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20 Questions for Your Agentic Enterprise (and How to Answer Them)

By · July 7, 2026

Quick answer

Navigate the agentic enterprise with 20 essential questions covering build, scale, optimize, and govern phases. Google's Agent Platform helps you answer them.

If you’re an IT leader, you’re probably fielding a flood of questions about building and deploying AI agents. The pressure to move fast is real, but the engineering reality is a tangled swamp of disconnected tools, security risks, and runaway costs. Where do you even start?

That’s where Gemini Enterprise Agent Platform comes in. It gives your teams a unified destination to build, scale, govern, and optimize agents—without drowning in complexity. We’ve gathered 20 essential questions to ask your engineering teams, with practical advice and code examples to get you going.

The Build Phase: Laying the Foundation

#0 Who is building the application?

Before choosing a tool, know who’s doing the work. With vibe coding, anyone—from engineers to legal teams—can build agents. The ecosystem spans no-code business experts, low-code assemblers, and high-code engineers. Pick a platform that empowers all three without siloing data or security.

#1 Where should my developers start?

Start by empowering your builders with specialized AI tools like coding agents. But most coding agents are isolated—they can’t see your live databases or docs. Use Google Antigravity as your primary harness, then integrate extensions:

#2 Who are we building for? Humans or other agents?

Decide early. For humans, focus on UX—use the Gemini Enterprise app or Agent-to-User Interface (A2UI). For agents, focus on interoperability with the open Agent2Agent (A2A) protocol.

#3 Which agent development tool should I use?

We see agent development as a four-rung ladder:

#4 Should I start with one agent or many?

Start with a single, highly specialized agent. If it tries to do everything, accuracy drops and debugging becomes a nightmare. As workflows grow, graduate to a multi-agent system using ADK.

The Scale Phase: Connectivity and Interoperability

#5 How do we connect enterprise data?

Use open standards like Model Context Protocol (MCP) to connect agents to live databases. But also organize data with clear business context to avoid hallucinations. See ADK and MCP Toolbox.

#6 How do we connect agents built on different frameworks?

Implement the A2A protocol for cross-framework connectivity. It allows agents built on LangGraph, ADK, or homegrown frameworks to communicate securely. See ADK and A2A.

#7 How do we help agents find the right tools?

Use focused agentic Skills that load capabilities on demand. Instead of a massive library, the agent pulls from a task-specific index card. See ADK and Skills.

#8 How do we deploy agents to scale?

Deploy within a fully managed, serverless execution environment like Agent Runtime. It offers elastic auto-scaling, containerized flexibility, and bidirectional streaming.

#9 What if agents lose context during long tasks?

Give them both short-term and long-term memory. ADK’s sessionService handles immediate steps, while Agent Memory Bank provides persistent storage.

The Optimize Phase: Trust and Efficiency

#10 How do we limit blast radius for agents running scripts?

Run untrusted code in a temporary, isolated sandbox. Agent Sandbox keeps it separate from core systems.

#11 How do I ensure my agent stays on-brand?

Use Guardrails—deterministic constraints outside the LLM’s reasoning that enforce safety rules. See Guardrails agent and ADK Workflows.

#12 How do we trust the result?

Automate evaluation with LLM-as-a-judge patterns. Use a more capable model to audit the primary agent’s output. See LLM-as-a-Judge.

#13 How do I control costs?

Use a tiered approach: lightweight models for simple tasks, open-source models like Gemma, and large reasoning models only for final decisions. Switch to Provisioned Throughput for steady traffic.

The Govern Phase: Security and Oversight

#14 How do I align agent data access with human users?

Use delegated authority—the agent inherits the user’s existing permissions. See Agent Identity.

#15 How do I manage shadow AI and agent sprawl?

Use a central Agent Registry to inventory all active agents, their owners, and permitted tools.

#16 How do I define interaction policies?

Apply IAM policies for boundaries and semantic policies that analyze intent in real time. See Policies.

#17 How do I enforce policies and gain visibility?

Route all traffic through an Agent Gateway that intercepts calls, blocks violations, and feeds telemetry to dashboards.

#18 How do I protect against data leakage and prompt injections?

Integrate Model Armor to intercept prompts and responses, enforcing security filters and sensitive data protection.

#19 How do I know if something goes wrong?

Use Agent Platform Threat Detection to flag anomalous behavior in near-real time.

#20 How can I manage the complete lifecycle in one place?

Use Agents CLI as the central command tool. It bridges local terminal work with production management, enabling version control, automated evaluations, and CI/CD integration.

By tackling these 20 questions early, you can build agents that do real work without keeping your security team up at night. Get started with Gemini Enterprise Agent Platform today.

Original announcement published on Google Cloud.