Mastering Custom Instructions: A Guide to Enhanced AI Communication in Question Base

Custom instructions transform how your AI assistant communicates across your organization. Question Base makes it simple to create intelligent, context-aware AI responses that speak your company's language.

Your AI assistant becomes more valuable when it understands your organization's unique terminology and communication style. Question Base's custom instruction features let you define specific terms, set response guidelines, and create channel-specific knowledge bases – all through an intuitive interface.

Configuring Company-Specific Terms and Acronyms for Smarter AI Responses

Start by heading to questionbase.ai/settings to configure your workspace-wide terminology. The Answer Context section is where you'll input company-specific terms, acronyms, and knowledge that your AI assistant should know.

Adding terms is straightforward – simply enter your organization's vocabulary in the format "Term – Definition". For example, you might add "ICP – Ideal Customer Profile" or "MQL – Marketing Qualified Lead". These definitions become part of your AI's core knowledge base, ensuring consistent understanding across all channels.

The beauty of this system is its flexibility. Your AI assistant immediately incorporates these terms into its responses, providing more accurate and contextual answers to your team's questions. When someone asks about your ICP, the AI knows exactly what they mean and can respond with the correct organizational context.

Setting Up Channel-Specific Instructions for Tailored AI Interactions

Question Base takes customization a step further with channel-specific instructions. Each Slack channel can have its own unique set of terms and response guidelines, perfect for teams with specialized needs or different communication styles.

To set this up, access your channel settings and enable the custom instructions option. Here you can specify how the AI should format its responses – for instance, you might want it to "Always answer with numbers as a preferred response" in channels focused on analytics or reporting.

Channel Context allows you to override or supplement workspace-wide definitions. For example, while "ICP" might mean "Ideal Customer Profile" across the workspace, you could define it as "Internal Custom Payment" for your finance channel. This granular control ensures that your AI speaks the right language in the right context.

Implementing Custom Knowledge Bases Across Different Communication Channels

Your custom knowledge base works seamlessly across multiple communication channels. Whether team members are asking questions in Slack or accessing information through the Question Base web interface, they'll receive consistent, context-aware responses.

The system maintains separate contexts for different channels while preserving your core organizational knowledge. This means your sales team can have their specialized acronyms while your technical team uses the same terms differently – all without confusion or cross-channel interference.

The AI adapts its responses based on where the question is asked, using the appropriate context and formatting guidelines for that specific channel. This creates a natural, intuitive experience for users while maintaining the accuracy and relevance of responses.

Maximizing AI Performance: Next Steps for Advanced Custom Instructions Setup

Take your AI assistant's capabilities further by regularly reviewing and updating your custom instructions. Start with core terminology that everyone uses, then gradually add channel-specific terms and guidelines as you identify different team needs.

Consider adding:

• Standard response formats for different types of questions

• Channel-specific disclaimers or additional context

• Team-specific terminology and acronyms

• Custom formatting preferences for different departments

Your AI assistant becomes more valuable as it learns your organization's unique language and communication patterns. Keep refining your custom instructions based on team feedback and usage patterns to create an increasingly sophisticated and helpful AI communication tool.