AgentKit vs Claude 3: Which AI agent builder is right for you in 2025?

So, you're looking to build an AI agent. The race is definitely on, but if you're like most developers, you're standing at a fork in the road. In one direction, you have OpenAI's all-in-one AgentKit. In the other, there’s Anthropic's flexible Claude Agent SDK, powered by their impressive Claude 3 models.

Both promise to help you build powerful agents that can get real work done, but they're built on entirely different ideas. We've all been there, choosing a framework only to realize months later that it wasn’t the right fit. Picking the wrong path here can lead to wasted development time, unexpected costs, and an agent that just doesn't meet your needs.

This guide breaks down the key differences in the AgentKit vs Claude 3 debate. We'll compare their architecture, features, and ideal use cases to help you make a solid decision. We'll also explore a third path for teams that need to deploy production-ready support agents without a massive engineering project.

What are AI agent builders?

First things first, let's make sure we're on the same page. An AI agent builder, or framework, is basically a toolkit that helps developers create AI systems that can perform tasks, use other software, and interact with data on their own. We're not talking about simple chatbots that just spit back canned answers. These are frameworks for building complex, multi-step workflows that can reason, plan, and actually act.

What is OpenAI AgentKit?

AgentKit is OpenAI's attempt at a unified, productized platform for building agents. The main idea is to give you a visual, low-code environment to quickly prototype and deploy customer-facing agents. It packs a visual canvas (Agent Builder), ready-to-use UI components (ChatKit), and evaluation tools into a single package. You can think of it as a complete operating system for agents, where OpenAI handles most of the infrastructure for you.

What is the Claude Agent SDK?

On the other hand, the Claude Agent SDK is a code-first, developer-focused toolkit from Anthropic. It's an SDK that gives you fine-grained control to build agents that run in your own infrastructure, powered by the latest Claude 3 models like Sonnet and Opus. It's all about modularity, security, and enterprise control. Think of it as a powerful engine and a chassis; you get complete freedom to build the car you want, but you're the one who has to put it all together.

Core philosophy: Platform vs. framework

The biggest difference between AgentKit and the Claude Agent SDK isn't just a single feature, it's their entire approach. It's the classic battle of a managed platform versus a flexible framework.

OpenAI AgentKit's approach: The all-in-one product

AgentKit is designed to keep you inside the OpenAI ecosystem. It's a centralized platform that has strong opinions on how things should be done, which makes it great for getting things done quickly, especially for teams that include non-engineers like product managers and designers. The main selling point here is speed. The visual builder and pre-built components mean you can get a prototype up and running in a few hours, not weeks.

But that speed comes with trade-offs. This all-in-one approach means you have less control over the underlying infrastructure, which can lock you into their models. If you need to build complex, non-standard integrations or have strict data residency rules, you might find the platform's guardrails a bit confining.

Claude Agent SDK's approach: The composable toolkit

Anthropic went in the opposite direction. The Claude Agent SDK is designed to be a component you plug into your existing systems. It's decentralized and built for developers first, which means you control the execution environment, the data, and the security protocols.

The main benefit here is control. For businesses with strict compliance needs or data privacy requirements (like running agents on-premise), this isn't just a nice-to-have, it's a must. You have the freedom to build exactly what you need, exactly how you need it. The catch? It requires a lot more engineering work. Your team is on the hook for wiring everything together, managing the infrastructure, and building the entire user interface from scratch.

Feature showdown: AgentKit vs Claude 3

Alright, let's get into the practical features that you and your team will actually be using. While both frameworks are powerful, they're geared toward very different workflows and team setups.

Feature	OpenAI AgentKit	Claude Agent SDK (with Claude 3)	The Bottom Line
Primary Interface	A visual, drag-and-drop "Agent Builder" canvas.	Code-first, using Python/TypeScript SDKs.	AgentKit is better for mixed-skill teams; Claude SDK is built for engineers.
Tool Integration	Built-in tool nodes and a curated "Connector Registry."	You define tools explicitly in code using the MCP protocol.	AgentKit is faster for standard tools; Claude SDK gives you more power for custom jobs.
UI Components	"ChatKit" library with 21 pre-built embeddable widgets.	None. You build the whole front-end yourself.	AgentKit is the clear winner for any customer-facing chat experience.
Execution Environment	Runs on OpenAI's managed infrastructure.	Runs in your own environment (local, on-prem, or private cloud).	Claude SDK is the go-to for data-sensitive or regulated industries.
Evaluation & Testing	Has integrated evaluation tools for grading agent performance.	You need to build or integrate your own testing setup.	AgentKit makes the quality assurance process a bit easier to get started with.

