Beyond SWE-bench: Enterprise Java AI Agents and Real-World Development Benchmarks

AI coding agents have matured to the point that they need to be seriously considered for enterprise Java development and general SDLC tasks. CLI Tools like Claude Code, Google’s Gemini CLI, Amazon Q Developer, and OpenAI’s assistants are examples from leading large AI labs, but there are also smaller startups and open-source options. These agentic coding tools can reason about architecture, grok large code bases, and hold great promise to help developers ship software faster. They are often used in a “human in the loop” style, but they can also be instructed to execute autonomously until they determine the goal has been completed.

This talk introduces Spring AI Agents. It provides a lightweight but powerful portable abstraction: the AgentClient. It acts as a consistent interface for invoking autonomous CLI-based agents. This allows developers to use the agentic tools they already have while providing flexibility to avoid locking into one single provider. It also introduces Spring AI Bench, a benchmark suite for evaluating agents on goal-directed enterprise-workflows. It evaluates how effectively different agents have completed their goals and can be considered the test harness that runs any agent via Spring AI Agents.

These autonomous tools represent a significant opportunity to offload routine, but complex, development tasks, allowing developers to focus on higher-level architecture decisions, creative problem-solving, and strategic technical leadership. May the best agent win!