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GitHub Repository
125 starsPython
How context engineering works, a runnable reference
by linsys·Apr 17, 2026·46 points·15 comments
AI Analysis
●MidShip It
Five-component architecture adds output enforcement to standard RAG pipelines.
Strengths
- •Clear five-component breakdown separates retrieval from output enforcement.
- •Runnable Bedrock examples avoid abstract theory without working code.
- •Comparisons folder shows concrete differences between RAG and context engineering.
Weaknesses
- •Requires AWS Bedrock setup and Claude FTU form approval to run.
- •Conceptual rename of existing orchestration patterns found in LangChain.
Category
Target Audience
AI engineers building enterprise RAG systems
Similar To
LangChain · LlamaIndex · DSPy
Post Description
I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
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