Descriptions:
Full post w/ Guide + Automation Skill:
https://natesnewsletter.substack.com/p/let-ai-pick-what-to-automate?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
AI agents are getting good enough to help pick the problem worth automating, not only run the task you hand them. I gave Fable and Codex the same open brief—inspect my real business and build the automation that matters—and they chose different problems.
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What’s really happening when you let AI pick the problem, not just the tool?
The common story is that agents need a tightly specified task. The real question is what happens when a model can inspect your work and tell you what deserves automating in the first place.
In this video, I share the inside scoop on giving Fable and Codex the same open brief:
– Why Codex picked the safe, finishable problem
– How Fable found the higher-leverage one
– What “big model smell” looks like in practice
– Where model routing now starts, before the task is defined
Letting AI help choose the problem is a real unlock, but the judgment of which consequence matters most still sits with you.
Chapters:
00:00 Same brief, two different outcomes
02:10 Why agent scale changes the workflow
03:10 Fable’s preflight build
04:45 Codex’s handoff proof
06:20 Strategic discovery versus execution
08:00 The reusable automation skill
10:40 The final verdict
Listen to this video as a podcast.
Spotify: https://open.spotify.com/show/0gkFdjd1wptEKJKLu9LbZ4
Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-news-strategy-daily-with-nate-b-jones/id1877109372
