Ramp built LLM-powered agents to automate expense approvals, achieving 65% automation rate. Key strategies include transparent reasoning with citations, allowing agents to express uncertainty, using categorical confidence levels instead of numerical scores, collaborative context improvement, and progressive autonomy from
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Choose problems where LLMs can shineShow your workBuild escape hatchesContext should be collaborativeGive users an autonomy sliderEvals are the new unit testsBuilding agentsSort: