Interview, Explained
In-depth breakdowns of tech interviews — section-by-section analysis with diagrams, quotes, and insights.
~17 minBret Taylor & Clay Bavor on renting intelligence, owning context
Sierra's Bret Taylor and Clay Bavor argue that as intelligence turns cheap and abundant, every durable advantage — owning context, selling outcomes, earning public consent, matching the right model tier to each job — lives in what you build around the model, not in the model itself.
~23 minJay Parikh on rebuilding every layer of GitHub for agents
Microsoft's CoreAI lead walks through what it takes to run GitHub when agents already open 40% of pull requests: rebuild every layer, make the old workflow optional, route across models, keep the quality bar from slipping, and tie token spend to outcomes.
~104 minJoshua Monrad on the biodefense gap AI is widening
AI will make engineered pandemics possible long before the world can defend against them, so Monrad argues the window to harden biosecurity - and maybe to pause - is closing fast.
~32 minRonak Malde on continual learning as the next learning paradigm
Trajectory's co-founder argues that continual learning — models that keep improving from real production use rather than one-off lab training — is the next paradigm, and shows a one-click platform that already took a legal model from 4% to 18% accuracy while running six times cheaper.
~9 minKeller Rinaudo on why making delivery better grows the market
Zipline's CEO argues autonomous drone delivery is not fighting for a fixed market — a decade of flying where it was illegal built the safety record, and making delivery about ten times better is growing demand about ten times, from African hospitals to Walmart and Uber.
~22 minLin Qiao on why AI agents are only as smart as your data
Fireworks AI CEO Lin Qiao argues that once general models commoditize intelligence and coding agents make any product easy to clone, the only durable moat left is your own proprietary data, turned into specialized, energy-efficient models you control.
~54 minVlad Tenev on why broad ownership keeps a society stable
Robinhood and Harmonic founder Vlad Tenev argues that broad ownership — pushed into tokenized stocks, private markets, agentic trading, prediction markets, and even AI-driven math — is the antidote to a fragile, centralized economy.
~72 minShawn Wang on How a Job Title Built an Industry
The host of Latent Space explains how naming the 'AI Engineer' turned non-prestigious work into a global discipline, why cheap code is now dissolving the software business underneath it, and why he still thinks the honest default for AI is doom.
~50 minDavid Pawlan on why trust, not capability, decides which agent you keep
After hands-on testing of 147+ consumer AI assistants, David Pawlan argues the thing that decides which agent people keep is not raw capability but trust, and that insight explains the category map, the collapsing switching cost, the real moat, and the race for your personal data.
~24 minTekedra Mawakana on why safety, not perfection, is the bar
Waymo's co-CEO argues the robotaxi debate is framed wrong: the benchmark is not a flawless machine but the deadly status quo of human driving, and her choices on price, hardware, competition, and jobs all follow from putting safety first.
~21 minLouis Mosley on why Europe's slow AI adoption could leave it uncompetitive
Palantir's Louis Mosley argues that the real split between American and European companies is the rate of AI adoption, not fears over sovereignty, and that the gap could leave Europe's blue chips uncompetitive within five years.
~48 minRichard Socher on Where AI Goes Superhuman First
Richard Socher argues AI goes superhuman wherever a problem offers unlimited data, a simulation, or a fast verifier — so building a scientific discovery engine is less about smarter models than about engineering verifiable environments and the rewards inside them.