Demo Team•February 28, 2024•8 min read
How to Build AI Agents That Actually Work for Business
A practical guide to building reliable AI agents using LLMs, RAG, and tool use — without the hype.
## The Problem with Most AI Agents
Most AI agent demos look great on stage but fail in production. Here's why, and how to fix it.
## Start with Clear Scope
An agent that does one thing well beats an agent that tries to do everything. Define the exact task boundary before writing a line of code.
## RAG Is Your Knowledge Layer
Retrieval-Augmented Generation lets your agent access company-specific knowledge without fine-tuning. Build a good retrieval pipeline first.
## Tool Use Over Reasoning
Give your agent specific tools (database queries, API calls, web search) rather than relying on pure LLM reasoning. Tools are reliable; reasoning is not.
## Evals Are Non-Negotiable
Build an evaluation suite from day one. If you can't measure your agent's accuracy, you can't improve it.