Better AI performance starts with your agent loop

Most people focus on picking the best AI model to get good results. Recent tests prove that the way you build your agent loop is actually more important. A simple model can beat a powerful one if your technical setup is better.

Changing the code that controls the agent can move it from the bottom of the rankings to the top. The quality of your output depends on the structure of the loop rather than just the underlying intelligence. This shift changes how companies should approach development.

Engineers now have three clear ways to run these loops. Each method comes with different costs and hardware requirements. Choosing the right path will help you save money while getting much more reliable work from your tools.