By FDE Interview Prep, a SourceStrongAI company

On this page15 sections
  1. The round in one exchange
  2. What it is
  3. What employers say they look for
  4. What candidates report
  5. The method
  6. Worked case: building permit delays
  7. More worked cases
  8. How it differs from system design and client simulation
  9. Practice prompts
  10. Go deeper, by how long you have
  11. The pass rate no one can source
  12. Your next step
  13. More posts on this topic
  14. Questions people ask
  15. Keep reading

Your next round is called decomposition, and unlike coding there is no problem list to grind and no obvious way to tell a good answer from a ramble. A decomposition interview hands you a vague customer problem that has more than one reasonable answer, and you work out loud from that problem to a concrete approach and a first version that works. Palantir, the employer most tied to the round, says on its careers site that open-ended technical questions are “a key part of the process.” Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page Its guide to those questions gives one piece of interview advice: “articulate the alternatives and trade-offs,” arrive at “some concrete approach,” and “deliver a functioning idea first, then expand it afterwards.” Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

This guide is part of the FDE interview guide and serves both kinds of role: the round is best documented at Palantir, and the skill it tests is the one AI labs and AI product companies hire FDEs for too. If you would rather feel the round first, sign in and run the free building permits case: 10 minutes against a deputy mayor who answers only what you ask.

The round in one exchange

Here is the whole round in miniature: one prompt, two ways to open, and the method that gets you from one to the other.

“Our claims take too long. The COO wants an AI for intake.”

The weak opening starts building what was asked for:

“I’d build an agent that reads the first-notice form, pulls out the policy and the loss, and routes the claim to the right adjuster ...”

The strong opening asks the one question that decides whether the agent matters at all:

“Before the agent: too long from when to when? First report to first contact, or to first payment? If the days pile up after intake, an intake agent can’t touch them.”

The weak opening may describe a fine agent. It also bets the project on something nobody has checked, that intake is where the time goes. The strong opening finds out first, and it still gets to the agent, later, where it can move the number.

Our method on one screen

  • Clarify. Ask only the questions whose answers change what you build, then commit to an assumption you label out loud.
  • Stakeholders and the metric. Name who decides, who uses it, who owns the data and who can block it; pick one number, with a guardrail and an owner.
  • Inputs. For each data source, say who owns it, how fresh it is, what is wrong with it and who grants access.
  • Order the work by risk. Put the riskiest unknown first, and say the order you turned down.
  • . Build the thinnest version that runs on real data for a real user making a real decision, and say what you fake.
  • Failure modes. Name different kinds, each with a signal you would see in the first week.
  • Close in four parts. Say the problem, the first version, the biggest risk and what you do on Monday.

This is our method, not an employer’s rubric. Each step is worked below, on this insurer, with the words to say.

What it is

A gives you a problem stated the way a customer states it: “our buses are unreliable,” “claims take too long,” “we want an AI agent.” There is no spec. The interviewer answers your questions, sometimes plays the customer, and watches how you get from the vague sentence to something a real user could use.

Palantir’s early-talent application timeline, a graphic on its careers page, lists the virtual onsite as two one-hour interviews, learning and decomposition, with behavioral and technical questions. Source 2Students | Palantir Careers (timeline image: RecruitingTimeline_V3.jpg)PublisherPalantirSource typecompany hiring page Its competency guide calls the skill “Navigating Open-Ended Questions”: tackling technical challenges “with multiple possible solutions that will incur different trade-offs.” Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

The word comes from the job, not the interview. In an April 2019 post on Palantir’s blog, a Delta, Palantir’s name for a forward deployed engineer, named “technical decomp” as a skill the job needs: “Our job is to take a high-level problem, ‘decompose’ or break it down, and design a solution.” Source 3Dev versus Delta: Demystifying engineering roles at Palantir (Palantir Blog; archived copy)PublisherPalantir Technologies (Palantir Blog on Medium)Source typearchived company page

The names it goes by

You may never hear the word “decomposition.” Listen for these:

  • Decomp, or the open-ended round. Palantir’s guide is titled “Navigating Open-Ended Questions,” and a Palantir-tagged Blind user wrote, in July 2020, that “decomp is about breaking down complicated and ambiguous problems.” Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring pageSource 4Palantir onsite (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 5Prep for 'decomp' interview at Palantir (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind
  • “High level problem solving interview.” One candidate on Blind wrote, in March 2023, that the recruiter called it a “high level problem solving interview,” and that the wording used to describe it said it “will be a data-focused open ended problem.” Source 6Palantir Decomposition Interview Tips (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind The candidate guessed it was the decomposition round.
  • Analytical Decomp. A Blind poster used the name in April 2022, asking what to expect in the Analytical Decomp interview for Palantir’s role. Source 7Palantir Deployment Strategist Interview (Blind)PublisherBlindSource typecandidate report on BlindSource 8Palantir Deployment Strategist (Blind)PublisherBlindSource typecandidate report on Blind
  • Case study. At least one FDE-type posting lists a case study interview without describing it: as of September 2026, Attio’s Forward Deployed GTM Engineer posting. Source 9Forward Deployed GTM Engineer @ AttioPublisherAttio (Ashby job posting)Source typecompany job posting It may or may not be the same round.

