{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/69ab3b7c7036d739021982df/6a650556d198963142f75e56?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Find a Real Job for Your First AI Agent.","description":"<p>For deeper playbooks and analysis: <a href=\"https://natesnewsletter.substack.com/\" rel=\"noopener noreferrer\" target=\"_blank\">https://natesnewsletter.substack.com/</a></p><p>What’s really happening when AI takes on customer support?</p><p><br></p><p>The common story is that AI helps teams answer tickets faster — but the reality is that the biggest gains come from finding and removing the hidden process that created the ticket in the first place.</p><p><br></p><p>In this video, I share the inside scoop on how we used AI to resolve 51 of 52 support issues in one week, reduce a comparable week from 52 cases to 19, and eliminate our largest recurring category.</p><p><br></p><ul><li>Why grouping cases by root cause matters more than grouping by subject line</li><li>How tickets can become scaffolds for cross-system research</li><li>What should remain behind a human approval gate</li><li>How to test an agent in draft mode before giving it more freedom</li><li>Why the remaining cases get harder after the repetitive work disappears</li></ul><p><br></p><p>For operators, builders, and customer-facing teams, the shift is from automating replies to rebuilding the workflow so fewer customers need to ask for help at all.</p><p><br></p><p>Subscribe for daily AI strategy and news.</p><p>Hosted on Acast. See acast.com/privacy for more information.</p><p><br></p>","author_name":"Nate B. Jones"}