AI generated ack

Author: ofriw

scripts/generate-podcast.js

@@ -108,6 +108,13 @@ async function generateDialogue(content, fileName) {
 
   const model = genAI.getGenerativeModel({ model: DIALOGUE_MODEL });
 
+  // Special handling for intro.md - add self-aware meta-commentary
+  const isIntro = fileName === 'intro';
+  const metaCommentary = isIntro ? `
+
+SPECIAL INSTRUCTIONS FOR THIS EPISODE:
+This is the course introduction. When discussing the section about how the course was developed using AI (including the podcast itself), have Alex and Sam briefly acknowledge in a natural, professional way that they themselves are AI-generated voices. This should feel like a thoughtful meta-moment, not gimmicky. Keep it concise - one or two exchanges where they note the self-referential nature of AI-generated hosts discussing AI-generated content. Make it feel authentic to how senior engineers would react to this realization.` : '';
+
   const prompt = `You are converting technical course content into a natural, engaging two-person podcast conversation.
 
 Speakers:
@@ -122,7 +129,7 @@ Guidelines:
 - Keep technical accuracy - don't dumb down the content
 - Make it engaging but professional
 - Break down complex concepts through dialogue
-- Reference real-world scenarios and examples
+- Reference real-world scenarios and examples${metaCommentary}
 
 Technical Content Title: ${fileName}
 

website/docs/intro.md

@@ -64,9 +64,19 @@ Most importantly: you'll know **when to use agents** and **when to write code yo
 ## Prerequisites
 
 - **Experience:** 3+ years professional software engineering
-- **Tools:** Access to a CLI coding agent (Claude Code, Aider, Cursor, or similar)
+- **Tools:** Access to a CLI coding agent (Claude Code, OpenAI Codex, Copilot CLI, etc)
 - **Mindset:** Willingness to unlearn "AI as teammate" and adopt "AI as tool"
 
+## About This Course's Development
+
+**This course practices what it teaches.** The entire curriculum—content structure, lesson progression, code examples, and documentation—was developed using the same AI-assisted techniques and workflows you'll learn here.
+
+Every module was planned, researched, drafted, and refined through systematic prompting, agentic research, and iterative validation. The process followed the exact methodology outlined in the course: breaking work into agent-appropriate tasks, grounding in architectural context, and validating output critically.
+
+**The podcast version of each lesson** was generated using Claude Code and Google's Gemini API—converting technical content into conversational dialogue, then synthesizing multi-speaker audio. The voices you hear (Alex and Sam) are AI-generated, as is their script. Even this acknowledgment exists because we applied the principle of transparency in AI-assisted work.
+
+This isn't marketing. It's validation. If these techniques can produce production-grade training material on their own application, they're robust enough for your codebase.
+
 ---
 
 **Ready to start?** Begin with [Understanding the Tools](/docs/understanding-the-tools/lesson-1-intro).