At this point, we’re all aware of LLM-based coding assistants like GitHub Copilot or CodeWhisperer. But what about AI for API development? What tools are being developed to integrate large language models and artificial intelligence into the API space?

Applying AI within API development can mean several different things. Sometimes, it means using LLMs to generate tests. Other times, LLMs can make code suggestions — if not write your code outright. AI for APIs can translate natural language into technical formats like API documentation or API specifications like OpenAPI. AI for APIs is all of these things.

To give you an idea of the emerging AI landscape, we’ve pulled together five AI tools for working with APIs. These AI assistants are specifically designed to aid common API-related tasks, such as testing, linting, generating specifications, and more.

1. API Connect by IBM Watson

API testing is one of the most essential aspects of delivering safe, secure, fast, and reliable APIs. Considering that 60% of organizations that use APIs have experienced some form of API-related data breach in the last two years, as reported by The 2023 State of API Security: A Global Study on the Reality of API Risk, it’s safe to say that API testing is only going to become more critical to an API’s success and user retention rates. The same is likely true with API performance, which can also be measured by API testing.

The trouble is making API testing scalable. A testing process that works well when you have only ten APIs has a strong chance of being painfully slow when you have 10,000 APIs. Different applications have different needs, as well. Luckily, AI is uniquely suited for API testing scenarios.

API Connect by IBM Watson uses AI in a simple but ingenious way for API testing. It uses AI to generate thousands of API requests of all kinds in a matter of seconds. It then reports any conformance or server-side errors, which are displayed in a series of easy-to-understand graphs. Performance can be tracked over time, as well, giving you even more insight into API performance trends. It can also be implemented into continuous testing situations like DevOps or a CI/CD pipeline.

2. LintGPT

Writing code for every conceivable circumstance is highly complicated, very time-consuming, and probably not even possible. Even writing out specifications in everyday language can be daunting. Just think of how long some instruction manuals can be.

LintGPT is a tool for the Optic API documentation generator. It can automate the process of creating an API style guide in plain, everyday language. Saving time is just one reason why using AI for APIs can be so enormously helpful. It eliminates other errors, like spelling or grammar, while ensuring that elements are consistent across an entire API.

It can also assess your code, having been trained on large quantities of some of the best API designs out there. LintGPT also catches any breaking changes before they’re shipped, preventing downtime and subsequent damage to your reputation.

3. Postman’s Postbot

One of the main points of using APIs is to prevent repetitive and unnecessary tasks. AI is perfect for this, as LLMs operate by what they’ve seen before. They notice patterns and then replicate them at the speed of thought.

Postbot by Postman is one of the first AIs for APIs to fully take advantage of this feature. It replicates many of the most common API functions, such as making API calls or creating API documentation, preventing you and your development team from having to write the same code repeatedly.

Efficiency is always a selling point with API products. That’s barely scratching the surface of the impact AI could have on the API industry. Much like Postman, Postbot brings developers one step closer to describing an API in natural language and letting the AI take care of the technicalities. Postbot features powerful data visualizations to more easily understand API responses with no coding required. It’s one more important step toward less technically-minded people being able to design, implement, and utilize APIs.

4. Treblle’s Alfred

Treblle’s Alfred is another AI tool for APIs that converts natural language into technical know-how. In Afred’s case, it continually analyzes your API documentation, which allows the AI to create tests, SDKS, and integrations. It also functions as a chatbot, answering any questions you might have about an API.

Alfred doesn’t merely generate code from existing documentation. It can help you with the coding itself, thanks to intelligent code suggestions. Alfred can also suggest ways you can improve your code, offering code quality enhancements and effortless code collaboration. Like IBM Connect, Treblle’s Alfred can also generate test cases with one click. Like Postbot, Alfred has the potential to revolutionize the API industry with its ability to translate natural language into code and vice-versa.

Not only can Alfred prevent you from having to create your own API documentation from scratch, but it can also save developers from having to read complicated technical writing. Instead, you can simply ask Alfred, and it’ll explain what’s in the documentation in plain, everyday language.

5. Workik AI

We’ll close out our AI for API roundup with perhaps the most powerful tool of the batch. Workik AI is billed similarly to other AI tools on our list, like Alfred, generating API specifications from plain text in a matter of seconds. That’s just the start, though.

For one thing, Workik AI works with nearly every language and framework that deals with APIs that you can imagine. You can specify for an API spec to be written following OpenAPI standards, for example, or for something to be written in Python. You can also describe common patterns or functions, and Workik AI will generate the code in whatever language you want. It can also debug code once it’s been generated.

Once you’ve generated a REST API using Workik AI, you can easily integrate it into automated testing workflows, CI/CD pipelines, and DevOps situations.

Closing Thoughts on AI Assistants for API Developers

AI assistants are radically disrupting every aspect of the way we conduct business. The way we write code and come up with schemas should be no exception. AI for APIs stands to be a liberatory force in the industry, letting people with less technical experience take advantage of all that APIs have to offer while simultaneously ensuring those APIs are secure and performing at optimal efficiency.

We’re bound to see a landslide of new AI tools for APIs in the very near future, so it’s important to start assembling your toolkit now before the hype train makes it hard to tell what’s worthwhile and what isn’t. These five AI tools for APIs are worthy of your time and investigation.