Not only Palantir

The skill travels. Ben Kracker, a forward deployed engineer director at Salesforce, said on Salesforce’s blog, in November 2025, that problem-solving is the number one skill an FDE needs, and that FDEs peel back a request to give customers the right solution, not the one they asked for. Source 10Today's Hottest Role: Forward Deployed EngineerPublisherSalesforce 360 BlogSource typecompany blog As of September 2026, Cohere’s Agentic Platform FDE postings ask for turning “ambiguous business problems into well-framed agentic workflows with clear success criteria.” Source 11Forward Deployed Engineer, Agentic PlatformPublisherCohere (Ashby job board)Source typecompany job posting

On the AI lab side, The Pragmatic Engineer quoted Colin Jarvis, then OpenAI’s head of forward deployed engineering, in August 2025: “often what the customer describes in scoping doesn’t match the data/system reality on the ground.” Source 12What are Forward Deployed Engineers, and why are they so in demand? (Gergely Orosz)PublisherThe Pragmatic EngineerSource typenews report That gap between the request and the reality is what a decomposition round puts in front of you.

What employers say they look for

No employer publishes a decomposition rubric. What they do publish is a short list of behaviors, and each one becomes a sentence you can say about the insurer.

What they publishWhat it sounds like
Alternatives and trade-offs“Two ways in: build the agent, or measure where the days go. I’ll measure first: if the days aren’t at intake, the agent can’t move the number.”
A concrete approach“First version: a morning list of claims waiting on a document, for the intake reps.”
A working idea first“This runs on Monday’s data. Once the reps use it, the agent drafts the requests.”
Thinking out loud“I’m asking this because the answer changes the design.”

The first three rows are Palantir’s own advice on open-ended questions. Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page Palantir explains the emphasis this way: “Urgent real-world problems need solutions fast — which means they need to work before we have time to make them perfect.” Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

The fourth comes from Palantir’s recruiting blog, which in August 2022 told intern and new-grad candidates to share questions and observations so interviewers can see how they approach the problem. Source 13From Pipeline to Prospect: Insights and Advice from Palantir Recruitment (Palantir Blog; archived copy)PublisherPalantir Technologies (Palantir Blog on Medium)Source typearchived company page Palantir’s onsite guidance says the same in fewer words: talk through how you plan to approach the problem, and ask questions if necessary. Source 14Palantir Careers | Getting HiredPublisherPalantirSource typecompany hiring page

Also worth knowing:

  • It is a conversation. A quoted on Palantir’s blog described their interviews as very interactive, “how would you approach this problem?” sessions worked through with the interviewers. Source 15Interviewing at Palantir: Advice from Palantirians (Palantir Blog; archived copy)PublisherPalantir Technologies (Palantir Blog on Medium)Source typearchived company page
  • Business and technical reasoning both count. First Round Review reported, in February 2026, that Palantir’s former FDE recruiting lead said these interviews aimed to assess both. Source 16So You Want to Hire a Forward Deployed EngineerPublisherFirst Round ReviewSource typenews report

At least one AI product company tests something close in its own format. Sierra says it replaced coding and algorithms interviews in its engineering process with an AI-native onsite that opens with a Plan session, in which the candidate drives the ideation of a product to build while interviewers ask questions (its post covers engineering hiring in general, not a forward deployed role). Source 17The AI-native interviewPublisherSierraSource typecompany blog

What no one publishes

We found no employer that publishes a scoring rubric or a pass rate for the decomposition round. The post on what the decomposition round tests sets out what is published and how to prepare against it.

What candidates report

Candidate reports show what happened to one person, once. Read them for the range of prompts and formats, not for a pattern. Every item here is labeled with who reported it and when.

