 2: Reading App Context - Making Your App State Visible to AI
 
+Welcome to **Chapter 2: Reading App Context - Making Your App State Visible to AI**. In this part of **CopilotKit Tutorial: Building AI Copilots for React Applications**, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
+
+
 > Master useCopilotReadable to share application state, data, and context with your AI copilot for intelligent interactions.
 
 ## Overview
@@ -775,4 +778,52 @@ Now that the AI can see your app context, let's explore how to enable AI to take
 
 **Ready for Chapter 3?** [Copilot Actions](03-copilot-actions.md)
 
-*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+
+## What Problem Does This Solve?
+
+Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for `text`, `className`, `status` so behavior stays predictable as complexity grows.
+
+In practical terms, this chapter helps you avoid three common failures:
+
+- coupling core logic too tightly to one implementation path
+- missing the handoff boundaries between setup, execution, and validation
+- shipping changes without clear rollback or observability strategy
+
+After working through this chapter, you should be able to reason about `Chapter 2: Reading App Context - Making Your App State Visible to AI` as an operating subsystem inside **CopilotKit Tutorial: Building AI Copilots for React Applications**, with explicit contracts for inputs, state transitions, and outputs.
+
+Use the implementation notes around `dept`, `length`, `projects` as your checklist when adapting these patterns to your own repository.
+
+## How it Works Under the Hood
+
+Under the hood, `Chapter 2: Reading App Context - Making Your App State Visible to AI` usually follows a repeatable control path:
+
+1. **Context bootstrap**: initialize runtime config and prerequisites for `text`.
+2. **Input normalization**: shape incoming data so `className` receives stable contracts.
+3. **Core execution**: run the main logic branch and propagate intermediate state through `status`.
+4. **Policy and safety checks**: enforce limits, auth scopes, and failure boundaries.
+5. **Output composition**: return canonical result payloads for downstream consumers.
+6. **Operational telemetry**: emit logs/metrics needed for debugging and performance tuning.
+
+When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
+
+## Source Walkthrough
+
+Use the following upstream sources to verify implementation details while reading this chapter:
+
+- [View Repo](https://github.com/CopilotKit/CopilotKit)
+  Why it matters: authoritative reference on `View Repo` (github.com).
+- [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)
+  Why it matters: authoritative reference on `Awesome Code Docs` (github.com).
+
+Suggested trace strategy:
+- search upstream code for `text` and `className` to map concrete implementation paths
+- compare docs claims against actual runtime/config code before reusing patterns in production
+
+## Chapter Connections
+
+- [Tutorial Index](index.md)
+- [Previous Chapter: Chapter 1: Getting Started with CopilotKit](01-getting-started.md)
+- [Next Chapter: Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App](03-copilot-actions.md)
+- [Main Catalog](../../README.md#-tutorial-catalog)
+- [A-Z Tutorial Directory](../../discoverability/tutorial-directory.md)
diff --git a/tutorials/copilotkit-tutorial/03-copilot-actions.md b/tutorials/copilotkit-tutorial/03-copilot-actions.md
@@ -8,6 +8,9 @@ parent: CopilotKit Tutorial
 
 # Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App
 
+Welcome to **Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App**. In this part of **CopilotKit Tutorial: Building AI Copilots for React Applications**, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
+
+
 > Master useCopilotAction to allow AI to perform operations, modify state, and interact with your application's backend.
 
