Why One Developer Built an AI Support Agent That Cannot Make Business Decisions

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A software developer has launched a public experiment to build a trustworthy LLM-powered customer support agent, documented in an open-source repository called reliable-ai-support. The core design principle splits responsibility clearly: the AI interprets user intent, while deterministic software enforces all business rules and policies. Every proposed action is routed through a risk-tiered validation gate before anything executes, ensuring the AI cannot independently process refunds, access unauthorized data, or trigger financial transactions. High-risk actions require human approval with a full audit trail, while the highest-risk actions are only proposed by the AI and must be carried out manually by a person. The project addresses a key concern in AI deployment — that an LLM's confidence is not a reliable indicator of correctness — by keeping consequential decisions firmly in the hands of rule-based systems and humans.

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