The first minutes decide what the rest of the round is about. This is the first step of our method. By the end of this lesson, you will ask two opening questions that each change what you would build, and in a 45-minute case you will commit to a first version by minute ten, with your assumptions said out loud.
We use one example through this lesson and the next six. The interviewer’s brief: “A hospital network’s patients who need an interpreter wait too long, and some appointments go ahead without one. The director of patient experience wants an AI translation app on every ward tablet. You have the interpreter request log and the outpatient appointment schedule.”
What goes wrong when you solve first
You will learn to hear solving first in your own voice, and name what it costs. A Palantir-tagged user on Blind who says they worked there wrote, in March 2025, in a thread about Palantir’s interview, that a bad decomposition looks like this: “don’t ask questions, make large assumptions without clarifying with interviewer, misunderstand the problem before jumping in, provide impractical solutions, don’t expand or provide possible optimizations to your original v0 solution.” Source 1Palantir FDSE Interview (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 2Update: interview experience - Palantir new grad FDSE interview (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind The first three items on that list happen in the first minutes.
The same point shows up outside Palantir. One candidate’s report on Aced, posted in August 2026 about an entry-level Databricks loop that ended in an offer, calls decomposition the most important round and says they had to “treat the interviewer almost like a client and clarify stakeholder, scope, and KPI before touching architecture.” Source 3Databricks Forward Deployed Engineer Interview ExperiencePublisherAced (formerly Exponent)Source typecandidate’s personal write-up Use that as your minute-one checklist: who it is for, how big it is, and which number has to move.
Here is solving first on the interpreter case:
Candidate: I’d put a speech-to-text model and a translation model behind a tablet app, streaming so the delay stays under a couple of seconds. Each ward gets a tablet, and we log every session for quality review.
It sounds competent and misses the two facts that decide this case, and one question would have found each. Hospital policy requires a qualified interpreter for informed consent, so the app cannot touch the conversations that matter most. And the network already pays for a video-interpreting service that nobody uses. The candidate designed a system for a problem they never defined.