Towards a Question and Answer world

Technical communication has traditionally been rooted in instructional guides: comprehensive resources users could turn to when they needed information. But that information was only useful if users could actually find it. The expectation was that users would search for what they needed and then read it. On the provider’s side, the goal was to make content easy to find, understand, and act upon.

While those in-depth resources still have their place, the way users want to access information may be undergoing a seismic shift. Michael Andrews and Ardis Ramey have suggested technical communication is rapidly moving towards a question-and-answer (Q&A) paradigm.

From reading to asking

According to Ardis Ramey, chatbots are shifting the emphasis from reading to asking.

Reading requires time, focus, and often some prior knowledge. Asking, by contrast, is fast, intuitive, and accessible. In this new model, users don’t need to know where the answer lives – they just need to know what they want to ask.

Why the change?

For years, we’ve been conditioned by search engines like Google. Questions dominate search queries.

Voice searches tend to be more conversational and are more likely to be phrased as questions. Estimates suggest that about 65% of voice searches are in question format.

And now we have chatbots.

The promise is:

• Users get quick, direct answers.
• Chatbots can understand context better than static documents, offering more tailored responses.
• Reduced cognitive load – sifting through documentation is work; getting an answer directly feels effortless.

But not a static FAQ

For years, the FAQ page been a staple of many websites.  But as the UK’s Government Digital Service (GDS) pointed out in their post FAQs: why we don’t have them, traditional FAQ pages often become:

• A dumping ground for content that doesn’t fit neatly elsewhere.
• A reflection of organisational assumptions about what users ask, rather than actual user needs.
• A source of content duplication and maintenance headaches.
• A poor user experience, forcing users to scan a long list of questions that may or may not be relevant to their specific, nuanced problem.

GDS argued that if information is important enough to be in an FAQ, it should be findable and well-integrated into the main content where users naturally look.

A Q&A world shouldn’t be a world of static FAQs. Instead of directing users to a fixed list, every part of the knowledge base becomes a source of answers. The FAQ is everywhere and nowhere specific. Users won’t navigate to a particular list. They’ll instead ask their question via a chatbot or an intelligent search bar.

What does this mean for technical communicators?

This shift isn’t a death knell for Technical Authors. It’s a refocusing of our core skills. Long-form guides and Help systems don’t disappear; they become the foundational content for these Q&A experiences.

Here’s how our role may need to adapt:

1. A Q&A approach focuses on the direct path from question to isolated answer. This doesn’t mean abandoning structure, but rather ensuring each part can be effectively decontextualised and re-contextualised by an AI.
2. Content must be granular, capable of standing alone as a coherent answer to a specific question.
3. Clear headings, structured sections, and rich metadata (schemas, taxonomies, and consistent terminology) help AI understand, index, and retrieve information accurately.
4. Ambiguity is the enemy of AI comprehension. Our writing must be precise and unambiguous.
5. We must become adept at predicting and understanding what users will ask, not just what tasks they perform. This means analysing search queries, support tickets, and chatbot logs to continually refine content.

In short, the future isn’t about crafting a list of 20 common questions. It’s about building a robust, intelligent knowledge system that can handle any question, and deliver a meaningful answer.

The evolving skill set of the Technical Author

The core competencies remain, but they’re evolving. We’ll likely need to:

• Learn tools for publishing content to AI-ready formats, or adapt to new features in existing platforms.
• Design content specifically for AI consumption and for question-based discovery.
• Continuously maintain and refine content, ensuring AI learns from the right sources and improves over time.

Challenges and opportunities

Naturally, this shift brings challenges:

• AI can hallucinate, provide incorrect answers, or miss important nuance.
• A poorly designed chatbot interface can feel like a modern-day Clippy.
• Users may receive shallow answers when deeper context is needed.

This is where technical communicators shine, by structuring content impeccably and overseeing the quality of AI-driven experiences.

The opportunities, though, are significant:

• Faster problem resolution, and happier users.
• Improved content findability.
• Reduced strain on support teams through call deflection.
• A more strategic role for techcomm professionals as the architects and curators of knowledge systems.

What do you think?

How is your organisation navigating this shift? Are you already designing for question-based access? Share your thoughts in the comments below.