Tim O'Reilly
Key Takeaways
- A society that uses automation to build shareholder value while impoverishing everyone else will not be successful.
- Plan scenarios and develop a robust AI strategy that can survive in multiple circumstances.
- Surfing the edge of change today requires balance and responsiveness.
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What is the fundamental human skill? It’s riding the crest of change and embracing the unknown, says Tim O’Reilly, tech trend visionary and CEO of O’Reilly Media. He “imbibed” this idea from sci-fi writer Frank Herbert (Dune) in the 1970s and has been “surfing the edge” of change ever since.
Tim founded Global Network Navigator (GNN), the first ever commercial web portal, and sold it to AOL in 1995. He went on to become one of Silicon Valley’s most influential thinkers, known for popularizing the phrases “open source” and “Web 2.0” among others. O’Reilly Media — which Tim started over 40 years ago — has provided business and tech training to millions of users and currently serves over 5,000 companies worldwide.
He has long argued that technology can create new jobs rather than laying people off – it’s a key theme in his 2017 book WTF? What’s the Future and Why It’s Up to Us. Despite evidence this year that AI has been wiping out jobs, especially for younger workers, Tim is optimistic people can adapt quickly and flourish in an automated world.
So we asked him — how can humans stay ahead of the game?
Big Think: Rather than creating employment, AI is in some respects killing it, according to 2025 Stanford research. What’s gone wrong?
Tim O’Reilly: AI is not taking jobs: the decisions of people deploying it are. We’re concentrating value in the hands of people who use it to gamble on share prices. Venture capitalists (VCs) are treating companies like financial instruments they can trade for a profit by consciously whipping up a media bubble rather than fostering real growth. These Silicon Valley hype-meisters should be ashamed of themselves.
The message in my book WTF is more relevant than ever — to look at this extractive pattern and do something about it now. If we valued companies that made real-world profits and reinvested them in solving problems — such as caring for aging populations, reducing working hours, advancing medicine — AI would create opportunities and new work.
One solution is to lower taxes for employing people, rather than automating them out of existence, and raise taxes on extractive capital gains.
Big Think: Should corporate leaders be responsible for protecting jobs from AI and how can they do that?
Tim O’Reilly: A society that uses automation to “build shareholder value” while impoverishing everyone else will not be successful. Some companies have trumpeted how they’ve used AI to lay off employees. They’ve missed the point. If you replace humans with AI, it won’t make customer service better. You have to integrate the two to improve service.
Some companies have trumpeted how they’ve used AI to lay off employees. They’ve missed the point.
Corporate leaders can start by listing all the things you wish you could do for your customers, but couldn’t afford. For example, at O’Reilly, we’re using AI to increase the content we can translate, into many more languages than before, increasing our addressable market. We are building more personalized learning paths for users, and creating tools for corporate customers to accelerate their employees’ skills and career paths.
In our business, we’ve experienced headwinds from potential customers saying “we won’t need to train programmers because AI will do the job.” The hiring prospects for junior programmers looked bleak for a while. But we’ve recently seen reports that even frontier labs are hiring junior programmers again, because they are quick to become more productive with the new tools.
Big Think: Is an AI-led market crash imminent?
Tim O’Reilly: The stock market is overvalued and due a correction. But bubbles can last longer than you think. After selling GNN for cash and stock options, I thought I had to get out quickly and realized my options for a tiny fraction of the $1 billion they would have been worth at the peak, a few years later. So the bubble will go for a while yet. But I do worry about some of the massive investment commitments that have been made.
Big Think: How might the bubble finally go pop?
Tim O’Reilly: A lot could go wrong. The immense energy requirements of AI could lead to delays. Reluctant people will bet on their old business models. For example, at GNN we tried to get book publishers and phone companies to take the internet seriously, but they wouldn’t, or took several years to start thinking about it.
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Some US AI labs have pushed this narrative that we need massive investment to reach artificial general intelligence (AGI) [which can perform any task a human can], or super intelligence [AI surpassing human brain power] — with the notion that it’s a winner-takes-all race. But Chinese businesses are showing you can build models very close to state-of-the-art for much less. US companies counting on monopoly rents would instead compete in a commoditized market, making it impossible to ever recoup their costs.
Big Think: What are the biggest pieces of nonsense about AI you’ve encountered recently?
Tim O’Reilly: The idea that previously software was a tool, now it’s a worker. That’s been true for a long time — software was doing work long before AI. It’s all in service of the narrative that this technology is different from anything before it.
Another big nonsense is how imminent AGI is — or “AI becomes super intelligent and, bang, everything is different,” with complete lack of real-world perspective or understanding of what needs to happen first. AI is not singular, it’s “normal technology.” There are still laws of physics, things to be built, and many constraints. We have a long way to go.
Big Think: What’s your advice for business leaders in this hype-led environment?
Tim O’Reilly: AI is a transformative technology, and we will learn how to make money with it. So you have to invest. But figure out how it really impacts your business and don’t buy the hype. Plan scenarios and develop a robust strategy that can survive in multiple circumstances. When the bubble bursts, you want to be making things that genuinely improve your customers’ lives. The market will eventually reward people doing the real stuff.
Big Think: What effect does the rise of “post-literate” media like YouTube and TikTok have on the learning environment?
Tim O’Reilly: YouTube is a fabulous resource but doesn’t live up to its potential for learning content because of its advertising model. For example, most videos contain five minutes of filler so they can be long enough to attract advertising. We’ll see this friction with large AI companies too if they settle on an advertising model. It’s one of the things I worry about most with artificial intelligence.
Big Think: You co-lead the AI Disclosures Project, which addresses societal dangers from commercialization of the technology. What are the challenges and how can we manage them?
Tim O’Reilly: Platforms monetize attention, often in ways that are against users’ interests. We remember when social media sites were good for following your friends and family. Now they’re continually pushing other stuff at you.
I keep urging my company to think “AI first” — try to do the job better in new ways.
The project initially asked: What if companies had to disclose metrics, as part of their SEC reporting, showing how their platforms operated before this process of “enshittification”? There’s a whole lot we could be doing to make AI protocols that promote safety and the interests of users, not just providers.
Also, in copyright, we’re trying to figure out if protocols can say, “You want to use my content? Pay me for it.”
Big Think: In the 1970s, you wrote a book about science-fiction author Frank Herbert. Are any of his ideas still relevant to you today?
Tim O’Reilly: All of them. Herbert’s famous line from the novel Dune is still true: “Fear is the mind killer.” Realizing the future does not have to be like the past and trying to keep it like the past is almost always the wrong strategy. In technology, that means being comfortable with the unknown.
Take those trying to build walls against the AI wave, pretending we can keep it at bay. Or walls against other changes, such as mass immigration, climate change or the aging population, rather than seeing the opportunities. The longer you spend putting up walls, the harder the crash when they fall.
Surfing the edge of change today requires balance and responsiveness. With AI, there are no standardized rules — you have to figure out where the edges are for yourself and your business. This is “get yourself dirty” work, not something you can do from a distance.
It’s an intensely creative period where we solve existing problems in new ways, and new problems that we couldn’t handle with previous tools. The answers are different every day because they are still being invented. The invention, diffusion, and learning are a social process.
For example, there’s a temptation to try to fit AI into existing workflows. When apps were invented, “mobile first” — design the new thing first, then retrofit the old thing when you understand it — became the watchword. I keep urging my company to think “AI first” — try to do the job better in new ways. When you’ve figured that out, go back and improve or integrate with what you did before.
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