At Palantir

  • Where it sits. Three Blind posters, between September 2021 and March 2025, mention a decomposition round at Palantir, for FDSE, software engineer and Deployment Strategist roles; two of them wrote before their interviews. Source 18Palantir FDSE Interview (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 19Palantir Interview London HELP !!! (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 20Palantir Deployment Strategist Interview Prep (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind
  • A full loop. One candidate reported, in December 2025, a Government-track FDSE loop whose “VO1 (Decomp)” round was 15 minutes behavioral and 45 minutes technical, and in which they were “shown multiple interconnected datasets and diagrams and asked to design a system around them”; a and a hiring manager round followed. Source 21Palantir FDSE Full Interview Loop Process (post by u/Not_the_Sauron)PublisherReddit r/csMajorsSource typecandidate report on Reddit
  • Inside a screen. A second candidate reported, in August 2025, a Palantir FDSE technical screen of 20 minutes of decomposition, on an app that connects users based on shared interests, and 20 minutes of coding. Source 22Palantir FDSE Interview (rejected but idk why) (post by u/Master_el)PublisherReddit r/csMajorsSource typecandidate report on Reddit
  • With a coding follow-up. One candidate reported, in March 2025, a one-hour “Decomposition & Analytics” interview that asked them to design a system where users share interests, then implement search(user_id, users). Source 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on Reddit It is worked below, under shared interests.
  • Abstract on purpose. A commenter wrote, in May 2026, that their onsite decomp was a “super abstract problem that you can drive how ever you want,” and that they received an offer; they posted in a thread titled “Palantir FDSE Technical Interview” but did not name the company or role themselves. Source 24Palantir FDSE Technical Interview (comment by u/MShakeed)PublisherReddit r/csMajorsSource typecandidate report on Reddit
  • Starting from a feature. On Blind in January 2025, a commenter who did not name their role replied to a post about a Palantir FDSE “data-focused open ended problem,” and wrote that it starts from a random feature. Source 25Palantir FDSE InterviewPublisherBlind (teamblind.com)Source typecandidate report on BlindSource 26Palantir FDSE Decomp/System Design InterviewPublisherBlind (teamblind.com)Source typecandidate report on Blind The order they gave: which features are P0, then data models, databases, what to analyze, which KPIs and what to present to executives.

Elsewhere

One candidate’s report on Aced (formerly Exponent), for an entry-level Databricks FDE role interviewed for in February 2026 and posted in August 2026, called the decomposition round the most important of the loop: “I had to treat the interviewer almost like a client and clarify stakeholder, scope, and KPI before touching architecture.” Source 27Databricks Forward Deployed Engineer Interview ExperiencePublisherAced (formerly Exponent)Source typecandidate’s personal write-up

A Blind comment about Databricks is worth knowing too. Replying to a Blind poster with an upcoming Databricks FDE design-and-architecture round, one commenter, who does not say how they know, wrote in September 2026 that it covers both data engineering and ML, and that interviewers focus on “FDE mindset rather than what tools you are using.” Source 28FDE interview at Databricks (Blind)PublisherBlindSource typecandidate report on Blind

By role

Reports about different roles stress different things.

  • Deployment Strategist. On Blind in September 2021, a user shown as a Palantir employee told a candidate preparing for a Deployment Strategist interview that problem solving and “customer polish” are the key things they look for, and to be ready for the decomp question. Source 20Palantir Deployment Strategist Interview Prep (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind In a separate Blind thread, in October 2022, a commenter who got an offer wrote that for Deployment Strategist they “don’t care too much about being super technical”: “As long as you can think in data terms it’s enough.” Source 7Palantir Deployment Strategist Interview (Blind)PublisherBlindSource typecandidate report on BlindSource 8Palantir Deployment Strategist (Blind)PublisherBlindSource typecandidate report on Blind
  • FDSE. Two reports describe a breakdown followed by code. One is the March 2025 FDSE candidate above; in the other, a commenter reported, in May 2026, a Palantir “coding +“ round that began with breaking down a real-world tool and then implementing a related function. Source 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on RedditSource 29Palantir FDSE Technical Interview (comment by u/shinji_dontdotoomuch)PublisherReddit r/csMajorsSource typecandidate report on Reddit That commenter posted in a Palantir FDSE thread but did not name their own role.

What to take from the reports

Formats differ, from a short slot inside a screen to a full hour. Some prompts come with data: two Palantir new-grad candidates on Blind, in threads from 2022, said theirs did, one with a sample dataset and one with London taxi records. Source 30Palantir Learning & Decomposition Interview (Blind)PublisherBlindSource typecandidate report on BlindSource 31Update: interview experience - Palantir new grad FDSE interview (Blind)PublisherBlindSource typecandidate report on Blind Some prompts come with nothing but a sentence, and some end in code.

So prepare one method that works at any length, and practice it three ways: on a sentence, on a dataset, and on a prompt that ends in a function. For a Deployment Strategist role, rehearse the customer half until it sounds polished and put the data in plain words. For an engineering role, make sure the entities you name in the breakdown are the ones your code takes. The post that works a reported Palantir prompt from start to finish shows what that sounds like at speed, and the post on decomposition interviews that come with a dataset covers the data end.

