{"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/69b264b5d308577aada668e8?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"4 AI Labs Built the Same System Without Talking to Each Other (And Nobody's Discussing Why)","description":"<p>What's really happening with AI capabilities at work — and why the \"jagged AI\" frame is now obsolete?</p><p><br></p><p>The common story is that AI is brilliant at some things and broken at others — but the reality is that jaggedness was never about intelligence; it was about how we were deploying it.</p><p><br></p><p>In this video, I share the inside scoop on why AI agents in proper harnesses are smoothing the capability frontier for real work:</p><p><br></p><p>- Why the jagged AI frontier was always a deployment problem</p><p>- How multi-agent coordination unlocks long-horizon knowledge work</p><p>- What Cursor's math breakthrough reveals about AI generalization</p><p>- Where meta-skills like sniff-checking become your competitive edge</p><p><br></p><p>The organizations and individuals who learn to decompose work, delegate to AI agents, and verify outputs will extend their leverage — those who don't will find the shift happening to them anyway.</p><p><br></p><p>Subscribe for daily AI strategy and news.</p><p>For deeper playbooks and analysis: https://natesnewsletter.substack.com/</p>","author_name":"Nate B. Jones"}