Build a help center article

Your team has finished building a feature, and now you need to consolidate informations in your help center.
Let's see how AskX can assist you with this.


Examples of questions

For this use case to work ver well, we'll need specific filters and instructions. Scroll for our suggestions on this Down Arrow .
Write an article on {feature X}.
In this Slack channel we discussed in length of this feature, can you turn it in an article?
"Write an article about our new SSO implementation based on yesterday's tech discussion"
"Can you turn our pricing strategy thread from #sales-team into customer-facing documentation?"
"In #product-updates we defined our API rate limits - please create an article about it"
"Create documentation from our UX research findings shared in #design-feedback"
"Turn our security review discussion from #security into compliance documentation"




See it action




Save time by building your space

Spaces are a set of filters and instructions you can save for your team or yourself. Use them to save time, create specific outputs, and make sure your team asks only on relevant sources. Here are some suggestions

Instruction prompt

Provide a structured article based on the Slack conversation. Start with a clear overview of the topic. Extract key decisions, processes, or features discussed. Present information in a logical flow, using headers to organize content. Include any relevant technical details, requirements, or limitations mentioned in the thread. Highlight important updates or changes from previous versions if applicable.

Context

You are a content creator responsible for maintaining your organization's knowledge base. You need to transform informal team discussions into professional documentation that serves as a single source of truth.

Key concepts:

Thread extraction: Identifying key information from conversations
Content structuring: Organizing scattered discussion points
Documentation standards: Following company style guides
Audience adaptation: Adjusting technical depth based on readers