The method

This is our method, a scaffold for thinking out loud. It is not an employer’s rubric, and no interviewer is checking you against it. We name the six steps so you can say where you are. The last two carry Palantir’s published advice, a concrete approach and a working idea first; the rest are ours. The decomposition method module teaches each step, and its first lesson, the open-ended round and the method on one page, is free.

A Palantir-tagged Blind user who said they had worked there wrote, in March 2025, that there is no one-size-fits-all answer, then suggested asking questions, breaking the problem into parts, building a practical solution within the constraints and then expanding that v0. Source 18Palantir FDSE Interview (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 19Palantir Interview London HELP !!! (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind The six steps below give each of those moves a name.

The running example is the insurer from the top of the page: a regional home insurer says claims take too long, and the COO wants an AI agent to handle claims intake. It fits both kinds of FDE role: the ask is an agent, and the lever is probably in the claims system’s data.

Step 1: clarify before you solve

Ask the few questions whose answers would change what you build, then stop and commit.

“When you say too long, from when to when: first report to first contact, to an adjuster assigned, or to first payment? And who is complaining: policyholders, agents or the regulator?”

Each answer flips a choice. If the complaint is first contact, intake is the problem and an agent might help. If it is first payment, the time is probably spent waiting for documents or an adjuster, and an intake agent touches none of it.

Then commit, out loud, with a labeled assumption:

“I’ll assume the complaint is time to first payment on simple water-damage claims. That’s my assumption, and I’ll check it against the data first.”

The common mistake is asking forever. When the interviewer answers with “What do you think?”, don’t ask again: state an assumption, write it down and move on. The post on clarifying questions lists what to ask first and what to skip, and the lesson Clarify before you solve drills it.

Step 2: stakeholders and the metric

Name who decides, who uses it, who owns the data and who can block it. Then pick one number.

  • Sponsor: the COO, who reports claim cycle time to the board.
  • Users: intake reps and desk adjusters.
  • Can block: claims counsel, who will not let software send anything that reads as a coverage decision.
  • Owns the data: IT, which runs the claims system.

“The metric is median days from first report to first payment on simple claims, with today’s value as the baseline. The guardrail is reopened claims, so we don’t get faster by paying wrong. The claims VP reads it every Monday.”

A metric with no guardrail can be gamed, and one with no owner is never read. The post on choosing a success metric works through the number, its guardrail and its owner on two cases.

Step 3: inputs, owners and freshness

For each data source, say who owns it, how fresh it is, what is wrong with it and who says yes to access.

“The claims system’s status history: IT owns it, there’s a nightly export, and I’d ask whether statuses are set by the system or typed by an adjuster, because typed ones drift. Adjuster notes: free text, the only place the reason for a delay lives. Assignment: I’d ask how a claim gets to an adjuster today, because that’s often one person with a spreadsheet.”

The last question finds the manual process hiding in the data, and that is where many cases turn. The question about who sets a status is the one that saves you in Step 6.

Step 4: order the work by risk

Put the riskiest unknown first, and say the order you rejected.

“First, measure where the days go, by stage, from the status history. Data access starts the same day, in parallel. I’m not starting with the agent, because the agent speeds up intake and I don’t yet know that intake is where the time goes.”

That last sentence is Palantir’s “alternatives and trade-offs” in practice: you considered the obvious order and turned it down for a reason.

Step 5: the walking skeleton

A walking skeleton is the thinnest version that runs end to end on real data for a real user making a real decision. Say who uses it, on what data, for which decision, and what you fake.

“Each morning, intake reps get a list of every open simple claim still waiting on a document, oldest first, from the status history. Real: the claims and their status. Faked: which document is missing, which a rep reads from the file by hand for now. What it teaches us: whether missing documents are where the days go.”

The lesson The walking skeleton covers what to fake and what never to fake.

When the ask is an agent

The agent comes back once the list shows that waiting on documents is where the days go. It serves that lever: it drafts the request for a missing document, and a person stays between the draft and the policyholder. Say where it fits and how you will know it is safe to launch:

“The agent drafts the document request; a rep sends it. Before launch I’d build an eval set from requests reps have already written, grade each draft send-as-is, edit or wrong, and launch when wrong is rare enough that claims counsel signs off.”

In words: a graded set of past cases, a written definition of wrong, a launch bar agreed before the build, and a review that keeps running after launch. On the board it might read like this. The numbers are ours, for the exercise; what matters is that each one is written down before launch.

