The rapid advancement of AI technology has led to a proliferation of AI agents that can perform various tasks, from writing code to answering phones. However, the true bottleneck for these agents is not their capability, but rather the trust and identity they can establish with humans.

Building an AI agent that can operate autonomously and handle day-to-day business operations requires more than just technical expertise. It demands a deep understanding of how humans interact with machines and how to establish trust and credibility.

Key factors that contribute to an AI agent’s success include its identity, which encompasses its name, voice, and track record. Agents with a well-defined identity are treated differently by humans, who respond to them and hold them accountable in a more personalized way.

Another crucial aspect is context persistence, which refers to an agent’s ability to remember and adapt to previous interactions. This capability is essential for building trust and establishing a strong working relationship with humans.

Ultimately, the trust gap is the most significant engineering problem that AI agents face. While it is relatively easy to develop an AI agent that can perform tasks, getting humans to trust it enough to work unsupervised is a much more complex challenge.

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