Gemini 3.5: From Chat to AI Agents – How Development Workflows Are Evolving

Gemini 3.5 Marks a Shift Toward Autonomous AI Agents

At Google I/O 2026 on May 19, 2026, Google unveiled its next-generation model, Gemini 3.5. The core of this update lies in the evolution from a chatbot that merely answers user queries to an autonomous "AI agent" capable of completing tasks independently.

The Gemini 3.5 family consists of two main models: Gemini 3.5 Flash, currently available for developers and enterprises, and Gemini 3.5 Pro, slated for rollout in June 2026. The enhancement of "Action" capabilities has made the automation of complex workflows a practical reality.

Unmatched Performance and Cost Efficiency

What developers should focus on is the speed and cost optimization achieved by Gemini 3.5 Flash. According to Google, Gemini 3.5 Flash is 4 times faster in output tokens per second compared to other frontier models and can reduce task completion costs by more than half.

In benchmarks, it shows superior performance over Gemini 3.1 Pro (based on Google's published data):

• Terminal-Bench 2.1: 76.2%
• GDPval-AA: 1656 Elo
• MCP Atlas: 83.6%
• CharXiv Reasoning (multimodal understanding): 84.2%

This enables the low-cost construction of real-time applications and large-scale agent workflows.

The Agent Ecosystem Accelerating Implementation

To fully leverage Gemini 3.5's capabilities, Google provides multiple platforms.

• Google Antigravity: An agent-first development platform and harness for deploying collaborative sub-agents.
• Gemini Spark: A personal AI agent powered by 3.5 Flash, operating 24/7, with a beta release planned in the United States.
• Others: Integration is being advanced through environments like Google AI Studio, Android Studio, and the Gemini Enterprise Agent Platform.

Concrete Enterprise Use Cases

Many enterprises are already integrating Gemini 3.5's "Action" capabilities into their operations. This is automating "workflows spanning weeks" and "complex document processing" that were impossible with traditional chat formats.

• Shopify: Uses parallel sub-agents to predict growth for merchants worldwide.
• Salesforce: Integrates 3.5 Flash into Agentforce to automate enterprise tasks with sub-agents.
• Xero: Deploys agents to manage long-term workflows, such as data collection for 1099 tax forms.
• Macquarie Bank: Pilots agents that reason over complex documents exceeding 100 pages to accelerate customer onboarding.
• Databricks: Builds agent workflows for data scientists with real-time information retrieval and diagnostic corrections.

Ensuring Safety and Reliability

For AI agents with autonomous actions, safety is a top priority. Gemini 3.5 was developed using the "Frontier Safety Framework," with enhanced guardrails for cyberattacks and CBRN (Chemical, Biological, Radiological, Nuclear) threats. Additionally, "Interpretability Tools" are implemented to analyze AI's internal reasoning before generating responses, aiming for transparent agent operations.

Conclusion

With the advent of Gemini 3.5, AI has transitioned from the stage of "knowing things" to "doing things." Particularly, the high-speed and cost-effective nature of 3.5 Flash will be a powerful tool for developers worldwide to design complex sub-agent structures and build practical AI agents.