Interview, Explained
In-depth breakdowns of tech interviews — section-by-section analysis with diagrams, quotes, and insights.
~7 minAidan Gomez on AI Safety Cartels
Cohere CEO Aidan Gomez backs a higher safety bar and public incident reporting, but warns that letting a few frontier labs set and grade the industry's safety rules would build an AI cartel instead of real protection.
~93 minRichard Socher on the Eureka machine that invents most everything
Richard Socher's new lab Recursive automates the one human step left in AI, research itself, to build a self-improving Eureka machine aimed at science, arguing that the real safety work is reward engineering and testing, and that we should regulate AI's specific applications rather than intelligence itself.
~50 minGreg Brockman on the AGI era and pacing the frontier
OpenAI president Greg Brockman argues the AGI era has quietly arrived as a capability, so the hard problem is now pacing it: keeping safety, security, and access ahead of models powerful enough to run for a full day or be deployed ten thousand at a time.
~47 minJensen Huang on why the AI doom predictions are made up
Jensen Huang argues the AI doom predictions are not grounded in science, that real risk sits only where the compute does, and that America wins AI the way it won electricity: by exploiting it broadly on open models, not by slowing down.
~35 minTony Bates on why AI-to-AI service still needs human rules
Genesys CEO Tony Bates argues that AI-to-AI customer service is inevitable, but it will run on the same governance, guardrails, and human hand-offs that already govern human agents — the operating model, not the model, is the hard part.
~65 minMehtaab Sawhney & Mark Sellke on why AI reaches the results humans gave up on
OpenAI's models are producing short, human-like proofs for open math problems, shifting the bottleneck from proving results to understanding and organizing them.
~40 minQuinn Slack on Parallel Coding Agents
Quinn Slack explains how Amp rebuilt its workflow around remote "orbs" — cloud agents that run in parallel — and, for a small trusted team, dropped local dev, mandatory code review, and much of classic CI.
~44 minWorld Labs on new view prediction, a new base-model primitive
World Labs' Atlas model reframes 3D as new view prediction, a base-model primitive on par with next token prediction, unifying reconstruction and generation so a handful of photos can rebuild and re-film an entire scene.
~57 minJeffrey Morgan on Why Open Models Win the Tokens, Not the Budget
Ollama's CEO explains why enterprises are moving the majority of their tokens to open models — cost gets them in the door, control keeps them — and why the durable value is the glue layer that turns a fragmented universe of models, harnesses and hardware into something that just works.
~27 minAnima Anandkumar on One Model for All of Physics
Anima Anandkumar and co-founder Benedikt Jenik are building Accelerated Understanding, a single foundation model for the physical world: many domains of physics in one model, trained on data from numerical simulators and improved by the laws of physics themselves, using neural operators to reach context lengths of trillions where transformers cannot.
~24 minMax Spero on building the internet's trust layer
Pangram co-founder and CEO Max Spero argues the internet needs a trust layer that measures the degree of AI in text and images — not a yes-or-no verdict — so platforms can find what is human and prioritize it as bots, slop, and AI-enabled fraud multiply.
~44 minSean Lie on why yesterday's fast is the new batch mode
Cerebras co-founder and CTO Sean Lie argues that wafer-scale speed is redefining inference: yesterday's fast is becoming batch mode, speed compounds into smarter agents, and the real frontier is moving to integration beyond the single chip.