Guide: Building Your First Multi-Step AI Agent with Gemini 3 Pro’s New API

Par /

At AIWiner, we don’t just talk about the future of AI; we show you how to build it. The release of Gemini 3 Pro (preview) brings with it powerful, native agentic capabilities, making it easier than ever to create robust, multi-step automation workflows. This guide is your blueprint. We will walk through the architecture required to leverage Gemini 3 Pro’s planning and tool-use features to build an AI agent that can handle complex, sequential tasks in an enterprise setting.

🛠️ I. Agent Architecture: The Gemini 3 Pro Loop (H2)

Building a truly autonomous agent requires more than a simple API call. The new capabilities of Gemini 3 Pro simplify the « brain » of the agent, but the surrounding architecture is key.

  • The Three Core Components:
    1. The Goal Setter (Input): Defining the complex, non-linear task (e.g., « Onboard a new vendor by creating their profile, sending initial paperwork, and notifying the finance team »).
    2. The Gemini 3 Pro Planner (Core): This is where the model shines. It interprets the goal, breaks it down into sequential sub-tasks, and determines which external Tools (APIs) are needed for each step.
    3. The Executor (Output/Action): A wrapper function that takes the model’s planned action (e.g., Tool: create_vendor_profile(name="...", docs="...")) and executes it against your internal systems (CRM, ERP, etc.).

🔗 II. Defining and Integrating Custom Tools (H2)

Gemini 3 Pro’s enhanced reasoning is only as good as the tools you give it. Your agent’s success depends on clearly defining the functions it can call.

  • API Schema Definition: You must present your internal APIs (for sending emails, updating databases, fetching reports) to the Gemini 3 Pro model in a structured format (usually JSON schema). This allows the model to « reason » about which function is most appropriate for the current sub-task.
  • Example Tool:

Tool Name: onboard_vendor Description: Creates a new vendor entry in the Finance ERP system. Parameters: vendor_name: string, tax_id: string

The agent’s intelligence now allows it to choose and format the correct inputs for this tool based on its current context.

💡 III. Real-World Use Case: Automated Due Diligence (H2)

Consider a task critical to compliance: automated due diligence.

  1. The Goal: « Verify all background documentation and financial statements for Vendor X and flag any discrepancies. »
  2. Gemini’s Steps:
    • Step 1: Use file_reader_tool to analyze the text and figures in the uploaded PDF financial statements (Multi-Modal input).
    • Step 2: Use search_api tool to cross-reference the vendor’s name against public sanction lists.
    • Step 3: Use Internal Reasoning to compare the data points.
    • Step 4: Use notification_tool to send an alert to the legal team if a discrepancy is found.

This demonstrates the powerful combination of Multi-Modal understanding, Tool Use, and Agentic Planning—all key strengths of Gemini 3 Pro.

🚀 IV. Elevate Your Enterprise Automation (H2)

The shift to Gemini 3 Pro’s agentic capabilities is not just a technical upgrade; it’s a strategic move to unlock true end-to-end automation. Start small, define clear tools, and let the model handle the complex orchestration.

To understand the core multi-modal technology that powers the reasoning capabilities of Gemini 3 Pro, make sure to read our definitive guide: [Gemini Explained: The Multi-Modal AI That’s Redefining Automation and Enterprise] (Ceci est le lien interne vers l’Article Pilier).

Retour en haut