WHY THE GREP LOOP IS COSTLY FOR AI AGENTS: HOW CODEGRAPH CHANGES THE WAY THEY SEARCH REPOSITORIES

AI coding agents are being adopted to speed up development and reduce development costs. But a significant share of the agent’s execution time and context window can be consumed not on solving the task, but on finding the right files and reconstructing the relationships between them. For a business, this means higher token usage and costs, longer execution times, and more developer time spent waiting for and reviewing the output. CodeGraph helps reduce these overhead: it immediately provides the agent with structurally connected context, reduces unnecessary searches and file reads, and allows it to move on to implementation sooner.