Sabi CEO Rahul Chhabra argues in an essay that brain computer interfaces should read people's intent and preferences to direct AI agents, not mimic keyboards
Context
The essay lays out the pitch behind a newly funded startup that wants AI to take instructions from brain signals, an idea that is still largely unproven.
This is an essay by Rahul Chhabra, the CEO of Sabi, which is building a brain reading cap, so it also promotes his own company. Sabi announced a $50 million seed round led by Khosla Ventures on October 9, and its cap is not yet on sale.
Deep dive
On October 17, Rahul Chhabra published an X article titled What if AI could read your mind? He opens by writing that Hans Berger invented EEG in 1924 hoping to build telepathic communication, and that advances in neural sensors and deep learning now make that dream possible with devices as simple as the baseball cap Sabi is building.
He argues the field has focused on brain computer interfaces that emulate mouse clicks and typing, which he calls the wrong target. Since computers are now AI models that get work done, he writes, the limit is how much they can understand without being told. He suggests decoded intentions could serve as prompts for agents, and that brain signals could reveal people's taste, such as which music moves them or which AI responses feel like slop.
Chhabra writes that Sabi has trained a typing model that can predict a user's next three to four keystrokes. That is his company's claim and has not been independently verified. He quotes Vinod Khosla telling Forbes that typing is not natural, a quote Forbes published on October 9.
He says none of this works without trust, and that neural data must stay encrypted. He ends by arguing that coupling human and machine minds closely offers a path to long term AI alignment.
Forbes and WIRED have described Sabi's technology as early, and Sabi says it plans to demonstrate early versions at CES 2027.
What to expect next
Watch for Sabi's planned demonstration at CES 2027, which should show whether its cap can decode intent reliably outside a lab.
Also watch for independent tests of noninvasive brain reading accuracy, and for rules on how neural data is stored and shared, since Chhabra himself says the idea depends on trust. Rival approaches, from implanted devices such as Neuralink to other wearables, will shape whether his view of the field catches on.