Best practices

Here are some best practices to keep in mind when you build and manage agents using the platform:

• Identify and clearly define the problem you are trying to solve with an agent. 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 agent.

• Choose the right model for your agent. There are several models that you can use to power your agent. 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 agent.

• Train your AIs with high-quality data. Agents rely on this data to solve problems and find answers for you. You can configure different types of data sources. Having diverse and clear datasets is crucial to ensure that the responses generated by an agent 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 agent'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 agents 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 agent. This is important to generate output that complies with regulations and policies and can be shared across different channels.