Eval plan: document-request drafts
  Set: 200 past simple claims, with the
       request a rep actually sent
  Grade each draft: send as-is / edit / wrong
  Wrong = asks for the wrong document,
          names a term not in the policy,
          or reads as a coverage decision
  Launch bar, agreed with counsel first:
    0 drafts that read as decisions
    under 5% wrong overall
  After launch:
    a rep reviews and sends every draft
    a senior adjuster regrades 20 a week

That is the job, not only the interview. As of September 2026, OpenAI’s healthcare FDE posting lists defining evaluations and against customer-specific acceptance thresholds as part of the role. Source 32Forward Deployed Engineer (FDE), Healthcare - SFPublisherOpenAI (Ashby)Source typecompany job posting At least one interview has probed it: one Google FDE candidate reported on Blind, in July 2026, a system-architecture round where he chose an agent-design track, in which the interviewer played the CTO of a company wanting an AI-powered system, and the discussion covered scoping, deployment and evaluation. Source 33FDE Interview Experience at Google (L4) (Blind)PublisherBlindSource typecandidate report on BlindSource 34Google Forward Deployed Engineer Interview Experience (Blind)PublisherBlindSource typecandidate report on BlindSource 35Is Google FDE interview same as SWE? (Blind)PublisherBlindSource typecandidate report on Blind The post “We want an AI agent” works a similar insurer’s agent request end to end: one workflow, a baseline, an eval set and a launch criterion.

Step 6: failure modes

Name the ways this fails, of different kinds, each with a signal you would see in the first week.

  • Data: status codes used differently by each office, so a stage looks long when it is mislabeled. Signal: stage times that differ wildly between offices.
  • Harm: a drafted message that reads as a coverage decision. Response: a rep sends every message, and claims counsel approves the templates.
  • People: adjusters judged on claims closed may pick the easy ones from the list. Signal: the oldest claims on the list stop moving.

The check for the data risk is one query: what share of each office’s status rows use each code. An office that never uses PENDING_DOCS may not be faster; it may be labeling differently. In words: count each status per office, and read the codes side by side.

SELECT c.office, s.status, COUNT(*) AS n,
  ROUND(100.0 * COUNT(*) /
    SUM(COUNT(*)) OVER (PARTITION BY c.office), 1) AS pct
FROM status_history AS s
JOIN claim AS c USING (claim_id)
GROUP BY c.office, s.status
ORDER BY s.status, c.office;

Close in four parts

When time is nearly out, say the problem, the first version, the biggest risk and Monday. Keep a hypothesis a hypothesis: you have not measured anything yet.

“To close: my hypothesis is that the days go to waiting for documents, not to intake, and the first version tests that. The first version is a morning list of open simple claims waiting on a document, oldest first. The biggest risk is that offices use status codes differently, which I’ll check against a sample of files. On Monday I’d ask IT for the nightly export.”

When the interviewer pushes

Knowing the forward path is not enough. Practice what you do when a constraint changes under you. These four pushes are our practice set, not a list of what interviewers say. Rehearse each reply until it comes out without a pause.

  • “That data doesn’t exist.” Say: “Then the first version collects it: the rep marks which document is missing, and in two weeks we have the field.”
  • “Legal won’t allow anything customer-facing.” Say: “Then the agent drafts for a rep and never sends; counsel approves the templates.”
  • “The COO wants a demo next week, not a report.” Say: “The demo is the morning list on real claims. The agent is the second demo, once we know it moves the number.”
  • “You have half the time.” Name the step you are skipping and why: “With half the time, I’ll skip mapping every source and work from the status history alone, because the first version runs on it.”

Each reply keeps the goal and changes the path. None of them argues with the customer or starts over.

Our time budget for the 45-minute case

This pacing is ours, not an employer’s. It is how we pace the 45-minute case, and it scales to whatever length your round has.

StepWhere to be
Clarify and the metricFirst 8 minutes
Inputs and the order of workWithin 15 minutes
Walking skeletonCommitted within 20 minutes
Failure modes and deepeningUntil 40 minutes in
Close in four partsLast 3 minutes

In a longer round, stretch the deepening, not the clarifying. In a short slot inside a screen, ask two clarifying questions, commit to the first version by the halfway mark, and spend what is left on one risk and the close.

Two threads through every step

Narration. Say which step you are in as you enter it, and write each fact on the board the moment you hear it.

Concreteness (the technical decomposition). Name the entities and their keys, one interface with its fields, and one volume estimate that decides a design choice. The Palantir Delta quoted above called the job skill technical decomp; in our method it means that once you know what to build, you break it into entities, interfaces and one volume check that picks the design. For the insurer: claim(claim_id, policy_id, office, loss_type, reported_at), status_history(claim_id, status, changed_at), and “a few hundred new claims a day is one query on a reporting copy, not a pipeline.”

A board at the end of the insurer run might read like this. In words: the six step names down the side, with each fact written under its step the moment you hear it.

