Context and Background:
Small Language Models (SLMs) are increasingly practical for real-world developer workflows. Unlike large models that require heavy compute, SLMs are lightweight, cost-efficient, and can run in production environments with minimal overhead. Developers often capture notes, tasks, or meeting summaries in plain text, but struggle to consistently format them into clean documentation. This session shows how SLMs, combined with Google’s Agent Development Kit (ADK) and Cloud Run, can be used to build an Intent-to-Docs agent that automatically formats natural language into Markdown, making documentation faster and more reliable.

Session Abstract:
This session demonstrates how to build and deploy a production-grade ADK agent on Cloud Run that converts free-form text into structured Markdown documentation. By leveraging small language models (SLMs) and focusing on deployment patterns, attendees will learn how to operationalize lightweight AI agents built with Gemma in real-world developer environments. The workshop highlights service configuration, backend integration with ADK, validation via the ADK interface, and scaling under load.

What the Session Covers:
* Introduction to ADK and its role in building agents
* Overview of Small Language models and the Google's Gemma family
* Overview of Cloud Run as a serverless deployment platform
* Implementing an Intent-to-Docs agent that formats natural language into Markdown
* Deploying the agent to Cloud Run and Validating interactions with the ADK interface
* Running load tests and observing Cloud Run autoscaling behavior

Key Takeaways:
* Understand how to build and deploy agents using the Agent Development Kit (ADK)
* Learn how Cloud Run simplifies deploying and scaling AI-powered services
* See a practical application of an agent built with Gemma for documentation and developer productivity
* Gain insights into production deployment patterns such as autoscaling, environment configuration, and API testing