Interview, Explained
In-depth breakdowns of tech interviews — section-by-section analysis with diagrams, quotes, and insights.
~35 minZach Lloyd on the software factory you define in code
Warp's CEO reframes agentic coding as an engineering discipline: define your software factory in code, store and measure every agent run, and tune it like any other system — the payoff is a self-improving pipeline, and a new job called factory engineering.
~6 minWill Manidis on Why AI's Winners Own the Rails
As the cost of frontier intelligence collapses, Manidis argues the lasting economic gains flow not to the labs that build AI but to the firms that own the rails and distribute it into the real economy.
~25 minRichard Socher on the Eureka Machine
Richard Socher argues AI's next frontier is scientific discovery — making biology programmable, writing proteins like language, and improving its own research — while regulation should target harmful uses, not intelligence itself.
~45 minJosh Gruenstein on robotics as the ultimate systems problem
Tutor Intelligence deploys real robots into American factories and warehouses to earn the data that trains its models, treating robotics as one compounding system rather than a stack of separate bets.
~67 minJacob Lauritzen on building a legal agent that never sees your data
Legora builds its legal agent blind, never seeing a client file, so it tests in simulated worlds built by lawyer-engineers and anchors every answer to a clickable citation.
~26 minAman Singh on running a firm where agents prompt people
Aman Singh, who leads AI at the AI-native wealth firm Arca, explains how owning the harness, persistent client memory, deterministic guardrails, and edge-based injection defenses let agents run proactive, multi-day financial workflows with a human in the loop for anything that moves money.
~27 minJoseph Kim on the 20% the base model won't build for you
OpenAI's ChatGPT-for-finance lead on why the base model is only the easy 80% of a product, and why the hard, durable 20% is in-house data, an org-chart safety model, taste trained from human judgment, and evals that predict the job.
~52 minJay Madheswaran on law's one real bottleneck: labor, not software
Eve's CEO argues plaintiff law was never short on software — it was short on labor, so AI that removes that constraint doesn't cut jobs, it multiplies how many people a firm can represent.
~49 minPaul Copplestone on building for agents, not just humans
Supabase's Paul Copplestone explains how a database company re-architected itself around agents — code-first interfaces, self-healing error messages, and a personal data layer you own — now that 70% of new activity comes from AI, not humans.
~11 minMatt Garman on the $580B Backlog Behind AWS's Growth
AWS's CEO argues its 40%-growth forecast is less optimism than bookkeeping — a $580B committed backlog, demand spread across every industry, and a buildout now capped by power and chips rather than by customers.
~7 minChris Urmson on Scaling Driverless Trucks From Proof to Profit
Aurora co-founder and CEO Chris Urmson explains why, with the self-driving problem largely solved, scaling driverless trucks is now a story about manufacturing rigor, utilization economics, a two-step path to profit, and a driver shortage with rare bipartisan backing.
~38 minJake Stauch on Why the Guardrails Are the Product
Serval's CEO argues that in the enterprise the guardrails (deterministic approvals, least-privilege permissions, audit trails) are the real product, and that they grow more valuable as the agents they wrap get smarter.