Clarify
  "Too long" = to first payment
  [A] simple water-damage claims
Stakeholders and metric
  COO, reps, adjusters, counsel
  Median days to first payment
  Guardrail: reopened claims
Inputs
  Status history (IT, nightly)
  Who sets a status? System or typed
  Adjuster notes: free text
Workstreams
  1 Where do the days go?
  2 Data access, in parallel
Walking skeleton
  Morning list: waiting on a doc,
    oldest first
  Later: agent drafts, rep sends
Risks
  Status codes differ by office
  Drafts that read as decisions

Worked case: building permit delays

Run it before you read on

This section gives away the case’s first move. Run the free permits case first if you want to find it yourself.

The brief: a city’s building permits take months, and the mayor wants weeks. The mayor has already promised an AI review tool. You have the permit system’s status history and reviewer assignments. It is our flagship case, and it is built for the trap in the brief: a tool promised before anyone measured where the time goes.

We wrote two calibration runs of this case to test our scorer. They are samples we wrote, not real candidates, and they show the difference between a strong run and a stalled one better than any rubric.

The strong run, in four moves

It asks nothing about the AI tool:

“Before we talk about any tool: when the mayor says permits take months, months from when to when? What number is she quoting, and is it the same number the building department reports?”

The answer names three different clocks: the mayor’s, the department’s and the applicants’. The strong run picks the mayor’s clock as the target in the next breath, and puts the other two beside it:

“I’d propose we aim at the mayor’s clock, received to issued, because that’s the one being judged in public, and report the department’s and the applicants’ clocks beside it so nobody can improve one by pushing time into another.”

The move: pick one clock and name the others as guardrails, so the metric can’t be gamed.

From there it follows one application through the building, one question per answer. The sponsor then says homeowners filing their own small projects are returned far more often than developers.

8:35 Candidate: “That kills my assumption from a few minutes ago: the returns are mostly homeowners, not big projects. It changes two things. Whatever applicants see has to work for someone who has never filed a permit, and we report homeowners’ times separately, or an improvement for expeditors will hide a homeowner problem.”

The move: a guess labeled as a guess, dropped out loud the moment a fact kills it, and the design changes with it.

9:55 Candidate: “Then here is the first version I’d commit to, and I’m putting it on the board now. A weekly stage-wait report ... by permit type and by homeowner versus professional. Real: the status history and the comments. Faked for now: the reason behind each return ... If it turns out review time dominates after all, I’d tear this plan up and look at review, and the AI tool might be the right answer.”

The move: commit under ten minutes, say what is real and what is faked, and name the result that would prove you wrong.

10:40 Deputy mayor: “The mayor can’t stand up in April and announce a report.”

11:30 Candidate: “Agreed, the report isn’t the announcement. It’s how we choose one that will still be true in the summer.”

The move: the sponsor wants a headline. The candidate agrees with the pressure, keeps the scope, and turns the report into the route to an announcement that will hold. No refusal and no lecture.

The over-scoping run

This run asks good questions too, and finds most of what the case hides. Then it keeps going. Told about the three clocks, it asks “Which one would you say is the right one?”, and when the sponsor points to the mayor’s, it defers the choice. Told again later, it proposes a new combined measure to “workshop” with stakeholders. It lists six areas of work with no order, and asked which comes first, says “probably the metric.” The sponsor’s last line: “I was hoping for more than a recommendation by now.”

What separated them was not knowledge. Both runs learned much the same facts. The strong run committed once the remaining unknowns were cheap to check; the stalled run treated every unknown as a reason to wait.

The first version, in code

The strong run’s first version is a weekly report of how long applications wait in each stage, split by homeowner and professional, built from the status history the city already has. An empty contractor_license means a homeowner; the query treats null and blank the same. Building, zoning, fire and structural reviews can run at once, and each review status carries its discipline. The core is one (SQLite syntax, tested). In words: for each application, how long each status lasted before the next change, where a review status ends at the next change in its own discipline; then each file’s time is summed and averaged over the applications that passed through that stage.

WITH stays AS (
  SELECT
    h.application_id,
    h.status,
    COALESCE(h.discipline, '-') AS lane,
    CASE WHEN NULLIF(a.contractor_license, '') IS NULL
         THEN 'homeowner' ELSE 'professional' END AS applicant,
    julianday(CASE WHEN h.discipline IS NULL
      THEN LEAD(h.changed_at) OVER (
        PARTITION BY h.application_id
        ORDER BY h.changed_at)
      ELSE LEAD(h.changed_at) OVER (
        PARTITION BY h.application_id, h.discipline
        ORDER BY h.changed_at)
    END) - julianday(h.changed_at) AS days
  FROM permit_status_history AS h
  JOIN applications AS a USING (application_id)
)
SELECT
  applicant,
  status,
  lane,
  COUNT(DISTINCT application_id) AS applications,
  ROUND(SUM(days) / COUNT(DISTINCT application_id), 1)
    AS days_per_application
FROM stays
WHERE days IS NOT NULL
GROUP BY applicant, status, lane
ORDER BY applicant, days_per_application DESC;

