Agents in Production: How OpenGov Built and Scaled OG Assist - Gabe De Mesa, OpenGov
Jun 26, 2026 · 18:30
Gabe De Mesa of OpenGov explains how the company built and scaled OG Assist, an AI agent embedded across its government ERP products, using the Effect TypeScript library for full control over the agent loop and adopting Google's A2A protocol for agent-to-agent communication. The team moved from LangGraph to a custom Effect-native loop to gain fine-grained control over tracing, error handling, and structured concurrency. They implement feedback and automated evals with thumbs-up/down and CI checks, human-in-the-loop approvals for mutating tool calls, and sandboxed code execution to keep production safe. Long conversations are managed via rolling summarization with memory recall. Observability comes from Effect's built-in tracing, enabling bottleneck profiling. Tools and skills are built as Effect toolkits, and internally OpenGov uses Claude and Cursor to accelerate development workflows.
