Spring AI Agentic Patterns (Part 5): Building Interoperable Agents with the Agent2Agent (A2A) Protocol

Engineering | Ilayaperumal Gopinathan | January 29, 2026 | ...

The Agent2Agent (A2A) Protocol is an open standard for seamless AI agent communication. It enables agents to discover capabilities, exchange messages, and coordinate workflows across platforms—regardless of their implementation.

Spring AI A2A integrates the A2A Java SDK with Spring AI through Spring Boot autoconfiguration. It seamlessly connects the A2A protocol with Spring AI's ChatClient and tools, enabling you to expose your agents as A2A servers.

This post is part of the Spring AI Agentic Patterns series. While previous posts covered making individual agents more capable (Agent Skills, AskUserQuestionTool, TodoWriteTool, Sub-agent orchestration), this post shows how the A2A Protocol enables agents to…

Anthropic Agent Skills Support in Spring AI

Engineering | Soby Chacko | January 28, 2026 | ...

In this blog, we show how using Spring AI, we can integrate with Anthropic's Native Skills API for Cloud-Based Document Generation and Custom Skills.

Spring AI adds support for Anthropic's Agent Skills — modular capabilities that let Claude generate actual files rather than text descriptions. With Skills enabled, Claude produces real Excel spreadsheets, PowerPoint presentations, Word documents, and PDFs that you can download and use directly.

This post covers how Spring AI integrates with Skills, including both pre-built Skills and Custom Skills for organization-specific document generation.

Spring AI Agentic Patterns (Part 4): Subagent Orchestration

Engineering | Christian Tzolov | January 27, 2026 | ...

Instead of one generalist agent doing everything, delegate to specialized agents. This keeps context windows focused—preventing the clutter that degrades performance.

Task tool, part of the spring-ai-agent-utils toolkit, is a portable, model-agnostic Spring AI implementation inspired by Claude Code's subagents. It enables hierarchical agent architectures where specialized subagents handle focused tasks in dedicated context windows, returning only essential results to the parent. Beyond Claude's markdown-based format, the architecture is extensible—supporting A2A and other agentic protocols…

This Week in Spring - January 27th, 2026

Engineering | Josh Long | January 27, 2026 | ...

Hi, Spring fans! Welcome to another installment of This Week in Spring! As I write this, I cannot believe we're nearly at the end of the month! Time sure flies.

Spring AI Agentic Patterns (Part 3): Why Your AI Agent Forgets Tasks (And How to Fix It)

Engineering | Christian Tzolov | January 20, 2026 | ...

Have you ever asked an AI agent to perform a complex multi-step task, only to find it skipped a critical step halfway through? You're not alone.

Research shows that LLMs struggle with "lost in the middle" failures—forgetting tasks buried in long contexts. When your agent juggles file edits, test execution, and documentation updates, important steps can silently disappear. One solution, inspired by Claude Code, is to make planning explicit and observable with the help of a dedicated TodoWrite tool. The result: agents that never skip steps and workflows you can observe in real-time.

This is Part 3 of our Spring AI Agentic Patterns series. We've covered Agent Skills for modular capabilities and AskUserQuestionTool for interactive workflows. Now we explore how TodoWriteTool

This Week in Spring - January 20th, 2026

Engineering | Josh Long | January 20, 2026 | ...

Hi, Spring fans! Welcome to another installment of This Week in Spring! It's already the 20th of January and we are off on yet another rip roarin' adventure as we look at the week that has been... this week in Spring!

Spring AI Agentic Patterns (Part 2): AskUserQuestionTool - Agents That Clarify Before Acting

Engineering | Christian Tzolov | January 16, 2026 | ...

Traditional AI interactions follow a common pattern: you provide a prompt, the AI makes assumptions, and produces a response. When those assumptions don't match your needs, you're left iterating through corrections. Each assumption creates rework—wasting time and context.

What if your AI agent could ask you clarifying questions before providing answers?

The AskUserQuestionTool addresses this. It allows the AI agent to ask clarifying questions before answering, gathers requirements interactively, and creates a specification aligned with your actual needs from the start.

Spring AI's…

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