Dan Biderman
Dan Biderman is the co-founder and CEO of Engram, a company building memory infrastructure for enterprise AI systems that he launched in 2026 after eight months of development. He completed postdoctoral research at Stanford University under Chris Ré, focusing on resource-efficient machine learning, after earning a PhD from Columbia University's Center for Theoretical Neuroscience. He is known for his work on making AI agents more cost-effective and for leading Engram's effort to create specialized memory models that learn organizational context, backed by $98 million in funding from investors including General Catalyst, Kleiner Perkins, and Sequoia Capital.
“The bottleneck for making these models more useful these days is not really raw intelligence, but understanding new and evolving context... How do you bake that into the model weights the same way that pre-training and post-training bakes that into the model weights very deeply?”
Source→“Demis at the Sequoia event about a month ago said pretty clearly that we need new breakthroughs around these topics. And obviously they're thinking about them. We're just focusing exclusively on this.”
Source→“We need all these smart people and Anthropic interpretability to try and break them apart.”
Source→“Anyone else who's seen the ChatGPT moment and went to do some work at Mosaic and stuff like that to learn how the sausage is made on the NLP side.”
Source→“To me, the main events were GitHub Copilot. That for me was just the main event and ChatGPT.”
Source→“As Amos Tversky, the Israeli psychologist used to say, he's not interested in artificial intelligence. He's interested in natural stupidity. So I would say I started similarly trying to see how people and animals experience the world.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.