Why We Chose Deterministic Workflows Over Autonomous Agents

Maya Shavin

Published author, international speaker and an open-source library maintainer of frontend and web projects

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Autonomous agents are exciting, but not always the right solution. When we build our agent system to migrate complex legacy PDF forms to structured business workflows, an autonomous agent seemed to be the obvious choice.

Except it wasn’t. The system outputs were inconsistent, difficult to validate, hard for users to trust, and expensive. To fix this, we redesigned the system around deterministic workflows, using AI only where it adds clear value.

In this session, I'll walk through the architectural evolution of our PDF-to-Workflow AI system, the lessons learned from what failed, how it helped to reduce migration time by 90% and the engineering tradeoffs that led us to a more reliable production-ready architecture framework.

You'll leave with practical patterns for designing trustworthy AI systems, understanding when deterministic workflows outperform autonomous agents, and building AI products that users are willing to adopt.

This talk has been presented at AI Coding Summit NYC, check out the latest edition of this Tech Conference.

architecture

Maya Shavin

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