Say the caveats before the interviewer does:

  • Stays that have not ended. A status with no next change has no end, so it drops out, and the files stuck longest vanish from the queue’s numbers. Report the age of open files beside it, and switch to medians and the slowest tenth once it runs.
  • Files that come back. A file returned to the applicant passes through intake twice. Averaging per stay would count it twice and make intake look quick; the query sums each file’s time first and averages per application.
  • Reviews that overlap. The building review and the structural queue can run side by side, so the rows don’t add up to the mayor’s clock. Say so before anyone sums them.
  • Ties. Two status changes with the same timestamp need a tiebreaker, or the order between them is arbitrary. Don’t fall back on row order, which need not match event order: break ties by the status sequence, checked with the intake supervisor.

The Pro lesson Worked case: a city’s building permits follows the strong run to the end, with the board, the stakeholders’ numbers and the moment each step earned its score.

More worked cases

These two questions are free, with full model answers. Here is the move that makes each one work. The third case, shared interests, is a reported prompt that ends in code.

City bus reliability

A city transit agency says its buses are unreliable and riders are leaving. “Unreliable” is the whole question: it can mean long waits on frequent routes, buses arriving together, trips that never run or buses leaving early. Each needs different data.

The move: on frequent routes, riders don’t read a timetable, so on-time performance is the wrong measure. The model answer uses excess wait, the wait riders experience minus the wait the schedule promises, which shows bunching even when the average gap looks fine. The first version is a page beside one dispatcher’s console for one corridor, flagging buses too close together. The guardrail is end-to-end run time, because holding a bus adds minutes for the riders already on it.

The line that earns trust: if the routes that lost riders are not the ones with the worst excess wait, reliability is not the main cause, and you say so on Friday instead of demoing a tool.

Hospital readmissions

A hospital group wants fewer patients readmitted soon after discharge. The tempting answer is a risk model. The model answer starts somewhere else: how many follow-up calls the care team can make each day, because that capacity sizes every list you produce.

The moves, in order: write down the definition of a readmission before anything else; name the guardrails, because readmissions also fall for bad reasons such as longer stays or returns billed as observation; then give the nurses a morning work list for one condition at one hospital, ranked by a rule anyone can read. A risk score replaces the rule only when it beats the rule in a fair comparison.

The two are different problem shapes. The bus case is about time lost in waits, the same shape as the permits case; the hospital case is about ranking work for a team with limited capacity. Learn to name the shape, and a case you have never seen starts to look familiar.

Shared interests: when the round ends in code

Two candidates reported, in March and August 2025, Palantir FDSE prompts about an app or system that connects users by shared interests. Source 22Palantir FDSE Interview (rejected but idk why) (post by u/Master_el)PublisherReddit r/csMajorsSource typecandidate report on RedditSource 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on Reddit One candidate, the one who reported in March 2025, was then asked to implement search(user_id, users), which returns users who share interests with user_id and have never met them. Source 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on Reddit Here is the breakdown in four lines, and the function it leads to.

  • Entities: a user, with a set of interests.
  • The relation that matters: who has already met whom. It is what makes this discovery, not a friends list.
  • The P0 feature: show me people I haven’t met who share what I care about, best matches first.
  • One metric: suggestions that lead to a first message, with blocks and reports as the guardrail.

Before the code, ask the question that changes it: “Does share mean one interest in common, or all of them? I’ll include anyone with one, and rank by how many.” Then say the shape of the data: “Users is a dict keyed by id; each user has a set of interests and a set of ids they’ve met.” Tested in Python:

from collections import Counter

def search(user_id, users):
    """Users who share an interest with user_id and have
    never met them, most shared interests first."""
    me = users[user_id]
    shared = Counter()
    for other_id, other in users.items():
        if other_id == user_id or other_id in me["met"]:
            continue
        overlap = len(me["interests"] & other["interests"])
        if overlap:
            shared[other_id] = overlap
    return sorted(shared, key=lambda uid: (-shared[uid], uid))

Then say the scaling line aloud, before you are asked: “This is linear in users. At scale I’d invert it, interest to user ids, so I only touch people who share at least one interest.” The entities you named in the breakdown are the arguments your function takes. Say that link out loud: it shows the breakdown was real. The Pro lesson Product-sense prompts works product prompts like this one end to end, from the user and the flow to the entities your code stands on.

