When [the AI] was then instructed to prevent the company’s financial decline, it independently concluded that averting an organizational setback was more important than adhering to the rules, and leveraged the insider information to make a trade.

Start by determining your use cases. What does your AI actually need to be able to do? How do you plan to use it on a daily basis, and who is going to be the one pressing the buttons? What do they need to be successful?

To improve, AI agents need feedback on their performance (just like people do). This second phase is where the reinforcement learning begins.

Sometimes data pipelines can seem like they’re working, not trigger any alerts, and actually have something massively wrong. This is where we recommend Impossible Reports.

Your approach to training an AI agent is just as important as your approach to training any new hire. While AI (obviously) learns differently than people do, setting it up for success with a solid foundation is crucial to making it an effective part of your team.