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Best practices & effective testing of a Gen AI bot

Best practices to build a Gen AI bot​

You can improve your bot by focusing on Prompting, Designing conversations and Model selection.

Prompting​

  • Keep prompts precise and to the point.
  • Provide detailed examples to guide the bot (a few short examples are effective).
  • Avoid ambiguous or open-ended statements.
  • Refrain from repeating the same instructions multiple times.
  • Clearly scope the prompt to define its boundaries.
  • Include examples of how the output should be formatted.

Designing conversations​

  • Focus on one goal per conversation. Use separate goal nodes for multiple goals.
  • Limit user inputs to around 5 to avoid confusion.
  • Avoid adding too many skills, as this can complicate the goal.
  • Provide ample context about the domain and company within the goal.
  • Clearly define the bot’s persona.

Model selection​

  • Avoid generating facts from the model.
  • Set the temperature to a low range (0 - 0.5) for more predictable responses.
  • Limit the number of tokens to improve response speed and reduce costs.
  • Consider using GPT-4O over GPT-4 for complex use cases due to its lower latency and cost-effectiveness.

Testing GenAI bots​

Follow these steps to test GenAI bots efficiently:

  • Create Test Cases: Develop at least 100 test cases to cover various scenarios.
  • Conduct Bulk Testing: Execute bulk tests for these 100 queries to evaluate overall performance.
  • Evaluate Knowledge Base Performance: Aim for 80% of queries to be answered correctly if the knowledge base is well-implemented.
  • Manually Test Agent/Conversations: Perform manual testing for conversational agents to ensure nuanced interactions and accuracy.