Generative AI

It goes without saying that technical writers create knowledge base articles for internal teams and customers. The knowledge base article is available in a wide variety of flavors, including user manuals, technical spec documents, configuration guides, procedures, and software product features. These knowledge base articles are read by humans, who then act!

This paradigm shift is taking place in terms of how knowledge base articles are produced, used, and some actions are carried out. The following technological trends and consumer behavior are responsible for this change.

In this blog, we’ll examine how changes in consumer behavior will affect the creation of knowledge base articles and how people will use them.

Change in Technical Writer Role

Technical writers and knowledge base providers are still determining how the rapid technological change following the release of ChatGPT-4 will affect their respective job roles and technological platforms. However, as shown in the table below, there is a change in consumer consumption trends for knowledge creation, discovery, and consumption.

Trends Then Now
Audience of your knowledge base Humans Artificial Intelligence bot
Content discovery engine Search engines such as Google, Bing, and so on Generative AI such as ChatGPT, Bard, and so on
Content discovery optimization Search Engine Optimization (SEO) Semantics content structuring
Content discovery mechanisms Search keywords Prompt
Outcomes of knowledge consumption Humans doing work Artificial Intelligence bot doing work with minimal human intervention

 

Technical writers need to change the way they think when creating knowledge base content so that it is understandable to AI bots and humans alike. Technical writers have traditionally produced content primarily for humans, so this is a radical change in how they do it now. Technical writers will create new knowledge for AI bots in the future, particularly for Generative AI technologies. However, as shown in the table below, the characteristics of writing for human consumption and how to create content for AI bots are very different.

Characteristics Writing for humans Writing for an AI bot
Content length Concise and precise As explanatory as possible
Use of visuals Short videos and gifs Media content needs rich annotation
Adding Metadata Optional Mandatory
Accessibility Mandatory Mandatory
Inclusive language Mandatory Mandatory
Content tone Can be conversational, monotone Generic tone
Content output Fixed Highly customizable
Content design Mandatory Flexible

 

Writing for Humans

Given the short attention span of people, a technical writer must write knowledge base articles with concise content. The traits are determined by a person’s biology, psychology, and cognitive abilities. This is equivalent to

Humans engage in specific actions as described in the knowledge base article once they have read and understood it. For instance, if a software user reads about a feature of a product in software documentation, they may configure that software.

Writing for an AI bot

Technical writers must modify their approach when creating new knowledge base articles for AI bots. An AI bot can interact with both humans and other AI bots and has limitless computing power to synthesize new knowledge and limitless storage to store massive amounts of data!

Given the traits of the AI bot, writing for an AI bot or Generative AI requires a different approach. This is equivalent to

If technical writers create content that is AI-friendly, then a customer can ask Generative AI what goal they want to achieve. Precise steps can be provided by generative AI technologies like ChatGPT, Bard, and others. Bot technologies like RPA and intelligent automation through APIs will probably ask a customer if they want to carry out those actions on their behalf.

Content Evaluation

How can we make sure that our current publicly available knowledge base contents are prepared for generative AI models to ingest and provide accurate answers based on our customers’ prompts, given that technical writers will produce content for AI bots? A sizable corpus of text taken from the public internet is used to train large language models (LLMs), such as ChatGPT. Your knowledge base content must be used by the LLMs, so those language models must be adjusted. Numerous examples of prompts and responses must be provided in order to fine-tune the LLMs. This can be accomplished by creating numerous FAQs with questions and detailed responses. The steps for technical writers to adapt their current knowledge base to be AI-friendly are listed below.

Metrics

When making efforts to future-proof your current knowledge base, quantifying the efforts required to create the content for your knowledge base is helpful. Vendors of knowledge base platforms will develop tools to aid technical writers in creating content that is AI-friendly. The metrics listed below can aid in winning over business stakeholders.

Conclusion

Enterprise software will soon be dominated by generative AI. Given that Microsoft is integrating ChatGPT into each and every enterprise product, it is widely used by clients around the world. Your investment in the current knowledge base will be future-proofed if you produce knowledge base content for ChatGPT. A shift in your technical writers’ perspectives is necessary to refactor your current knowledge base. While refactoring your current knowledge base and creating new knowledge content, Generative AI technology characteristics need to be taken into account.

 

Now I eagerly await the day when Generative AI technologies respond to my question via prompt and are also capable of acting on my behalf via bot technology!