A 5-point checklist before you select and implement an AI agent platform

Ensure their environment is intuitive, easy to test your agents within, and has enhanced options for your agents such as short- and long-term memory. Plus, there should be features for responsible AI — reflection, groundedness, and context relevance — and safe AI — fairness and bias, toxicity check, human-in-the-loop, and PII redaction. You’ll also want to have, at a glance, visibility into your credits used as part of your subscription, as well as value-added features like the ability to improve the role and instructions for your agent using AI.

Thorough API documentation

Once your agents are built in the AI agent builder platform, the next step is to use API calls to implement these agents within your own applications. Look for plentiful documentation at the API level, but also higher-level information that explains the sequence when provisioning agents on the fly, and so on. This is where clear documentation can help your own IT team get up to speed and learn the required sequence from environment setup, to RAG creation and training, to agent creation, to agent interaction and inquiry. 

They’ll also need clear documentation on how to monitor and report on token usage, and how to monitor and display historical inquiries, AI agent and security performance, and integration with other systems. Having this information can often halve your development and testing time since there’s far less back-and-forth between your IT team and the agent provider resolving questions and issues.