Inside:
→ Clear definition of core terms (pipeline, CoT, RAG)
→ Overview of different prompting techniques
→ Working with different media types(text, images, audio, video)
→ How AI agents use external tools or generate code
→ Methods for evaluating GenAI outputs
→ Prompting frameworks you should know
→ Risks of prompt hacking and hardening measures
→ Alignment challenges and strategies to mitigate them
→ Detailed real-world case study

• 🧠 40+ in-depth guides covering Chain-of-Thought, RAG, ReAct, Tree-of-Thoughts, Self-Consistency, Program-Aided LMs & more

- 💻 Interactive notebooks, live demos, and real-world code examples

- ⚡ Includes specialized sections for GPT-4, Gemini, Claude, LLaMA, Mixtral, Phi-2, and OLMo models

- 📚 Constantly updated with the latest research papers, techniques, and benchmarks

- 🧩 New DAIR.AI Academy courses on Prompt Engineering, Context Engineering & AI Agents

- 🏆 Reached #1 on Hacker News, featured by *WSJ*, *Forbes*, *Markettechpost*

- 🔬 3M+ learners — used in universities, startups, and enterprise training programs

- 🧰 Includes tools, datasets, metrics, evaluation frameworks, and advanced prompting case studies

- 💬 Active community with 193+ contributors and 500+ deployments

- 🧩 Covers emerging topics like synthetic data generation, adversarial prompting, bias mitigation, and factuality

- 📖 Offers extensive collections on prompt applications — coding, reasoning, summarization, creativity, and truthfulness
- 🚀 MIT-licensed, fully open source, designed for collaboration and contribution