Pick an AI Model That Fits How You Actually Work

YouTube/Podcast/Substack · YouTube · Podcast · Read

• Core reframe: model selection should weigh working style, not just benchmarks — even when one model is technically superior, a worse-benchmarked model may fit an individual’s workflow better.
• Named tool: “Model Fit” — a diagnostic that asks how you work, then recommends a model mix rather than a single “best” model.
• Personal case study: despite Fable 5 scoring higher, Nate defaults to GPT-5.6 Sol daily because Sol suits his habit of long upfront prompts with iterative correction, while Fable 5 excels at “reading between the lines” for those who under-specify.
• Covers GPT-5.6, Fable 5, Grok 4.5, and GLM 5.2 as the current model set being routed across, rejecting “pick whichever tops the latest benchmark” as the decision rule.
• Practical takeaway: build a model-mix strategy (not a single-vendor commitment) matched to task type and individual/team working patterns — treat different subscriptions as complementary specialists, not competing options.