Building a multi-step AI agent in Java with Spring AI 2.0

Short summary

Spring AI 2.0 enables dynamic multi-step agentic workflows where an LLM autonomously chains tool calls without hardcoded orchestration logic. This tutorial demonstrates a civic research assistant that coordinates postcode resolution, MP lookup, bill search, and voting record retrieval—with each step feeding structured data into the next decision point. The implementation includes a guardrail that verifies every citation against actual tool outputs to prevent hallucination; complete runnable code and Spring AI 1.x→2.0 migration guide provided.

• •Spring AI 2.0 supports dynamic multi-step agents where LLM chains tool calls without hardcoded flow orchestration
• •Real-world example: civic research assistant coordinates five tools to research UK parliamentary issues
• •Includes hallucination prevention guardrail—every citation verified against actual tool outputs

Generated with AI, which can make mistakes.