Agent Bricks in Action: Automating Insurance Underwriting with a Supervisor Agent-Led Architecture

Sudhir_G — Tue, 19 May 2026 20:07:54 GMT

About three years ago, when Generative AI was still in its early stages, I worked on a commercial application for insurance underwriting. It was a Life Insurance Underwriting assistant built on an early version of GPT-4 (1106).

The design was simple. We relied on a single, carefully engineered prompt. Applicant details, underwriting guidelines, and decision logic were all embedded directly into that prompt, using CoT prompting. The model processed everything in one pass and returned a recommendation. There was no tool calling. No structured way to interact with data systems. No separation between reasoning, retrieval, and computation. Every improvement came down to refining the prompt and driving incremental gains in consistency.

Fast forward to today, and the way we build these systems looks very different. We can now break the problem into specialized components. Structured data can be queried through natural language using tools like Genie. Documents can be retrieved through a dedicated knowledge layer using Knowledge Assistant Brick. External signals can be pulled in through governed Unity Catalog functions and APIs. A supervisory agent can coordinate all of this, deciding what to call, when, and how to synthesize the results.

In this architectural shift, the focus moves from crafting a single prompt to designing a system of interacting components, each responsible for a specific part of the workflow.

In this blog, I walk through a practical implementation of that approach on Databricks, where a multi-agent supervisor automates a traditionally manual underwriting workflow, using Databricks Agent Bricks.

Blog link: https://lnkd.in/gSeQQ4KE

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Agent Bricks in Action: Automating Insurance Underwriting with a Supervisor Agent-Led Architecture