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Monday, June 29, 2026

BUILD MULTI-STEP AGENTS WITH GEMINI 3.5'S NEW ACTION CAPABILITIES

Gemini 3.5 enables more capable, multi-step AI agents.

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{"agent devs","AI product managers","startups","enterprise AI"}

What Happened

Google just rolled out Gemini 3.5, and the big headline for builders is its enhanced agentic capabilities, particularly its ability to execute multi-step actions. This isn't just about better chat; it means Gemini can now break down a complex request into smaller, sequential steps, use tools (APIs, internal systems) to perform each action, and orchestrate a multi-stage workflow. It's a significant move towards AI systems that can proactively "do" things, not just "say" things.

Why It Matters

This fundamentally changes the game for what you can build with LLMs. We're moving beyond static query-response cycles to AI that can autonomously interact with the real world, your software, and external services. For builders, this unlocks the ability to create truly intelligent agents that automate complex business processes, manage intricate data flows, or even act as sophisticated personal assistants. It means less hand-holding for AI and more robust, end-to-end automation possibilities.

What To Build

You should be building sophisticated workflow automation agents. Think an AI that can receive a customer support query, search your knowledge base, access the CRM to check customer history, draft a personalized response, and escalate to a human only if necessary – all in one go. Consider AI-powered personal assistants that integrate across your applications (calendar, email, project management) to truly manage your day, not just give you information. For developers, build agents that can interact with APIs, perform complex data transformations, and even orchestrate cloud infrastructure deployments based on high-level goals.

Watch For

Keep a close eye on the robustness and reliability of multi-step execution – edge cases are always tricky. Look for new agentic frameworks and tools that emerge specifically to leverage Gemini 3.5's action capabilities, simplifying orchestration. Also, monitor how Google addresses the safety and control mechanisms for these more autonomous agents; their ability to take actions introduces new risks.

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