Part 9/14:
A critical concern for complex AI systems is observability—being able to track, verify, and trust the outputs generated by multi-agent setups. Erik stresses that simplicity remains crucial; starting with minimal, clear systems helps prevent unmanageable complexity and inefficiency.
Developing verification techniques—particularly in the context of multi-agent systems—is a key research focus. Ensuring that each agent follows instructions precisely and that overall outputs are trustworthy requires robust oversight mechanisms. For instance, agents managing sub-agents need to communicate effectively and provide clear instructions to avoid miscommunication and errors.