{"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/6a5428e9c2f78bb6893694d3?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Pick an AI Model That Fits How You Actually Work","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 as the model race expands into GPT-5.6, Fable 5, Grok 4.5, GLM 5.2, and increasingly complicated model mixes?</p><p><br></p><p>The common story is that you should pick whichever model tops the latest benchmark — but the reality is that the best model depends on how you think, how you prompt, and what your hardest work requires.</p><p><br></p><p>In this episode, Nate shares the inside scoop on choosing a model by work pattern rather than hype.</p><p><br></p><ul><li>Why “dumber” does not mean dumb</li><li>How model families develop different working styles</li><li>Why benchmarks are evidence, not the selection heuristic</li><li>How Ringer pairs a strong architect with cheaper workers</li><li>What knowledge-work AI still needs beyond coding harnesses</li></ul><p>For builders, operators, researchers, and team leaders, understanding your own work is becoming more durable than memorizing every model leaderboard.</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"}