# Agents

DevFeed: [Agents](<https://devfeed.tech/articles/agents-31801.md>)

Original publisher: [Read original article](<https://huyenchip.com//2025/01/07/agents.html>)

Author: Chip Huyen

Published: 2025-01-07T00:00:00Z

Content type: article

Language: en

Sources: [Chip Huyen](<https://devfeed.tech/sources/chip-huyen.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Tool](<https://devfeed.tech/topics/tool.md>), [foundation-models](<https://devfeed.tech/topics/foundation-models.md>), [AI Engineering](<https://devfeed.tech/topics/ai-engineering.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-engineering](<https://devfeed.tech/tags/ai-engineering.md>), [foundation-models](<https://devfeed.tech/tags/foundation-models.md>), [tools](<https://devfeed.tech/tags/tools.md>)

## AI overview

This article provides an overview of intelligent agents, focusing on how foundation models enable agentic applications. It examines tools and planning as factors that shape agent capabilities, and discusses agent failure modes and evaluation. The author notes that the field is emerging and lacks established theoretical frameworks.

## Source excerpt

Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as "the study and design of rational agents." The unprecedented capabilities of foundation models have opened the door to agentic applications that were previously unimaginable. These new capabilities make it finally possible to develop autonomous, intelligent agents to act as our assistants, coworkers, and coaches. They can help us create a website, gather data, plan a trip, do market research, manage a customer account, automate data entry, prepare us for interviews, interview our candidates, negotiate a deal, etc. The possibilities seem endless, and the potential economic value of these agents is enormous. This section will start with an overview of agents and then continue with two aspects that determine the capabilities of an agent: tools and planning. Agents, with their new modes of operations, have new modes of failure. This section will end with a discussion on how to evaluate agents to catch these failures. This post is adapted from the Agents section of AI Engineering (2025) with minor edits to make it a standalone post. Notes: AI-powered agents are an emerging field with no established theoretical frameworks for defining, developing, and evaluating them. This section is a best-effort attempt to build a framework from the existing literature, but it will evolve as the field does. Compared to the rest of the book, this section is more experimental. I received helpful feedback from early reviewers, and I hope to get feedback from readers of this blog post, too. Just before this book came out, Anthropic published a blog post on Building effective agents (Dec 2024). I'm glad to see that Anthropic's blog post and my agent section are conceptually aligned, though with slightly different terminologies. However, Anthropic's post focuses on iso