From the course: Building AI That Remembers: Architecting Reliable, Context-Aware Enterprise Agents
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Human review where it matters
From the course: Building AI That Remembers: Architecting Reliable, Context-Aware Enterprise Agents
Human review where it matters
Okay, friends, here's a warning. The faster an agent moves, the higher the risk of runaway errors. See, letting an agent autonomously issue thousands of refunds creates efficiency. But one mistake, one logic error will trigger a massive financial leak. So what's the solution? Design checkpoints based on decision stakes. Let's talk about what this means for Big Star. Big Star categorizes business tasks into three oversight levels. Green represents autonomous execution. These are for low-stake tasks where mistakes are going to carry negligible cost. So these are going to be things like if you are sending a tracking link, if the agent needs to explain a standard return policy, or if a customer is asking for a shipping status, those things can run with full autonomy. The agent, it can act instantly, doesn't need any human review. Yellow designates human in the loop, but these are for medium stakes operations where the agent, it can still act, but it needs the human to review the log…
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