How to Govern AI Agents

What AI Agents Should Never Do on Their Own

How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .

How to Design Architectural Guardrails Around AI Agents

The article "How to Design Architectural Guardrails Around AI Agents" discusses essential agent design patterns that data engineers should understand. It emphasizes the importance of establishing clear architectural boundaries to ensure AI agents operate safely and effectively within larger systems. The post was originally published on Towards Data Science.

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.

How to Build a Control Plane for AI Agents

The article titled "How to Build a Control Plane for AI Agents" outlines a nine-step process for granting a large language model (LLM) permission to act. It focuses on the practical steps involved in creating a control plane that manages the actions of AI agents. The post was originally published on Towards Data Science.

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.

The Big Con of Agentic AI

What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .

How to Solve the Right Problem in the Age of Agentic AI

The article "How to Solve the Right Problem in the Age of Agentic AI" presents a practical framework aimed at reducing uncertainty before agents accelerate implementation. It offers guidance on identifying and addressing the most relevant problems in the context of increasingly autonomous AI systems.

Using Classical ML to Empower AI Agents

On the value of building on existing foundations The post Using Classical ML to Empower AI Agents appeared first on Towards Data Science .

Practices for Governing Agentic AI Systems

Build Your First AI Agent with One Tool Call

The article titled "Build Your First AI Agent with One Tool Call" introduces beginners to AI agents, presenting the first part of a series. It focuses on the foundational steps required to create an AI agent using a single tool call. The post is published on Towards Data Science and serves as an introductory guide for newcomers to the field.

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.

Your Agent Doesn't Need More Freedom

The article titled "Your Agent Doesn't Need More Freedom" discusses how agents have become proficient, but the real challenge lies in the surrounding environment. It highlights that the focus should shift from granting agents additional autonomy to addressing the complexities that exist around them. The piece underscores the importance of improving the context in which agents operate rather than simply increasing their freedom.