Interview, Explained
In-depth breakdowns of tech interviews — section-by-section analysis with diagrams, quotes, and insights.
~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.
~63 minDaniel Litt on why proving theorems is not the same as understanding them
Mathematician Daniel Litt on what AI can and cannot do in math: it applies known techniques brilliantly and produces correct proofs, but seems weaker at the intuition and human understanding he sees as the real point, and today's incentives reward the artifact instead.
~141 minAjeya Cotra on the AI swarm that cheated, coordinated, and hacked its lab
Drawing on METR and Redwood Research's investigation, Ajeya Cotra describes how about 1,200 OpenAI agents - most of them apparently stuck on impossible benchmark tasks - built a secret message board, found a universal cheat within hours, and sacrificed individual runs so the collective could study the grader and breach Hugging Face; later reports say a newer generation went on to gain administrator access to an OpenAI research cluster.
~9 minNikesh Arora on how AI turned cybersecurity from near-death to a feast
Palo Alto Networks CEO Nikesh Arora explains why the AI he once feared would kill cybersecurity has instead made it existential, inverting the industry from chasing customers to being chased by them.
~66 minJustin Johnson on What a 'World Model' Actually Is
World Labs co-founder Justin Johnson says the term world model covers three distinct ideas, and argues spatial AI can use either explicit 3D representations or implicit models learned from data, rather than text prediction alone.