Dwarkesh Patel has been advocating for continual learning in AI, arguing that frozen models are limited and that continual learning is necessary for long-running, open-ended problem solving. The autho…
The author announces a shift away from covering LLM agents to exploring deeper historical and fundamental questions about AI automation, specifically what humans will do when their work is automated a…
A developer cut an AI agent's token use by 94% and latency by 87% by compiling a natural-language skill into a specialized Python harness that calls an LLM only for selection and generation, replacing…
Cognitive debt, the inability to keep up with code generated by AI agents, is reframed as leverage that can accelerate development but risks creating systems no human understands. Drawing on Peter Nau…
Vivek Haldar argues that local AI agents running on a personal machine are superior to cloud-based agents for individual work, citing advantages like full filesystem access, persistent memory, and pri…
Vivek Haldar, a former heavy Emacs user, has abandoned the text editor after decades of use because AI agents have replaced it as his primary computing interface. Haldar's GitHub commits have surged w…
A New York Times op-ed by Jasmine Sun warning that AI could create a permanent underclass has sparked debate in Silicon Valley, with proponents of the Jevons paradox arguing that cheaper AI will incre…
Software engineering job postings have surged since mid-2025, particularly in AI-exposed industries, according to a Citadel Securities report, while a Stanford study shows actual employment among juni…