Demo Team•February 28, 2024•1 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.