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 .
Your Agent’s Tools Can Make Decisions, Too
The article titled "Your Agent’s Tools Can Make Decisions, Too" discusses decision models as tools and offers a hands‑on guide for their implementation. It highlights how agents can leverage these tools to make informed choices. The post was originally published on Towards Data Science.
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Towards Data Science
Jun 21
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 .
Towards Data Science
Sep 21
A New Kind of Model for AI Decision-Making?
Exploring TypeSafe's Jev and comparing it with OpenAI on intent classification The post A New Kind of Model for AI Decision-Making? appeared first on Towards Data Science.
Towards Data Science
Oct 9
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.
Towards Data Science
Oct 2
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
Sep 3
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.
Towards Data Science
4d ago
Let Decision Models Watch Your Agents
Let Decision Models Watch Your Agents is a hands‑on guide that explains how to detect behavioral anomalies by analyzing an agent’s evolving execution history. The article provides practical steps and techniques for monitoring agent behavior over time. It is published on Towards Data Science.
Towards Data Science
Oct 11
A Practical Guide to OpenAI's New Decisions API
The article titled "A Practical Guide to OpenAI's New Decisions API" was published on Towards Data Science. It poses the question, "Is this the JEV killer?", suggesting a discussion about the impact of OpenAI's new Decisions API. The post appears to explore practical aspects of using this API and its potential significance.
Towards Data Science
Jun 17
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.
Towards Data Science
Jul 13
Agentic RAG: Let the Agent Search
A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science .
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.
Towards Data Science
Sep 22
An Introduction to Jev
The article titled "An Introduction to Jev" discusses an AI system that focuses on making decisions rather than generating text. It highlights Jev’s unique approach to decision-making within the broader context of AI development. The piece was originally published on Towards Data Science.