Ensure that your environment is intuitive and easy to test agents, and enhance your agent options, such as short- and long-term memory. Additionally, responsible AI capabilities (reflection, grounding, contextual relevance), and safe AI-equity and bias, toxicity checks, loops, and PII editing are required. You should also look at value-added features such as the visibility of credits used as part of your subscription and the ability to use AI to improve the role and direction of agents.
Intensive API documentation
Once agents are embedded in the AI Agent Builder platform, the next step is to implement these agents within your own application using API calls. Look for rich documentation at the API level as well as high-level information that explains the sequence when provisioning agents on the fly. This is when clear documentation helps your IT team learn faster, from setting up the environment to required sequences, creating and training lags, creating agents, interacting and enquiries with agents .
It also requires clear documentation on how to monitor and report token usage, historical inquiries, AI agents and security performance, and how to monitor and view integration with other systems. Having this information often cuts development and testing time by halving, as IT teams and agent providers are far less likely to solve questions or problems.
