What happens to your AI bill when agents improve and more people start using them? Nate draws on his conversations at Dreamforce to examine the cost of wider adoption, the work agents can make affordable, and the decisions that change cost per successful result.
The discussion covers redesigning workflows, routing routine work to cheaper models, matching an agent’s surrounding software to its capabilities, and evaluating results before scaling up.
More analysis and practical playbooks: https://natesnewsletter.substack.com/
Editorial note: Draft podcast copy; current Acast house format has not been independently confirmed. No chapters included.
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