Put the Agent Inside the Workflow

You Probably Don’t Need an Agent Framework

Most LLM applications need a clear workflow, not an autonomous agent. Here's how to build one in plain Python.

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 .

Build an LLM Agent That Can Write and Run Code

A hands-on walkthrough of code execution with the OpenAI Agents SDK and Docker The post Build an LLM Agent That Can Write and Run Code appeared first on Towards Data Science .

From Local LLM to Tool-Using Agent

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science .

How to Give an LLM Agent a Browser

Building a browser-use agent with OpenAI Agents SDK and Playwright MCP The post How to Give an LLM Agent a Browser appeared first on Towards Data Science .

How to Apply Coding Agents to Non-Programming Tasks

Perform non-programming tasks with coding agents The post How to Apply Coding Agents to Non-Programming Tasks appeared first on Towards Data Science .

Put Your Own Logic Inside the Codex Agentic Loop

The article titled "Put Your Own Logic Inside the Codex Agentic Loop" discusses how to incorporate custom logic into Codex hooks, as described in the post on Towards Data Science.

How to Build a Powerful LLM Knowledge Base

Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on 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.

Introducing Agents.js: Give tools to your LLMs using JavaScript

Tool Calling, Explained: How AI Agents Decide What to Do Next

Understanding ow LLMs interact with the world around them, from returning data to taking action The post Tool Calling, Explained: How AI Agents Decide What to Do Next appeared first on Towards Data Science .

Empowering product development with an agentic workflow