Supervised Fine Tuning - Starter Pack Agentic AI Solution using ADK

[suddhasatwabhaumik]

As enterprise needs grow more sophisticated, standard prompting techniques are proving insufficient for complex scenarios. This has elevated the importance of fine-tuned Large Language Models (LLMs) for specialized tasks like nuanced Text-to-SQL generation and advanced conversational systems. However, the iterative and resource-intensive nature of fine-tuning presents a significant bottleneck to rapid deployment.

To address this, we propose the creation of an Autonomous Fine-Tuning Agent, built using the Agent Development Kit (ADK) on Google Cloud. This agent reimagines the model customization workflow by moving from a manual, step-by-step process to a goal-oriented, autonomous system. Instead of a user-driven tool, this agent leverages an AI-native approach to manage the entire fine-tuning lifecycle. The core of this agent is a reasoning engine, like Gemini, that plans and executes a series of tasks to achieve a desired outcome.

The process begins with an AI engineer or client providing the agent with a high-level objective, such as achieving a target accuracy for a specific task. The user equips the agent with a small seed set of 20-50 examples and a ground truth dataset for evaluation. From there, the agent operates autonomously, using a suite of specialized tools:

• Synthetic Data Generation: The agent intelligently analyses the seed data and determines the optimal strategy for generating a high-quality, scaled-up dataset of thousands of examples.
• Supervised Fine-Tuning (SFT): It programmatically initiates the fine-tuning job on a user-selected base model, such as Gemini Flash.
• Automated Evaluation & Iteration: Upon completion, the agent evaluates the new model against the ground truth dataset. Critically, it then analyzes the results. If the desired accuracy is not met, the agent autonomously decides on the next steps—whether to generate more diverse synthetic data, refine the existing set, or attempt another fine-tuning run. This iterative loop continues until the agent's goal is achieved or human intervention is requested.

By packaging this intelligence into an agent built on the ADK on Google Cloud, we empower our teams and clients to delegate the complex engineering loop of fine-tuning. The user interface transforms from a control panel into a dashboard for monitoring the agent's progress and reviewing its final, comprehensive report. This agentic framework dramatically accelerates the development of highly accurate, custom AI models, making production-grade GenAI more accessible and efficient.