Kevin Roose
Simon & Schuster (UK) Farrar, Straus and Giroux (US)
I think about AI almost every day. Part of this is a hazard of being a science journalist, while part is simply that I think large language models (LLMs), the technical juice behind products like ChatGPT, are fascinating in both their flaws and successes. Even if you aren’t as AI-preoccupied as I am, you probably find it a tricky topic to escape, not least because we seem to get daily hysterical warnings about a coming AI apocalypse. But what is incredible is that the current AI era only really kicked off with the launch of ChatGPT in 2022.
Sure, researchers had been tinkering with LLMs long before they became products, and many other forms of AI had previously taken the world by storm, such as IBM’s Watson in 2011 or DeepMind’s AlphaGo in 2016. What made 2022 different is that it was the year that anyone with an internet connection could easily start talking to a computer and get something reasonably comprehensible back.
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Since then, the progress of AI has felt like a rollercoaster the world can’t get off. It is easy to forget how we got here after just a few years, which is why by Kevin Roose is a very welcome read, documenting the past decade from the founding of OpenAI to the present day. It is a story that involves names you are probably familiar with – Sam Altman, Elon Musk and Demis Hassabis – and many more that you aren’t, but who have played an equally important role in getting to where we are today.
Roose’s argument is that the race to build artificial general intelligence (AGI) is the 21st-century equivalent of the Manhattan Project to build a nuclear weapon during the second world war. One key difference between then and now is that much of the work today is being done by private companies, not government scientists, potentially making it much harder to document. Thankfully, Roose says he interviewed more than 150 insiders at OpenAI, Anthropic and Google DeepMind, and it shows – the access here is excellent.
One important thing to know is that Roose is self-declared “AGI-pilled”, Silicon Valley lingo meaning he believes that AI will achieve general, human-level intelligence in the near future. This AGI-is-coming lens warps his view of recent history and aligns him with internal AI company narratives more than I would like. In fact, his epilogue reveals that he thinks AGI is essentially already here, as long as you downgrade your expectations of what AGI means, which feels slightly pointless to me.
Despite this, The AGI Chronicles is an excellent historical read. It details how OpenAI was created by Altman, Musk and others out of fears that DeepMind would get to AGI first, how fallings-out led to Musk leaving and, separately, how Anthropic was created as an apparently more safety-first AI company.
Roose’s argument is that the race to build AGI is the 21st-century equivalent of the Manhattan Project
His dive into the history of the AI safety movement and its various factions also helps explain why AI executives can warn about AI destroying humanity at the same time as asking for billions of dollars to build it. There is some overlap with Supremacy by Parmy Olson, but her history goes deeper and her analysis is more sceptical, while Roose’s access is better, so it is worth reading both books.
Roose’s book is also an excellent technical read, explaining the mechanics behind LLMs, some of the crucial discoveries of the past decade and how the companies overcame various technical hurdles along the way. These two strands, historical and technical, give you a full primer on modern AI while never falling into textbook mode.
Roose has done an impressive job of covering an incredibly fast-moving field. Supremacy suffered in its final section, which was essentially just a rapid summary of everything Olson could squeeze in before her press deadline, but Roose has pushed right up to the limit and covered the “agentic” developments of early 2026, when AI tools were increasingly writing computer code and becoming more powerful. The only events he misses are the emergence of AI as a maths powerhouse earlier this year, and the Hugging Face hacking incident revealed in July. Both of these will be an important part of future AI histories, but the present moves too fast for publishing house speed.
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