 ## Overview
@@ -922,4 +925,52 @@ Now that the AI can perform actions in your app, let's explore the different cha
 
 **Ready for Chapter 4?** [Chat Components](04-chat-components.md)
 
-*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+
+## What Problem Does This Solve?
+
+Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for `text`, `name`, `className` so behavior stays predictable as complexity grows.
+
+In practical terms, this chapter helps you avoid three common failures:
+
+- coupling core logic too tightly to one implementation path
+- missing the handoff boundaries between setup, execution, and validation
+- shipping changes without clear rollback or observability strategy
+
+After working through this chapter, you should be able to reason about `Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App` as an operating subsystem inside **CopilotKit Tutorial: Building AI Copilots for React Applications**, with explicit contracts for inputs, state transitions, and outputs.
+
+Use the implementation notes around `endpoint`, `description`, `contact` as your checklist when adapting these patterns to your own repository.
+
+## How it Works Under the Hood
+
+Under the hood, `Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App` usually follows a repeatable control path:
+
+1. **Context bootstrap**: initialize runtime config and prerequisites for `text`.
+2. **Input normalization**: shape incoming data so `name` receives stable contracts.
+3. **Core execution**: run the main logic branch and propagate intermediate state through `className`.
+4. **Policy and safety checks**: enforce limits, auth scopes, and failure boundaries.
+5. **Output composition**: return canonical result payloads for downstream consumers.
+6. **Operational telemetry**: emit logs/metrics needed for debugging and performance tuning.
+
+When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
+
+## Source Walkthrough
+
+Use the following upstream sources to verify implementation details while reading this chapter:
+
+- [View Repo](https://github.com/CopilotKit/CopilotKit)
+  Why it matters: authoritative reference on `View Repo` (github.com).
+- [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)
+  Why it matters: authoritative reference on `Awesome Code Docs` (github.com).
+
+Suggested trace strategy:
+- search upstream code for `text` and `name` to map concrete implementation paths
+- compare docs claims against actual runtime/config code before reusing patterns in production
+
+## Chapter Connections
+
+- [Tutorial Index](index.md)
+- [Previous Chapter: Chapter 2: Reading App Context - Making Your App State Visible to AI](02-app-context.md)
+- [Next Chapter: Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar](04-chat-components.md)
+- [Main Catalog](../../README.md#-tutorial-catalog)
+- [A-Z Tutorial Directory](../../discoverability/tutorial-directory.md)
diff --git a/tutorials/copilotkit-tutorial/04-chat-components.md b/tutorials/copilotkit-tutorial/04-chat-components.md
@@ -8,6 +8,9 @@ parent: CopilotKit Tutorial
 
 # Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar
 
+Welcome to **Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar**. In this part of **CopilotKit Tutorial: Building AI Copilots for React Applications**, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
+
+
 > Master CopilotKit's chat UI components for creating conversational AI interfaces in your React applications.
 
 ## Overview
@@ -829,4 +832,52 @@ Now that you can build chat interfaces, let's explore Generative UI - AI-generat
 
 **Ready for Chapter 5?** [Generative UI](05-generative-ui.md)
 
-*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+
+## What Problem Does This Solve?
+
+Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for `className`, `text`, `gray` so behavior stays predictable as complexity grows.
+
+In practical terms, this chapter helps you avoid three common failures:
+
+- coupling core logic too tightly to one implementation path
+- missing the handoff boundaries between setup, execution, and validation
+- shipping changes without clear rollback or observability strategy
+
+After working through this chapter, you should be able to reason about `Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar` as an operating subsystem inside **CopilotKit Tutorial: Building AI Copilots for React Applications**, with explicit contracts for inputs, state transitions, and outputs.
+
+Use the implementation notes around `rounded`, `font`, `theme` as your checklist when adapting these patterns to your own repository.
+
+## How it Works Under the Hood
+
+Under the hood, `Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar` usually follows a repeatable control path:
+
+1. **Context bootstrap**: initialize runtime config and prerequisites for `className`.
+2. **Input normalization**: shape incoming data so `text` receives stable contracts.
+3. **Core execution**: run the main logic branch and propagate intermediate state through `gray`.
+4. **Policy and safety checks**: enforce limits, auth scopes, and failure boundaries.
+5. **Output composition**: return canonical result payloads for downstream consumers.
+6. **Operational telemetry**: emit logs/metrics needed for debugging and performance tuning.
+
+When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
+
+## Source Walkthrough
+
+Use the following upstream sources to verify implementation details while reading this chapter:
+
+- [View Repo](https://github.com/CopilotKit/CopilotKit)
+  Why it matters: authoritative reference on `View Repo` (github.com).
+- [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)
+  Why it matters: authoritative reference on `Awesome Code Docs` (github.com).
+
+Suggested trace strategy:
+- search upstream code for `className` and `text` to map concrete implementation paths
+- compare docs claims against actual runtime/config code before reusing patterns in production
+
+## Chapter Connections
+
+- [Tutorial Index](index.md)
+- [Previous Chapter: Chapter 3: Copilot Actions - Enabling AI to Take Actions in Your App](03-copilot-actions.md)
+- [Next Chapter: Chapter 5: Generative UI - AI-Generated React Components](05-generative-ui.md)
+- [Main Catalog](../../README.md#-tutorial-catalog)
+- [A-Z Tutorial Directory](../../discoverability/tutorial-directory.md)
diff --git a/tutorials/copilotkit-tutorial/05-generative-ui.md b/tutorials/copilotkit-tutorial/05-generative-ui.md
@@ -8,6 +8,9 @@ parent: CopilotKit Tutorial
 
