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GenAI can improve API documentation

How GenAI can improve API documentation?

Category: AI

Last updated on Jun 27, 2024

The API documentation is an essential toolkit for any developer utilizing your APIs to integrate with other business applications. The Open API file aligning with OpenAPI specification (OAS) has become the gold standard for producing API documentation. The appetite for developers to try things quickly and build an integration played a huge role in shaping how API documentation tool vendors offer new features for quick value realization. For example, many API documentation tools offer a playground whereby developers can “Try” how APIs produce responses for a certain input through various endpoints. Some tools automatically generate code samples for various programming languages so that developers can directly plugin the code for their integration efforts. Developers also explore the various documentation related to API endpoints, such as security, path parameters, query parameters, and responses. This greatly enhances developer productivity and reduces time to value. The API documentation is fundamental to building an ecosystem for developers in addition to the developer community

GenAI use cases for API Documentation

Generative AI (GenAI) enhances the developer experience by providing new ways to interact with API documentation. There are many emerging use cases where developers can adopt GenAI in their software development cycle. Developers can get code snippets quickly instead of browsing through entire documentation, troubleshoot errors effectively, generate code documentation, and more importantly, annotate custom fields inside API documentation specification files

1. Content Generation

GenAI tools can create documentation for API endpoints automatically since they can understand the logic in the code snippets and their functionality. This helps developers to quickly build documentation for REST API endpoints and also emerging GraphQL as well. These can be part of the developer’s IDE/SDK stack whereby documentation generation happens quickly.

2. Enhance Consistency and Quality

GenAI can read and adopt the style guides. The style guides can be then incorporated during the documentation creation process thus enhancing consistency and producing high-quality documentation.

Code snippets

Instead of browsing through the entire API documentation for code snippets, developers can use GenAI-based search engines to get a code snippet quickly by asking the right questions. They can also tweak their questions to generate synthetic code utilizing the power of GenAI capabilities. For example, the GenAI technology is smart enough to convert code from one programming language to another language. Code snippets can be checked for syntax errors and logical errors. Thus, developers feel empowered as they are able to accomplish tasks much faster and more efficiently.

Code snippet

Also read: Guidelines for Structuring code snippets in technical writing for GenAI-based agents


When a developer is faced with some errors and wishes to troubleshoot code, the GenAI chatbot can greatly enhance the developer experience. Just pasting the error output or error logs into the chatbot prompt and asking how to debug this error would produce a response detailing the troubleshooting sequence. The developer can have a conversation with the GenAI chatbot, which assists in answering follow-up questions. The chatbot can guide and also educate developers on best practices. Some of the chatbots correlate developers’ questions with any customer support ticket raised to alert the customer that this could be a potential production bug. Suppose the chatbot is using any private knowledge utilizing any internal documentation that has reported this issue as a bug. In that case, it can immediately alert developers in the chat interface about the issue.  If the developer is logged in, the chatbot can provide more personalized information based on historic chats, such as

  • Proactive updates on the issues that the developer has reported
  • Provide more personalized responses based on the developer profile and usage patterns
  • Provide updates regarding API uptime and other reliability metrics

Custom fields definition

Developers can also use GenAI technology, such as copilot to help generate field descriptions for various parameters and data fields used inside the API definition file. This OAS definition can be enriched using GenAI such that good field descriptions can be automatically generated depending on the context of the API function within the code. This reduces the mundane effort by developers to produce high-quality API documentation.

Custom fields definition

Code documentation

For many business applications, the middleware/integration code that creates an API to interface the front end with the back end is complex in nature. Developers often have the responsibility of producing high-quality code documentation for those APIs. Utilizing GenAI tools, developers can now easily produce documentation.   

Benefits of GenAI toolkit

GenAI toolkit, such as chatbot, offers rich developer experience in understanding and accessing API documentation.  Most of the low-value tasks can be easily and quickly undertaken with the help of GenAI assistant. Some of these assistants/toolkits are integrated with developers’ tools such as IDE, SDK toolkits, editors, integration tools, and so on. The benefits offered by GenAI capabilities are

  • Increase in developer productivity
  • Reduction in troubleshooting time for any API-related errors
  • Increase in developer’s satisfaction in terms of code maintenance
  • Increase in customer satisfaction because of high-quality API documentation


GenAI toolkit such as chatbot offers rich developer experience in understanding and accessing API documentation. Chatbots offer a very personalized experience to help developers solve their problems more quickly and effectively. GenAI capabilities such as code documentation, summarization, and checking code syntax/semantics are helping developers to increase their productivity. These GenAI tools offer more value to developers, reducing their effort on mundane low-value activities.

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