𝗧𝗵𝗶𝘀 𝗶𝘀 𝘁𝗵𝗲 𝗼𝗻𝗲 𝗿𝗲𝗽𝗼 𝗲𝘃𝗲𝗿𝘆 𝗔𝗜 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗺𝘂𝘀𝘁 𝗸𝗻𝗼𝘄.
Not because it’s trending.
But because it shows how RAG actually works in the real world.
The NirDiamant/RAG_Techniques repository isn’t a tutorial dump.
It’s a complete RAG engineering handbook.
𝗪𝗵𝗮𝘁’𝘀 𝘀𝗽𝗲𝗰𝗶𝗮𝗹 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗶𝘀 𝗿𝗲𝗽𝗼 👇
→ It goes far beyond “vector DB + prompt”
→ Covers 40+ RAG techniques, from fundamentals to production-grade systems
→ Every technique is explained with clear intuition + runnable code
→ Designed for engineers building serious GenAI systems, not demos
𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗲𝗮𝗿𝗻 👇
↳ Foundational RAG done right
↳ Chunk sizing, proposition chunking, reliable RAG
↳ The basics most people skip and later regret
If you’re building copilots, internal search, agents, or production GenAI systems. This repo should already be bookmarked.
𝗚𝗶𝘁𝗛𝘂𝗯 → https://t.co/JJ2Gxl0TMR
Cc : Author
Day 04 @ Kodr 2.0 → Diving into CI/CD pipelines with GitHub Actions!
@sheryians_
Learned to integrate:
* Jest & Linting
* Husky for pre-commit hooks
* Continuous Integration & Deployment
Also applied MongoDB Aggregation Pipelines → faster queries & optimized performance.
Team meeting with PM + peers was super productive. Excited for what’s next!
#RBAC#MongoDB#Bootcamp#DevCommunity
Day @sheryians_ – Sprint on Authentication
Built User, Role & Permission models with RBAC for secure access control. Used interfaces + services for clean architecture.
My Team
@codewithbixi
@ankitn9109
Key takeaway: Today connected Docker portability + IAM security + AWS networking. Each day, DevOps is becoming more clear and industry-ready!
Big thanks to @ankurdotio bhaiya
Day 03 at Kodr2.0 Bootcamp 🚀 We tackled a big issue: Docker images built on our system often don’t match AWS architecture. Here’s what we learned @sheryians_