Skip to main content

Best practices

When you build and work with AIs using the AppDirect AI platform, we recommend incorporating some of the following best practices:

  • Identify and clearly define the problem you are trying to solve with an AI. It could be a customer pain point or a perpetual issue in one of your business processes. Clarity of what needs to be addressed is key to building the right tools with an AI.

  • Choose the right LLM for your AI. There are several models that you can use to power your AI. With AppDirect AI, you get the choice of all the publicly available models from OpenAI. Each model has its strengths and weaknesses. Some may be good at data analysis, whereas others would be good at content generation. Understand these pros and cons to choose the best model for your AI.

  • Train your AIs with high-quality data. AIs rely on this data to solve problems and find answers for you. AppDirect AI allows you to configure different types of data sources. Having diverse and clear datasets is crucial to ensure that the responses generated by an AI are distortion-free and reliable.

  • Monitor, iterate, and improve. Just like how you refine prompts to get the best result from a conversation, it is important to continuously monitor your AI's performance and make adjustments over time. For instance, tweaking training instructions based on historical data can enhance results. Models are updated frequently. Look for such updates and retrain your AIs periodically with new data.

  • Ensure that training inputs are free from any form of bias. You must apply ethical considerations when you input training data and design your AI. This is important to generate output that complies with regulations and policies and can be shared across different channels.

Was this page helpful?