 # Chapter 5: Generative UI - AI-Generated React Components
 
+Welcome to **Chapter 5: Generative UI - AI-Generated React Components**. In this part of **CopilotKit Tutorial: Building AI Copilots for React Applications**, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
+
+
 > Enable AI to generate and modify React components dynamically through natural language conversations.
 
 ## Overview
@@ -731,4 +734,52 @@ Now that you can generate UI components, let's explore CoAgents and LangGraph in
 
 **Ready for Chapter 6?** [CoAgents & LangGraph](06-coagents.md)
 
-*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+*Generated for [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)*
+
+## What Problem Does This Solve?
+
+Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for `className`, `text`, `gray` so behavior stays predictable as complexity grows.
+
+In practical terms, this chapter helps you avoid three common failures:
+
+- coupling core logic too tightly to one implementation path
+- missing the handoff boundaries between setup, execution, and validation
+- shipping changes without clear rollback or observability strategy
+
+After working through this chapter, you should be able to reason about `Chapter 5: Generative UI - AI-Generated React Components` as an operating subsystem inside **CopilotKit Tutorial: Building AI Copilots for React Applications**, with explicit contracts for inputs, state transitions, and outputs.
+
+Use the implementation notes around `font`, `component`, `form` as your checklist when adapting these patterns to your own repository.
+
+## How it Works Under the Hood
+
+Under the hood, `Chapter 5: Generative UI - AI-Generated React Components` usually follows a repeatable control path:
+
+1. **Context bootstrap**: initialize runtime config and prerequisites for `className`.
+2. **Input normalization**: shape incoming data so `text` receives stable contracts.
+3. **Core execution**: run the main logic branch and propagate intermediate state through `gray`.
+4. **Policy and safety checks**: enforce limits, auth scopes, and failure boundaries.
+5. **Output composition**: return canonical result payloads for downstream consumers.
+6. **Operational telemetry**: emit logs/metrics needed for debugging and performance tuning.
+
+When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
+
+## Source Walkthrough
+
+Use the following upstream sources to verify implementation details while reading this chapter:
+
+- [View Repo](https://github.com/CopilotKit/CopilotKit)
+  Why it matters: authoritative reference on `View Repo` (github.com).
+- [Awesome Code Docs](https://github.com/johnxie/awesome-code-docs)
+  Why it matters: authoritative reference on `Awesome Code Docs` (github.com).
+
+Suggested trace strategy:
+- search upstream code for `className` and `text` to map concrete implementation paths
+- compare docs claims against actual runtime/config code before reusing patterns in production
+
+## Chapter Connections
+
+- [Tutorial Index](index.md)
+- [Previous Chapter: Chapter 4: Chat Components - Building Chat Interfaces with CopilotChat and CopilotSidebar](04-chat-components.md)
+- [Next Chapter: Chapter 6: CoAgents & LangGraph - Building Agentic Workflows](06-coagents.md)
+- [Main Catalog](../../README.md#-tutorial-catalog)
+- [A-Z Tutorial Directory](../../discoverability/tutorial-directory.md)