AI Engineering7 min read
RAG evaluation: metrics that actually matter
Learn how to quantitatively measure RAG system quality using the RAG Triad: context relevance, recall, faithfulness, and answer relevancy. Understand LL...
Loading...
Build Your First Software Factory Execution Harness live Thursday, Oct 1, 12:00 PM ET
Oct 1, Reserve a seatBlogDaily bytes of
Daily bytes of
AI engineering.
Bite-sized insights for building production AI systems. Expert guides, real-world patterns, and practical engineering wisdom.
Explore posts
136 posts in total
AI Engineering8 min read
Assembling and running your thinking RAG agent
How assembling works in production. Learn how to wire up all the nodes in LangGraph to create a complete, self-correcting RAG agent. See it in action with
AI Engineering7 min read
Building a self-correcting RAG agent
Learn how to build the decision-making nodes for an intelligent RAG agent: routing, grading, and generation. Understand how self-correction loops make a...
AI Engineering6 min read
Building an agent's brain with LangGraph
Learn how to build the foundation of an intelligent RAG agent using LangGraph. Understand state management, tool nodes, and the transition from linear c...
AI Engineering6 min read
Why your simple RAG is failing (and what to do about it)
Learn why linear RAG pipelines fail on complex queries and how to identify when you need a more sophisticated approach. Understand the limitations of si...
AI Engineering8 min read
Vertical vs. Horizontal agent communication: MCP vs. A2A
Learn the difference between vertical (MCP) and horizontal (A2A) agent communication patterns. Understand when to use agent-to-tool vs. agent-to-agent p...
AI Engineering9 min read
Function calling vs. MCP: the direct request vs. The conversational protocol
Learn when to use Function Calling (tool calling) vs. Model Context Protocol (MCP) for connecting AI agents to tools. Understand the architectural diffe...
AI Engineering10 min read
The decoupled agent: a guide to MCP
Learn how to build scalable, decoupled agents using Model Context Protocol (MCP). Step-by-step guide to creating MCP servers and connecting them to AI a...
AI Engineering8 min read
Giving your LLM hands: a deep dive on tool calling
How giving works in production. Learn how to build agents that can interact with the real world using tool calling. Step-by-step guide to implementing func
AI Engineering in Practice10 min read
The 'brain' of RAG: a guide to embeddings & vector databases
Understand how embeddings and vector databases work under the hood. Learn how computers translate text meaning into numbers and search millions of docum...
AI Engineering13 min read
How to choose your vector database
Compare vector databases for RAG systems. Learn when to use Chroma, Qdrant, Weaviate, pgvector, Pinecone, and Vespa based on performance, scale, and dev...
AI Engineering10 min read
Batteries-included RAG platforms: Dify vs. RagFlow vs. Onyx
Compare batteries-included RAG platforms that bundle the entire pipeline into one application. Learn when to use Dify, RAGFlow, and Onyx for rapid deplo...
Your Instructor
Built by Param Harrison
Cofounder of AEOsome.com and Chief Mentor at learnwithparam.com with 14+ years building production systems. I've trained 50+ engineers on AI engineering - these programs distill what actually works into structured paths you can follow at your own pace.
Ready to go deeper?
Go beyond articles. Build production AI systems with hands-on courses, or join a live cohort.