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Two recent Bay Area senior AI/ML offers had a pretty interesting tradeoff. One is from LinkedIn, with lower headline TC but more predictable public-company compensation. The other is from Harvey, with higher first-year TC and a much larger equity gra
Meta is preparing to release Muse Spark 2.0, while Chinese models are already flooding the market. Inference costs will keep collapsing. Tokens will become dirt cheap, and “good enough” models will satisfy the majority of enterprise use cases. Anthro
I have Figma’s AI Design Architecture and AI Live Coding rounds coming up and I’m not totally sure what to expect. The architecture round was described as adding AI-powered requirements into the system design. Does that mean something like designing
Grok 4.5 and Meta’s Muse Spark 1.1 both just dropped, and both seem heavily focused on coding / debugging / agentic workflows. It feels like AI coding tools are moving from “autocomplete” to something closer to “junior engineer that can execute tasks
Genuine question: With AI coding tools getting better, why are coding interviews still so focused on solving problems under pressure without much real-world context? I get that companies still need to test fundamentals. But in actual work, engineers
