I made my Enterprise RAG book $0 today — would love feedback from people building RAG systems

I’ve spent the last few years building production RAG systems and documenting what worked, what didn’t, and where things tend to break in production.

I turned those lessons into a book covering topics like:

• RAG reference architectures
• Data extraction and chunking
• Hybrid and multi-stage retrieval
• Graph and hierarchical RAG
• Agentic and multi-agent RAG
• Memory
• Evaluation and synthetic data
• Security and compliance
• Production monitoring and human-in-the-loop systems

The book is $0 on Amazon today, so I thought I’d share it here in case it’s useful to anyone working on RAG.

https://a.co/d/0dBRCb7F

I’m especially interested in feedback from people actually building these systems: What’s missing? What deserves more depth? What would you change?

If you end up finding the book useful, an honest Amazon review is appreciated, but feedback here is equally valuable.

Full contents

Part I — About
01 About the Author

Part II — RAG & Reference Architecture
02 The Evolution of RAG
03 Foundations of RAG Systems
04 Reference Architecture

Part III — Data Extraction
05 Data Extraction

Part IV — Chunking
06 Chunking Strategies

Part V — RAG Strategies
07 Baseline RAG Pipeline
08 Context-Aware RAG
09 Dynamic RAG
10 Hybrid RAG
11 Multi-Stage Retrieval
12 Graph-Based RAG
13 Hierarchical RAG
14 Agentic RAG
15 Multi-Agent RAG Systems
16 Streaming RAG

Part VI — Memory & Content Management
17 Memory-Augmented RAG
18 Knowledge Graph Integration

Part VII — Evaluation
19 Evaluation Metrics
20 Synthetic Data Generation

Part VIII — Fine-Tuning
21 Domain-Specific Fine-Tuning

Part IX — Security
22 Privacy & Compliance in RAG

Part X — Production
23 Real-Time Evaluation & Monitoring
24 Human-in-the-Loop RAG

Part XI — Twig RAG Strategies
25 RAG Strategies in Twig

Part XII — Conclusion
26 Conclusion & Future Directions

I made my Enterprise Retrieval Augmented Generation book $0 today — would love feedback from people building RAG systems

I’ve spent the last few years building production RAG systems and documenting what worked, what didn’t, and where things tend to break in production.

I turned those lessons into a book covering topics like:

• RAG reference architectures
• Data extraction and chunking
• Hybrid and multi-stage retrieval
• Graph and hierarchical RAG
• Agentic and multi-agent RAG
• Memory
• Evaluation and synthetic data
• Security and compliance
• Production monitoring and human-in-the-loop systems

The book is $0 on Amazon today, so I thought I’d share it here in case it’s useful to anyone working on RAG.

https://a.co/d/0dBRCb7F

https://preview.redd.it/xur6100utjkh1.png?width=1930&format=png&auto=webp&s=6b4b48c18e58e8eb258bdb49008747aac25e2b12

I’m especially interested in feedback from people actually building these systems: What’s missing? What deserves more depth? What would you change?

If you end up finding the book useful, an honest Amazon review is appreciated, but feedback here is equally valuable.

Full contents

Part I — About
01 About the Author

Part II — RAG & Reference Architecture
02 The Evolution of RAG
03 Foundations of RAG Systems
04 Reference Architecture

Part III — Data Extraction
05 Data Extraction

Part IV — Chunking
06 Chunking Strategies

Part V — RAG Strategies
07 Baseline RAG Pipeline
08 Context-Aware RAG
09 Dynamic RAG
10 Hybrid RAG
11 Multi-Stage Retrieval
12 Graph-Based RAG
13 Hierarchical RAG
14 Agentic RAG
15 Multi-Agent RAG Systems
16 Streaming RAG

Part VI — Memory & Content Management
17 Memory-Augmented RAG
18 Knowledge Graph Integration

Part VII — Evaluation
19 Evaluation Metrics
20 Synthetic Data Generation

Part VIII — Fine-Tuning
21 Domain-Specific Fine-Tuning

Part IX — Security
22 Privacy & Compliance in RAG

Part X — Production
23 Real-Time Evaluation & Monitoring
24 Human-in-the-Loop RAG

Part XI — Twig RAG Strategies
25 RAG Strategies in Twig

Part XII — Conclusion
26 Conclusion & Future Directions

Hey All, A few months ago I had published the "21 RAG Strategies" Book Here. And it was downloaded about 2500 times across subreddits. I made 2 revisions from the feedback.

This week I published it on Amazon and it became a best seller. I am getting ready to publish the next editition. Help me improve the content. What am I missing. what would you add?

Table of Contents

• RAG and the Reference Architecture
  • 02 The Evolution of RAG
  • 03 Foundations of RAG Systems
  • 04 Reference Architecture
  • P A R T I I I Data Extraction
  • 05 Data Extraction
  • P A R T I V Chunking
  • 06 Chunking Strategies
  • P A R T V RAG Strategies
  • 07 Baseline RAG Pipeline
  • 08 Context-Aware RAG
  • 09 Dynamic RAG
  • 10 Hybrid RAG
  • 11 Multi-Stage Retrieval
  • 12 Graph-Based RAG
  • 13 Hierarchical RAG
  • 14 Agentic RAG
  • 15 Multi-Agent RAG Systems
  • 16 Streaming RAG
  • P A R T V I Memory and Content Management
  • 17 Memory-Augmented RAG
  • 18 Knowledge Graph IntegrationP A R T V I I Evaluation
  • 19 Evaluation Metrics
  • 20 Synthetic Data Generation
• Fine-Tuning
  • 21 Domain-Specific Fine-Tuning
• Security
  • 22 Privacy & Compliance in RAG
• Production
  • 23 Real-Time Evaluation & Monitoring
  • 24 Human-in-the-Loop RAG
• Twig RAG Strategies
  • 25 RAG Strategies in Twig
• P A R T X I I Conclusion
  • 26 Conclusion & Future Directions

I finally took the leap and published the 21 RAG strategies guide as a book on Amazon. It now has chapters on chunking and agentic RAG. What should i add next?

Table of Contents

P A R T I About

01 About the Author

P A R T I I RAG and the Reference Architecture

02 The Evolution of RAG

03 Foundations of RAG Systems

04 Reference Architecture

P A R T I I I Data Extraction

05 Data Extraction

P A R T I V Chunking

06 Chunking Strategies

P A R T V RAG Strategies

07 Baseline RAG Pipeline

08 Context-Aware RAG

09 Dynamic RAG

10 Hybrid RAG

11 Multi-Stage Retrieval

12 Graph-Based RAG

13 Hierarchical RAG

14 Agentic RAG

15 Multi-Agent RAG Systems

16 Streaming RAG

P A R T V I Memory and Content Management

17 Memory-Augmented RAG

18 Knowledge Graph IntegrationP A R T V I I Evaluation

19 Evaluation Metrics

20 Synthetic Data Generation

P A R T V I I I Fine-Tuning

21 Domain-Specific Fine-Tuning

P A R T I X Security

22 Privacy & Compliance in RAG

P A R T X Production

23 Real-Time Evaluation & Monitoring

24 Human-in-the-Loop RAG

P A R T X I Twig RAG Strategies

25 RAG Strategies in Twig

P A R T X I I Conclusion

26 Conclusion & Future Directions