Home Speakers Shawn Wang (swyx) Quote Foundation Models are “ few shot learners ”, exhibiting in-context learning and even zero shot transfer capabilities that generalize beyond the original intent of model trainers. In other words, the people creating the models don’t fully know what they are capable of.
Words found on the source page on Nov 6, 2026.
More from Shawn Wang (swyx) Essay The Rise of the AI Engineer Jun 30, 2023
I think software engineering will spawn a new subdiscipline, specializing in applications of AI and wielding the emerging stack effectively, just as “ site reliability engineer ”, “ devops engineer ”, “ data engineer ” and “ analytics engineer ” emerged. Essay The Rise of the AI Engineer Jun 30, 2023
In the near future, nobody will recommend starting in AI Engineering by reading Attention is All You Need, just like you do not start driving by reading the schematics for the Ford Model T. Essay The Rise of the AI Engineer Jun 30, 2023
There are 10x as many ML Engineer jobs as AI Engineer jobs on Indeed, but the higher growth rate of “AI” leads me to predict that this ratio will invert in 5 years. Essay The Rise of the AI Engineer Jun 30, 2023
We are observing a once in a generation “shift right” of applied AI, fueled by the emergent capabilities and open source/API availability of Foundation Models. A wide range of AI tasks that used to take 5 years and a research team to accomplish in 2013, now just require API docs and a spare afternoon in 2023.
On the same topics Blog The Specter Of Neuralese Sep 24, 2026
An AI with more real layers can actually be “smarter” in the conventional sense of the term. Blog The Specter Of Neuralese Sep 24, 2026
For 100 steps in a row, the AI can shoot delicate subtle ideas from layer to layer at the speed of light. Then there’s one step where it has to encode them into twenty-six glyphs invented by Phoenician turquoise miners in 1800 BC. Then it has to re-encode the Phoenician glyphs into delicate subtle lightspeed ideas before it can do anything else. Blog The Specter Of Neuralese Sep 24, 2026
The science of reading these thoughts is a subfield of AI interpretability, which is still in its infancy. Blog Mysteries Of AI Generalization Sep 23, 2026
This trains the AIs to be focused on task success, which naturally risks including things like reward-hacking, cheating, and single-minded pursuit of stated goals at the expense of ethical injunctions. Blog Why I still haven't bought into true RSI Sep 19, 2026
It is important to not confuse massive steps in inference-time scaling, a dynamic which should be fairly predictable, with being the outputs of RSI, which is highly uncertain. Podcast Dwarkesh Podcast: Agent swarms, alignment, and recursive self-improvement Sep 17, 2026
If you have five hours, you’re probably going to do a lot better. The AI models are pretty similar. About this quote 
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