AI agents in GoSearch can drive major productivity gains, and getting the best results starts with following best practices. Thoughtful setup and clear guidelines enable agents to deliver accurate, relevant, and safe responses across your organization.
This guide will help you maximize agent effectiveness, whether you’re creating, refining, or deploying custom agents.
By following these practices, users will learn how to:
- Design clear and effective agent instructions for consistent, reliable results.
- Use prompt engineering to tailor agent responses for specific tasks, audiences, or use cases.
- Select and connect relevant data sources, ensuring agents have the right context to answer questions.
- Configure agent settings for accuracy, guardrails, and safe execution.
- Gather and apply feedback to continually improve agent performance and value.
Define the agent’s purpose and audience
- Set your agent up by giving it a clear, well-defined role. Start by choosing a specific, recognizable name and writing a short summary that tells users what the agent is meant to do.
- Make sure to call out who the agent is for—such as HR staff, developers, or customer success teams—and include any important context like preferred output formats (e.g., bullet points or Slack-ready messages). A strong identity builds trust and helps users know exactly when and how to use the agent.
Write clear and concise instructions
- Clearly outline what the agent should and should not do. Be direct, specific, and action-oriented.
- To avoid scope creep or inconsistent results, consider limiting it to a defined set of response types or output formats. Use numbered or bulleted lists to map out supported tasks, step-by-step processes, or common use cases. The clearer your instructions, the more reliable and focused your agent will be.
Set boundaries and guardrails
- Agents perform better when they know their limits. Define what questions or actions are out of scope for the agent. For example, you can instruct a Product Support agent to only relay instructional material from verified help articles and always use a positive tone.
- Give the agent access only to the information it needs and avoid providing unnecessary context. The less irrelevant context an agent has to sift through, the more precise its responses will be.
Choose relevant data sources
- If your agent relies on a single source of truth like a Confluence space or Notion wiki keep its focus tight.
- For broader-use agents, like general workplace assistants, you can connect multiple resources, but try to avoid overwhelming the agent with unnecessary information or granularity.
Add realistic conversation starters
- Make it easy for users to engage with your agent by providing clear, real-world example prompts. These conversation starters should reflect actual questions or requests your users might have and showcase the agent’s strengths.
- Whether it’s “Write a welcome email for a new hire” or “Summarize our Q2 roadmap,” examples help users know what to expect and how to get the best results from the agent right away.
Test and iterate the agent before wide rollout
- Before sharing your agent with a wider audience, test it. Run sample queries based on real workflows, and see if the results are as anticipated.
- Fine-tune your instructions, response formats, or data sources as you see fit and make adjustments before the agent gets shared widely to your whole team.
Monitor and update agents regularly
- Keep using your agent regularly and keep their data sources updated.
- As your business processes evolve, update your agent’s instructions, conversation starters, or connected data sources to keep everything aligned. A well-maintained agent stays useful, trusted, and relevant over time.
You should now be able to use and build agents effectively. If you need further assistance, please consult the GoSearch Help Center, Contact Technical Support, or Chat with Us.
