Tool design is all you need for SOTA SWE agents
Building reliable AI agents is hard, but it does not have to be. One of the critical concerns for large-scale adoption is their reliability and the difficulty of building agents that deliver in the real world. After building over a hundred integrations for AI agents and talking to many builders, we’ve realized that creating reliable AI automation takes more than just powerful large language models.
Reliable coding agents need precise and efficient tools to interact with development environments, manage codebases, and implement changes accurately. Our experiment shows that tool design significantly impacts agent reliability, often the key differentiator between successful and unsuccessful implementations.
Instead of just tools, providing Coding agents with an IDE with code intelligence features like code completion and secure development containers can improve the agent’s performance.
We achieved notable performance gains by deploying multiple specialized agents, each focused on specific tasks rather than relying on a single generalist agent.
