{"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/6a148071942fd18754e18adf?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Public AI Work: How Teams Actually Learn From AI","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><br></p><p>What's really happening when AI work moves out of private chats and into shared company spaces?</p><p><br></p><p>The common story is that AI adoption is mostly about buying better tools -- but the reality is that the companies learning fastest are making the work itself visible.</p><p><br></p><p>In this episode, I share the inside scoop on how public AI workflows can become apprenticeship infrastructure for teams learning to work with agents.</p><ul><li>Why Slack is becoming a practical substrate for human-AI collaboration</li><li>How Shopify's River workflow makes agent work observable</li><li>What most companies lose when AI work stays hidden in private windows</li><li>Where senior operators should make non-sensitive AI work public</li><li>Why constraints can turn AI use into shared learning instead of isolated productivity</li></ul><p><br></p><p>This matters for operators, builders, executives, and team leads who need AI adoption to compound across the organization, not just live inside the habits of a few early adopters.</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>","author_name":"Nate B. Jones"}