Tag
Salesforce discusses 'loop engineering' as a method for AI agents to evaluate their own progress, but argues that current metrics often fail to measure true business outcomes, suggesting agents should be aligned with shared business goals.
MIT researchers tracked 300 real AI implementations and found that only 5% of evaluations lead to full production deployment, with 95% of AI investment not producing measurable outcomes. Successful deployments focused on bounded tasks with defined success metrics.
A discussion on how to handle skeptical enterprise clients when selling AI agents, with advice to focus on business outcomes rather than the underlying technology.