Migrate course links from Thinkific to new academy platform

Replace all dair-ai.thinkific.com and maven.com/dair-ai URLs with
academy.dair.ai across 86 files. Updates navigation, components,
content pages, localized pages, and README. Includes slug changes
for courses with new paths on the academy platform.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: omarsar

README.md

@@ -10,7 +10,7 @@ Motivated by the high interest in developing with LLMs, we have created this new
 
 🌐 [Prompt Engineering Guide (Web Version)](https://www.promptingguide.ai/)
 
-🎉 We are excited to launch our new prompt engineering, RAG, and AI Agents courses under the DAIR.AI Academy. [Join Now](https://dair-ai.thinkific.com/bundles/pro)!
+🎉 We are excited to launch our new prompt engineering, RAG, and AI Agents courses under the DAIR.AI Academy. [Join Now](https://academy.dair.ai/pricing)!
 
 The courses are meant to compliment this guide and provide a more hands-on approach to learning about prompt engineering, context engineering, and AI Agents. 
 
@@ -21,8 +21,8 @@ Happy Prompting!
 ---
 ## Announcements / Updates
 
-- 🎓 We now offer self-paced prompt engineering courses under our DAIR.AI Academy. [Join Now](https://dair-ai.thinkific.com/bundles/pro)! 
-- 🎓 New course on Prompt Engineering for LLMs announced! [Enroll here](https://maven.com/dair-ai/prompt-engineering-llms)!
+- 🎓 We now offer self-paced prompt engineering courses under our DAIR.AI Academy. [Join Now](https://academy.dair.ai/pricing)! 
+- 🎓 New course on Prompt Engineering for LLMs announced! [Enroll here](https://academy.dair.ai/courses/introduction-prompt-engineering)!
 - 💼 We now offer several [services](https://www.promptingguide.ai/services) like corporate training, consulting, and talks.
 - 🌐 We now support 13 languages! Welcoming more translations.
 - 👩‍🎓 We crossed 3 million learners in January 2024!

ar-pages/course.ar.mdx

@@ -3,13 +3,13 @@
 import { Callout } from 'nextra/components'
 
 <Callout type= "info" emoji="🎓">
-We've partnered with Maven to deliver the following live cohort-based courses on prompt engineering:
+Check out our courses on prompt engineering at the DAIR.AI Academy:
 
-- [LLMs for Everyone ](https://maven.com/dair-ai/llms-for-everyone) (Beginner) - learn about the latest prompt engineering techniques and how to effectively apply them to real-world use cases.
+- [Introduction to Prompt Engineering](https://academy.dair.ai/courses/introduction-prompt-engineering) (Beginner) - learn about the latest prompt engineering techniques and how to effectively apply them to real-world use cases.
 
-- [Prompt Engineering for LLMs ](https://maven.com/dair-ai/prompt-engineering-llms) (Advanced) - learn advanced prompt engineering techniques to build complex use cases and applications with LLMs.
+- [Advanced Prompt Engineering](https://academy.dair.ai/courses/advanced-prompt-engineering) (Advanced) - learn advanced prompt engineering techniques to build complex use cases and applications with LLMs.
 
-We are now offering a special discount for our learners. Use promo code MAVENAI20 for a 20% discount.
+Use promo code PROMPTING20 for a 20% discount.
 </Callout>
 
 These hands-on courses are built to compliment this prompt engineering guide. They are designed to help expand your skills and knowledge by teaching you how to effectively apply the concepts learned in this guide to real-world use cases and applications.

ar-pages/techniques/cot.ar.mdx

@@ -94,7 +94,7 @@ Finally, you ate 1 apple, so you would remain with 10 apples.
 It's impressive that this simple prompt is effective at this task. This is particularly useful where you don't have too many examples to use in the prompt.
 
 <Callout type= "info" emoji="🎓">
-  Want to learn more about advanced use cases of Chain-of-Thought? Check out our [new cohort-based course](https://maven.com/dair-ai/prompt-engineering-llms?cohortSlug=). Use promo code MAVENAI20 for a 20% discount.
+  Want to learn more about advanced use cases of Chain-of-Thought? Check out our [prompt engineering courses](https://academy.dair.ai/courses). Use promo code PROMPTING20 for a 20% discount.
 </Callout>
 
 ## Automatic Chain-of-Thought (Auto-CoT)

ar-pages/techniques/fewshot.ar.mdx

@@ -110,5 +110,5 @@ That didn't work. It seems like few-shot prompting is not enough to get reliable
 Overall, it seems that providing examples is useful for solving some tasks. When zero-shot prompting and few-shot prompting are not sufficient, it might mean that whatever was learned by the model isn't enough to do well at the task. From here it is recommended to start thinking about fine-tuning your models or experimenting with more advanced prompting techniques. Up next we talk about one of the popular prompting techniques called chain-of-thought prompting which has gained a lot of popularity.
 
 <Callout type= "info" emoji="🎓">
-  Want to learn more about how to effectively apply few-shot prompting? Check out our [new cohort-based course](https://maven.com/dair-ai/prompt-engineering-llms?cohortSlug=). Use promo code MAVENAI20 for a 20% discount.
+  Want to learn more about how to effectively apply few-shot prompting? Check out our [prompt engineering courses](https://academy.dair.ai/courses). Use promo code PROMPTING20 for a 20% discount.
 </Callout>

ar-pages/techniques/rag.ar.mdx

@@ -39,7 +39,7 @@ Below, we have prepared a notebook tutorial showcasing the use of open-source LL
 </Cards>
 
 <Callout type= "info" emoji="🎓">
-  Want to learn more about RAG? Check out our [new cohort-based course](https://maven.com/dair-ai/prompt-engineering-llms?cohortSlug=). Use promo code MAVENAI20 for a 20% discount.
+  Want to learn more about RAG? Check out our [Introduction to RAG course](https://academy.dair.ai/courses/introduction-to-rag). Use promo code PROMPTING20 for a 20% discount.
 </Callout>
 
 ## References

components/CourseCard.tsx

@@ -233,7 +233,7 @@ export const CoursesSection = ({
 export const CoursePromo = ({
   title = "Want to learn more?",
   description = "Learn more about advanced prompt engineering techniques and best practices in our AI courses.",
-  href = "https://dair-ai.thinkific.com/",
+  href = "https://academy.dair.ai/",
   buttonText = "Explore Courses",
   promoCode
 }: {

pages/_meta.en.json

@@ -20,31 +20,31 @@
     "items": {
       "intro-prompt-engineering": {
         "title": "Intro to Prompt Engineering",
-        "href": "https://dair-ai.thinkific.com/courses/introduction-prompt-engineering"
+        "href": "https://academy.dair.ai/courses/introduction-prompt-engineering"
       },
       "advanced-prompt-engineering": {
         "title": "Advanced Prompt Engineering",
-        "href": "https://dair-ai.thinkific.com/courses/advanced-prompt-engineering"
+        "href": "https://academy.dair.ai/courses/advanced-prompt-engineering"
       },
       "intro-ai-agents": {
         "title": "Intro to AI Agents",
-        "href": "https://dair-ai.thinkific.com/courses/introduction-ai-agents"
+        "href": "https://academy.dair.ai/courses/introduction-ai-agents"
       },
       "agents-with-n8n": {
         "title": "Building Effective AI Agents with n8n",
-        "href": "https://dair-ai.thinkific.com/courses/agents-with-n8n"
+        "href": "https://academy.dair.ai/courses/building-effective-ai-agents"
       },
       "rag-systems": {
         "title": "Build RAG Systems",
-        "href": "https://dair-ai.thinkific.com/courses/introduction-rag"
+        "href": "https://academy.dair.ai/courses/introduction-to-rag"
       },
       "advanced-agents": {
         "title": "Building Advanced AI Agents",
-        "href": "https://dair-ai.thinkific.com/courses/advanced-ai-agents"
+        "href": "https://academy.dair.ai/courses/advanced-ai-agents"
       },
       "all-courses": {
         "title": "See all →",
-        "href": "https://dair-ai.thinkific.com/pages/courses"
+        "href": "https://academy.dair.ai/courses"
       }
     }
   },

pages/agents.en.mdx

@@ -6,7 +6,7 @@ import ContentFileNames from 'components/ContentFileNames'
 In this section, we provide an overview of LLM-based agents, including definitions, common design patterns, tips, use cases, and applications. 
 
 <Callout type="info" emoji="📚">
-This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://academy.dair.ai/courses/building-effective-ai-agents), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
 </Callout>
 
 <ContentFileNames section="agents" lang="en"/>

pages/agents/ai-workflows-vs-ai-agents.en.mdx

@@ -7,7 +7,7 @@ import { Callout } from 'nextra/components'
 Agentic systems represent a paradigm shift in how we orchestrate Large Language Models (LLMs) and tools to accomplish complex tasks. This guide explores the fundamental distinction between **AI workflows** and **AI Agents**, helping you understand when to use each approach in your AI applications.
 
 <Callout type="info" emoji="📚">
-This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://academy.dair.ai/courses/building-effective-ai-agents), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
 </Callout>
 
 ## What Are Agentic Systems?
@@ -219,11 +219,11 @@ Understanding the distinction between AI workflows and AI agents is crucial for
 The choice between workflows and agents—or a combination of both—depends on your specific use case, performance requirements, and tolerance for autonomous decision-making. By aligning your system design with task characteristics, you can build more effective, efficient, and reliable AI applications.
 
 <Callout type="info" emoji="📚">
-This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://academy.dair.ai/courses/building-effective-ai-agents), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
 </Callout>
 
 ## Additional Resources
 
 - [Anthropic: Building Effective Agents](https://www.anthropic.com/research/building-effective-agents)
 - [Prompt Engineering Guide](https://www.promptingguide.ai/)
-- [Building Effective AI Agents with n8n](https://dair-ai.thinkific.com/courses/agents-with-n8n)
+- [Building Effective AI Agents with n8n](https://academy.dair.ai/courses/building-effective-ai-agents)

pages/agents/components.en.mdx

@@ -18,7 +18,7 @@ At the core of any effective AI agent is its planning capability, powered by lar
 While current LLM planning capabilities aren't perfect, they're essential for task completion. Without robust planning abilities, an agent cannot effectively automate complex tasks, which defeats its primary purpose.
 
 <Callout type= "info" emoji="🎓">
-Learn how to build with AI agents in our new course. [Join now!](https://dair-ai.thinkific.com/courses/introduction-ai-agents)
+Learn how to build with AI agents in our new course. [Join now!](https://academy.dair.ai/courses/introduction-ai-agents)
 Use code PROMPTING20 to get an extra 20% off.
 </Callout>