AgentKit's visual builder makes it possible for non-developers to help map out workflows, and its ChatKit library is a huge time-saver for anyone building a customer-facing chatbot. You can get a polished, embeddable chat experience without having to write a mountain of front-end code.

The Claude Agent SDK, however, basically hands developers the keys to the entire car. Its reliance on code means you can build incredibly powerful, custom tools that integrate deeply with your company’s internal systems. This is where it really excels, especially for complex, backend-heavy tasks where a slick UI isn't the main goal.

AgentKit vs Claude 3 use cases and the hidden work of building support agents

With these differences in mind, how do you actually choose? It really comes down to what you're trying to build.

When to choose OpenAI AgentKit

AgentKit is a great choice for rapidly building and deploying customer-facing chatbots, simple internal tools, and prototypes where the user interface is a top priority. For instance, a SaaS company that wants to add a documentation chatbot to their website would find AgentKit's visual builder and pre-made UI components incredibly useful.

When to choose the Claude Agent SDK

The Claude Agent SDK is better suited for building agents with deep, custom integrations into internal systems, tasks that require high security and data privacy, and complex, engineering-heavy projects. A financial services company building a code analysis agent that has to run securely within its own VPC and access private databases would need the control and flexibility the Claude SDK provides.

The reality of building for customer support

While both frameworks are powerful, they are general-purpose tools. Building a customer support agent that actually works well involves a lot more than just connecting a model to a few APIs. This is where a lot of teams get stuck, realizing too late that the framework was just the first step of a very long journey.

Here are a few of the headaches you'll likely run into:

• The "cold start" problem: Neither framework can learn from your team's past conversations right out of the box. You're responsible for manually building and maintaining a knowledge base from scratch, which is a huge and never-ending project.

• No confidence engine: How can you be sure your agent will perform well on your specific customer questions before it goes live? Building a reliable simulation environment to test your agent against your historical data is a pretty big engineering challenge on its own.

• Missing support-specific workflows: Core support functions like smart ticket triage, sentiment analysis, or knowing when to escalate to the right human aren't built-in. You have to code all of this logic from the ground up.

• The hidden costs: The cost isn't just about API calls. It's the months of developer time spent building, testing, and maintaining the agent, plus the ongoing operational work of keeping it running smoothly.

A better way: The specialized platform for support automation

Instead of starting from zero with a general-purpose developer framework, you could use a specialized platform that's already designed for support automation. This is where tools like eesel AI come into the picture.

The idea is simple: eesel AI gives you the outcomes you're trying to build with AgentKit or the Claude SDK, but without the months of development and hidden problems.

It directly addresses the limitations of a do-it-yourself approach:

• It solves the cold start: eesel AI connects to your helpdesk and instantly learns from your past tickets, macros, and knowledge sources. There's no manual training; it understands your business context from day one.

• You can test with confidence: It includes a powerful simulation mode that tests your AI on thousands of your historical tickets. This gives you an accurate, data-backed resolution rate before you ever turn it on for customers.

• It's built for support: Workflows for triaging tickets, taking actions in your helpdesk (like tagging or closing), and escalating to human agents are all part of the platform's no-code workflow engine.

• You can go live in minutes: Because it's a fully self-serve platform with one-click integrations for tools like Zendesk, Intercom, and Freshdesk, you can have a working AI agent up and running in minutes, not months.

Build vs. buy: What's right for you?

So, what's the final call in the AgentKit vs Claude 3 matchup?

OpenAI's AgentKit offers incredible speed and a great user interface right out of the box, making it perfect for rapid prototyping and polished chat experiences. The Claude Agent SDK provides the deep control and security needed for complex, enterprise-grade projects where you need to own the entire stack.

Both are excellent frameworks for building general-purpose AI agents from the ground up. However, if your goal is to launch a high-performing agent for customer support, the question changes from "which framework should I use?" to "should I be building this from scratch at all?"

For teams that need to automate support now, a specialized platform like eesel AI offers a faster, more reliable, and ultimately more cost-effective solution by handling all the hard parts for you.

Ready to see what a purpose-built AI support agent can do? Try eesel AI for free and you can deploy your first agent in under 5 minutes.