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Productionising GenAI Agents: Evaluating Tool Selection with Automated Testing

How to create reliable and scalable GenAI Agents for real-world applications

Heiko Hotz
TDS Archive
17 min readNov 22, 2024

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Image by author — created with Flux 1.1 Pro

Introduction

Generative AI agents are changing the landscape of how businesses interact with their users and customers. From personalised travel search experiences to virtual assistants that simplify troubleshooting, these intelligent systems help companies deliver faster, smarter, and more engaging interactions. Whether it’s Alaska Airlines reimagining customer bookings or ScottsMiracle-Gro offering tailored gardening advice, AI agents have become essential.

However, deploying these agents in dynamic environments brings its own set of challenges. Frequent updates to models, prompts, and tools can unexpectedly disrupt how these agents operate. In this blog post, we’ll explore how businesses can navigate these challenges to ensure their AI agents remain reliable and effective.

What is this blog post about?

This post focuses on a practical framework for one of the most crucial tasks for getting GenAI agents into production: ensuring they can select tools effectively. Tool selection is at the heart of how generative AI agents perform tasks, whether retrieving…

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

Heiko Hotz
Heiko Hotz

Written by Heiko Hotz

Generative AI Blackbelt @ Google — All opinions are my own

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