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Testing Strategy

Testing Strategy: From Your First Interactions to Beta Tester Feedback​

Testing is an important and at the same time exciting phase of developing your AI Expert. It's an opportunity not only to "vet" their knowledge, but also to better understand their "personality," fine-tune their communication, and discover how they can best serve your clients.

Important Mindset: Working with AI as a Living System, Not a Flawless Machine​

Before you start testing, it's helpful to understand some specifics of working with artificial intelligence:

  • πŸ€– AI is not traditional software: Unlike classic programs that behave exactly according to pre-programmed code, AI (and therefore your BuddyPro Expert) is a dynamic and to some extent unpredictable system. It learns, interprets and generates responses based on vast amounts of data and complex algorithms. This gives it amazing capabilities, but it also means its behavior is not always 100% predictable or controllable down to the last detail.

  • πŸ”„ Embrace "imperfection" as part of the process: Your goal is not to create an AI that never makes a mistake or never deviates from your expectations. Such AI doesn't exist yet. Instead, view testing as a process of gradual tuning and improvement. Every "mistake" or unexpected response is valuable information that helps you better "educate" your AI.

  • βš–οΈ Working with perfectionism: Many of us tend to strive for perfection. With AI, however, it's important to find balance. If you spend a disproportionate amount of time trying to achieve absolutely flawless behavior in every conceivable situation, it can frustrate you and unnecessarily slow you down. Focus on key functions, correct understanding of your know-how, and an overall positive user experience.

  • 🎯 Feeling "I don't have control": Because AI has a certain degree of autonomy in its responses, you may occasionally feel that you don't have the outcome fully in your hands. Instead of trying for absolute control, focus on setting clear guidelines and boundaries.

  • βœ… When is AI "good enough"? Don't wait for absolute perfection. AI is "good enough" for beta testing or even for initial launch when it correctly handles key topics, maintains consistent personality, and provides a positive overall experience.

Remember that your AI Expert is like a new team member -- they need time to get trained and your help to become a real asset. Testing is a way to help them in this growth.

Why Is Testing Important?​

Testing helps you:

  • βœ… Verify understanding of your know-how: Does your AI Expert truly understand, interpret and apply correctly the information you've provided in the sources folder?
  • 🚫 Detect "hallucinations" and inaccuracies: Even the most advanced AI can sometimes "make up" information or provide inaccurate or misleading responses. Testing helps minimize these cases and identify areas where you need to supplement or clarify your know-how.
  • πŸ—£οΈ Fine-tune tone, communication style and personality: Does your AI's communication style match the personality defined in your system prompt? Is the chosen language (e.g., formal/informal) consistent? Is the AI's tone friendly, expert, empathetic -- exactly as you expect?
  • πŸ—ΊοΈ Ensure smooth and intuitive user experience: Does the onboarding process (onboarding messages) work as you intended? Is interaction with the AI natural, understandable and easy even for less tech-savvy users?
  • πŸ’‘ Identify "weak spots" and knowledge gaps: Where does the AI need additional knowledge, clearer instructions, or where are its responses not sufficiently deep or specific?
  • πŸ› οΈ Check functionality of all settings: Are disclaimers for sensitive topics properly set up? Do links work, if AI provides them?
  • πŸ’° Understand operating costs: Testing also helps you better estimate what types of interactions and how complex responses generate higher AI credit costs (using the /showCost command you can track the cost per AI response).

Phase 1: Your Internal Testing (You as Creator in the Role of First User)​

Before showing your AI Expert to the world, become its first user.

A) Testing as "New User" -- What Will the First Impression Be?​

Try out how your AI communicates with someone it doesn't know yet.

  • Switch to the role of a newcomer: Enter in the chat with your BuddyPro instance
  • Activate test profile with an invite: After switching to /test:{tester_ID} mode, enter the invite code
  • Verify onboarding: Go through the welcome messages in the Dashboard in the Messages section. Are they clear? Do the links work? Is the first impression positive?
  • Return to administrator mode: When you're done, enter the command to exit test mode

B) Exploring AI Knowledge and Behavior​

Now simply chat with your AI -- explore what it can do and how it responds.

  • Ask about various topics from your know-how, from simple questions to more complex scenarios.
  • Try what it does when you formulate a question vaguely or ask about something completely outside the field.
  • Notice whether responses are understandable, whether they match the defined personality, and whether the AI correctly uses disclaimers for sensitive topics.

Don't be afraid to experiment. The goal is to understand how your AI "thinks".

Phase 2: Testing with a Small, Selected Group of External Beta Testers​

When you feel the AI is working well internally, invite several other people to provide valuable feedback from a real user's perspective.

  • A) Selecting testers: Approach 5-15 people who represent your target audience (e.g., loyal clients, colleagues, active community members).

  • B) Generating invites for testers: Create a unique invite for each tester (or small group) to provide them controlled access. Use the command:

    /generateBuddyProInvite:{trialMessages}:{code}:{usersLimit}

    Example: /generateBuddyProInvite:150:TESTER01:1 creates an invitation for one tester with 150 messages and the code TESTER01. Then send the generated link (e.g., t.me/YourBotUsername?start=TESTER01) to the testers.

  • C) Simple instructions for testers: Let them know what you expect from them. It doesn't have to be complicated -- ask them to try chatting with the AI about topics that would interest them, and notice clarity, potential errors, or overall impression. Also let them know they're testing AI that's still learning, and that their feedback is important.

  • D) Easy feedback collection: Arrange a way for them to let you know their observations (e.g., shared Google Doc, email, private Telegram group). Concrete examples and ideally screenshots are important if they encounter a problem.

Remember that testing isn't a one-time action, but rather a cycle of trying, learning and improving. Every feedback, whether your own or from testers, is a valuable source of information for perfecting your AI Expert. Enjoy this process of discovery!

Frequently Asked Questions (FAQ)​

What to do when AI Expert keeps "hallucinating" or responding incorrectly even after my internal testing?

This is a normal part of the process. If you run into problems:

  1. Refine the instructions in your System Prompt. Maybe the AI needs clearer rules or boundaries.
  2. Fill in know-how in your sources. Often AI "hallucinates" when it doesn't have enough specific information on a given topic.
  3. Check role definitions: If the error is related to a specific area, look at the definition of the role. The /lastRole command will tell you which role has been used. You may need to modify the role or have it re-generated after adding know-how.

Don't be afraid to experiment with modifications -- it's a debugging process.