Ai Workflows
These answers come from the year-long archive of my previous chatbot that lived on my previous site iamnicola.ai. I’ve curated the most useful sessions—real questions from operators exploring AI workflows, experimentation, and conversion work—and lightly edited them so you get the original signal without the noise.
What is RAG and how does it work?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement a RAG system?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the difference between RAG and fine-tuning?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I choose between RAG and fine-tuning for my use case?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What are the best practices for RAG implementation?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I optimize RAG system performance?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What vector databases work best with RAG?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I handle RAG system errors and edge cases?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the cost of running a RAG system?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I measure RAG system effectiveness?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What are common RAG implementation mistakes?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I scale a RAG system?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the difference between RAG and traditional search?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG with multiple data sources?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What are the security considerations for RAG systems?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I improve RAG retrieval accuracy?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is chunking and why is it important for RAG?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I handle long documents in RAG?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the best embedding model for RAG?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG with real-time data?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the difference between RAG and semantic search?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG for customer support?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What are the limitations of RAG systems?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG with structured data?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the best architecture for a RAG system?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG with multiple languages?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What is the difference between RAG and knowledge graphs?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG for document Q&A?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
What are the performance benchmarks for RAG?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How do I implement RAG with streaming responses?
Direct Answer
RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers curren...
How does this chatbot work?
Direct Answer
Aria is a Retrieval-Augmented Generation (RAG) chatbot that answers questions by searching through more than 200 content sources on nicolalazzari.ai—including articles, guides, case studies, Q&A entries, pricing information, and consulting pages. Instead of rel...
Choosing the Right LLM
Selecting a large language model starts with your constraints: cost, latency, brand voice, and compliance. The goal is to match the model’s strengths to the job, not chase the newest release.
Evaluation rubric
- Use case clarity. Lis...
What is RAG?
Retrieval-Augmented Generation (RAG) combines two building blocks: a search step that pulls in trusted information and a generation step that writes the response. Instead of asking an LLM to invent an answer from memory, you give it the exact context it needs.