Towards Data Science

Where the Agent Development Lifecycle Fits

The article "Where the Agent Development Lifecycle Fits" discusses how to coordinate the development of agent capabilities with the applications they power. It highlights the importance of aligning agent creation processes with the needs of the end‑use cases they support. The piece appears on Towards Data Science and focuses on integrating agent development into broader application workflows.

Towards Data Science
Aug 4

Using Agents as Tools

Building manager–specialist workflows with the OpenAI Agents SDK The post Using Agents as Tools appeared first on Towards Data Science .

By Shuai Guo
Towards Data Science
Aug 28

From One Agent to a Team: Understanding Codex Subagents

The article "From One Agent to a Team: Understanding Codex Subagents" offers a practical guide on how to create specialist agents and manage their collaboration using the Codex Command Line Interface. It explains the process of defining subagents and coordinating their tasks to build a cohesive team of AI agents. The guide is aimed at developers looking to extend Codex’s capabilities through modular, specialized agent workflows.

By Shuai Guo
Towards Data Science
Aug 27

How to Work with AI Coding Agents

The article "How to Work with AI Coding Agents" offers a practical guide aimed at improving code quality rather than merely increasing quantity. It focuses on strategies and best practices for effectively collaborating with AI coding tools to produce better code. The post was originally published on Towards Data Science.

By Sara A. Metwalli
Towards Data Science
Aug 30

8 Tips for Writing Effective Agent Instructions

The article "8 Tips for Writing Effective Agent Instructions" offers quick and simple guidance to improve the clarity and effectiveness of instructions given to agents. It presents a concise set of practical tips aimed at helping readers craft better agent instructions. The post is published on Towards Data Science.

By Payal Patel
Towards Data Science
Aug 18

From Prototype to Production: The Architecture Behind Secure & Governed AI Agents

The article discusses how to transition AI agents from prototype to production by implementing responsible AI practices, security measures, and governance frameworks suitable for enterprise use. It outlines the necessary architectural layers that ensure these agents operate safely and comply with organizational policies. The focus is on building robust, secure, and governed AI systems that can be reliably deployed in business environments.

By Partha Sarkar
Towards Data Science
Aug 18

Building Enterprise Agent Systems that People can Trust, Verify and Improve

The article outlines five principles that guide the successful deployment of enterprise agent systems, illustrated with a real-world example from a $100M+ company. It explains how these principles help ensure that such systems can be trusted, verified, and improved over time. The post serves as a practical guide for building reliable agent-based solutions in production environments.

By Sheila Teo