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Notes from the engineering floor. Ideas, decisions, and lessons from building things that have to work in the real world.

AI Engineering12 min read

What is RAG? Complete Guide to Retrieval-Augmented Generation (2025)

RAG (Retrieval-Augmented Generation) grounds LLMs in your private data. Learn how RAG works, when to use it, its architecture, costs, and when fine-tuning is a better choice.

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6 articles found

AI Engineering / 12 min read

What is RAG? Complete Guide to Retrieval-Augmented Generation (2025)

RAG (Retrieval-Augmented Generation) grounds LLMs in your private data. Learn how RAG works, when to use it, its architecture, costs, and when fine-tuning is a better choice.

AI Engineering / 10 min read

RAG vs Fine-Tuning: Which Does Your AI Application Need?

A definitive technical comparison of RAG vs fine-tuning. When to use each, when to combine them, costs, trade-offs, and real-world examples from production AI systems.

AI Engineering / 14 min read

How to Build an AI Agent: Complete Developer Guide 2025

A complete technical guide to building AI agents from scratch: architecture, tool use, memory, orchestration frameworks (LangChain, LangGraph, CrewAI), and production deployment.

Business / 9 min read

AI Development Cost in 2025: RAG, Agents & LLMs Pricing Guide

Transparent pricing guide for AI development in 2025. What does it actually cost to build a RAG system, AI agent, fine-tuned model, or full AI product? Real numbers from production projects.

AI Engineering / 11 min read

Best Vector Databases for AI Apps: Pinecone vs Weaviate vs Qdrant vs pgvector (2025)

A technical comparison of the top vector databases for AI applications in 2025: Pinecone, Weaviate, Qdrant, Chroma, and pgvector. Performance, cost, features, and when to use each.

Business / 8 min read

How to Hire an AI Development Company: 10 Questions to Ask Before You Sign

A founder's guide to hiring an AI development company. The 10 questions you must ask, red flags to avoid, what good looks like, and how to evaluate technical credibility.