🤖 AI Summary
Overview
This episode explores the paradox of AI-driven automation: while AI makes expert-level tasks more accessible, it simultaneously increases the demand for human expertise to refine, direct, and innovate. Dan Shipper and Brandon Gell discuss the implications of AI on work, the limits of AI autonomy, and how individuals and companies can adapt to thrive in an AI-enhanced world.
Notable Quotes
- You prompt AI to do something, it blows your mind, you feel inadequate, and then it stops working and looks back at you and says, 'What should I do next?'
– Brandon Gell, on the inherent limitations of AI.
- If you ride the models, you're going to be fine. You're going to have a job, you're going to do great work, and you don't have to worry.
– Dan Shipper, on adapting to AI advancements.
- If your answer to progress is firing people, you're not a very creative CEO.
– Brandon Gell, critiquing layoffs attributed to AI.
🤖 The AI Paradox: More Automation, More Human Work
- Dan explains that AI makes yesterday's expert competence
cheap and widely available, enabling non-experts to perform tasks previously reserved for specialists.
- This abundance of close but not quite right
output creates a demand for experts to refine and contextualize the work.
- At Every, AI tools are deeply integrated into workflows, yet the company has grown from 4 to 30 employees, demonstrating that automation doesn't eliminate jobs—it shifts the nature of work.
🧠 AI Autonomy vs. Human Agency
- AI can act autonomously within defined tasks but lacks true agency, which requires self-motivated decision-making.
- Dan argues that AI will always rely on humans to define what matters, even as it becomes more advanced.
- The distinction between autonomy (task execution) and agency (self-driven action) ensures that humans remain central to decision-making.
📉 The Myth of AI-Driven Layoffs
- Layoffs attributed to AI, such as those by the CEO of ClickUp, are often more about poor management or economic pressures than actual automation.
- Companies that prematurely replace human workers with AI often face setbacks, as poorly implemented AI systems fail to meet expectations.
- Brandon and Dan emphasize the importance of creative leadership in leveraging AI to enhance, rather than replace, human work.
📈 Riding the Models: Thriving in an AI World
- Dan advises individuals to ride the models
by learning to use AI tools effectively in their work.
- AI can enable people to perform more fulfilling and ambitious tasks by automating repetitive or lower-level work.
- While opting out of AI is possible, those who embrace it will likely find more opportunities to innovate and excel.
✍️ Using AI for Long-Form Writing
- Dan shares how he used AI tools like Claude and Codex to draft and refine his 8,000-word essay, After Automation.
- By iterating ideas with AI and listening to AI-generated audio drafts, he maintained continuity and clarity in his writing process.
- This workflow highlights how AI can augment creative tasks without replacing the human touch.
AI-generated content may not be accurate or complete and should not be relied upon as a sole source of truth.
📋 Episode Description
Dan Shipper runs one of the most AI-native companies today. Every has agents embedded in nearly every workflow—“if you swing a stick in our Slack, you're as likely to hit a human as an agent,” he says. And yet the company has grown from four people to 30 since GPT-3 came out, and is still hiring.
Why does Dan believe there's more human work to do than ever?
In a format flip for AI & I, Every's COO Brandon Gell turns the tables and interviews Dan about his latest essay, “After Automation”—an 8,000-word argument for why rising automation doesn't eliminate demand for human work, it increases it. The thesis: AI makes yesterday's expert competence cheap and widely available, which floods every field with output that's close but not quite right—and that creates more demand for the humans who can take it the rest of the way.
Dan talked with Brandon about the paradox at the heart of agent-native work: The more AI can do, the more humans are needed to direct it, refine its output, and decide what matters next.
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Links to resources mentioned in the episode:
“After Automation” by Dan Shipper: https://every.to/chain-of-thought/after-automation
Brandon Gell on Every: https://every.to/@brandon_5263
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Timestamps:
00:00:51 Introduction
00:05:51 The AI paradox: more automation, more human work
00:10:00 How AI makes yesterday's expert competence cheap
00:18:00 AI can act autonomously but it does not have agency
00:20:39 Why Dan is all in on AGI
00:21:57 AI layoffs are a lie
00:25:42 Ride the models and you'll be fine
00:35:30 How to use AI as a long-form features editor