Interview, Explained
In-depth breakdowns of tech interviews — section-by-section analysis with diagrams, quotes, and insights.
~64 minAlex Rives on the data bottleneck behind a world model of life
Biohub's head of science argues virtual-cell AI is held back less by model design than by what instruments can measure, and lays out a 1.8 billion dollar push to generate the cell data a world model of life would need.
~46 minSundar Pichai on why AI compute isn't dark fiber
Alphabet's CEO argues the AI build-out is real demand rather than a bubble, explains why Google spends its scarcest resource, compute, on the frontier before its cloud business, and lays out how it tries to keep recursive self-improvement, the vanishing interface, and its own optimism disciplined.
~40 minDylan Field on Why Design Is the New Code
Figma's CEO argues that as AI commoditizes code and production, the scarce and defensible layer becomes design, point of view, and the human choice to create rather than consume.
~31 minNader Khalil & Sydney Sykes on What AI Can't Commoditize
Two NVIDIA leaders argue that when AI lets anyone build anything, the only durable advantages are the ones it cannot copy: velocity, genuinely hard problems, proprietary and physical data, and the founder's own judgment.
~29 minBen Lamm on running de-extinction like a platform company
Colossal's CEO reframes de-extinction as the demo for a reusable synthetic-biology platform: AI narrows the genome search, the famous animals fund the research, and the real prize is 'programmable life' across medicine, agriculture, and materials.
~59 minJad Naous on why AI solved code but not operations
Grepr CEO Jad Naous argues AI conquered coding because code lives in the same distribution it was trained on, while operating real production systems stays hard — so his bet is to hand the AI a deterministic signal that something changed and let it run a bounded debugging playbook instead of asking it to predict the chaos.
~34 minArsalan Tavakoli-Shiraji on why the best tech doesn't win enterprises
Databricks co-founder Arsalan Tavakoli-Shiraji on why enterprise AI is years behind the valley, and why the winners will own the context, distribution, and domain expertise around the model, not the model itself.
~37 minVijoy Pandey on why every multi-agent system fails silently
Outshift's Vijoy Pandey says connected agents fail silently: bad assumptions compound until three cognitive failures crater measured accuracy from 98% to 16%, and he argues the same probabilistic shift is remaking computing all the way down to quantum.
~52 minZoe Weil on ranking that moves you, not finds things
Sequen reranks retail products in real time from the signals most systems ignore, such as hover time and scroll speed, to influence behavior in a high-intent moment, judging itself by what people buy rather than what they click.
~26 minGary Marcus on why AI only works where answers get verified
Gary Marcus argues today's AI is reliable only where answers can be externally verified, so the hype, the sky-high valuations, and the extinction fears all overshoot what the technology can actually do.
~51 minTerry Angelos on how payment credentials turned AI agents into actors
Once AI agents got access to payment credentials they jumped from recommending purchases to making them, and that one change is forcing a rebuild of the whole trust stack — vaults, tokens, chargebacks, merchant rules, and who is liable when an agent gets it wrong.
~39 minGreg Brockman on why new knowledge from AI is now impossible to deny
OpenAI president Greg Brockman argues AI has crossed from giving answers to generating genuinely new knowledge — pointing to roughly 400 resolved open math problems — and says the same shift is about to rewrite the physics of drug discovery and cybersecurity, with the whole project being to keep humans in the driver's seat.