How it differs from system design and client simulation

Reports describe the round differently. On Blind, one commenter called decomp “Basically system design,” another “a low level version of the normal system design interview,” and a third, before their interview, had read it is “High level and less technical than traditional system design.” Source 18Palantir FDSE Interview (Blind)PublisherBlind (Teamblind)Source typecandidate report on BlindSource 31Update: interview experience - Palantir new grad FDSE interview (Blind)PublisherBlindSource typecandidate report on BlindSource 36Palantir Decomposition Question (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind A Blind commenter in April 2022 called Palantir’s Deployment Strategist decomp “very similar to consulting case interview.” Source 7Palantir Deployment Strategist Interview (Blind)PublisherBlindSource typecandidate report on BlindSource 8Palantir Deployment Strategist (Blind)PublisherBlindSource typecandidate report on Blind Yet one candidate’s report on Aced, for a Palantir Deployment Strategist role interviewed for in September 2025 that ended in an offer, says that going in expecting a consulting case was the wrong mindset. Source 37Palantir Deployment Strategist Interview ExperiencePublisherAced (formerly Exponent)Source typecandidate’s personal write-up

Our reading: open like a case, finish like a design.

RoundYou start withYou end with
DecompositionA vague problemA first version and a plan
System designA stated system to buildAn architecture and its limits
Client simulationA customer in a situationTrust, a decision, next steps

Practice prompts

Practice on prompts other people report, then on ours. Say each answer out loud against a clock, and write the board as you go.

Prompts people report

  • London taxis. One candidate on Blind, in an undated update to an October 2022 post about a Palantir new-grad interview, wrote that they were given 8,000 records of London taxi data with 8 columns and asked for a first-cut solution to improve drivers’ lives, deployable in a week. Source 30Palantir Learning & Decomposition Interview (Blind)PublisherBlindSource typecandidate report on Blind
  • Insider trading. First Round Review reported, in February 2026, that Palantir’s former FDE recruiting lead gave this example: explain insider trading to the candidate, then ask what data they would need, what they would ask the customer and what they would look for. Source 16So You Want to Hire a Forward Deployed EngineerPublisherFirst Round ReviewSource typenews report
  • An unsolved customer problem. First Round Review also reported her saying hiring managers would present a problem a customer was working on that no one had solved, and ask how the candidate would solve it. Source 16So You Want to Hire a Forward Deployed EngineerPublisherFirst Round ReviewSource typenews report
  • Class scheduling. One poster wrote in r/InterviewCoderHQ, a forum that may be tied to an interview-assistance product, in March 2026, that they had been a Palantir interviewer for a few years and that a retired new-grad decomp question was “design a class scheduling app for your university, assume you’d have two weeks to build a fully functioning prototype.” Source 38Palantir SWE Interview breakdown (comment by u/Top_Substance9093)PublisherReddit r/InterviewCoderHQSource typecandidate report on Reddit
  • Shared interests. Two candidates reported, in March and August 2025, Palantir FDSE prompts about an app or system that connects users by shared interests; it is worked above. Source 22Palantir FDSE Interview (rejected but idk why) (post by u/Master_el)PublisherReddit r/csMajorsSource typecandidate report on RedditSource 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on Reddit
  • A delivery courier, and a planet. On Blind in January and February 2025, one commenter described a hypothetical question similar to the one they got: helping a cousin who delivers for Uber Eats choose which orders to take, and another wrote they got an application to log species on a different planet. Source 25Palantir FDSE InterviewPublisherBlind (teamblind.com)Source typecandidate report on BlindSource 26Palantir FDSE Decomp/System Design InterviewPublisherBlind (teamblind.com)Source typecandidate report on Blind
  • A retailer’s data. A Reddit commenter wrote, in December 2024, that decomp is closer to a business case study than system design, and that their interviewer gave the example of data available to a major food and beverage retailer and asked how to use it to raise revenue or enter a new market. Source 39Comment on Palantir FDSE 2024 threadPublisherReddit r/csMajorsSource typecandidate report on Reddit The commenter posted in a thread about Palantir FDSE interviews but did not name the company or role.
  • Pacman. One candidate’s Glassdoor review from March 2015, for a Palantir Forward Deployed Engineer role, gives the decomposition question “How would you implement Pacman?” Source 40Palantir Technologies Forward Deployed Engineer Interview Questions (archived)PublisherGlassdoor (archived by the Wayback Machine)Source typecandidate’s personal write-up

Prompts from our bank

Each of these is free, with a framework and a model answer.

How to practice one

Set a timer. Say the step names as you enter them. Commit to a first version before the halfway mark. Close in four parts. Then have someone push back with one of the four pushes above, and answer it. Read the model answer and find the one step where yours was thinnest, and do that step again tomorrow on a different prompt.

Go deeper, by how long you have

Pick the line that matches your calendar.

The pass rate no one can source

Search for this round and you will soon meet a number presented as its success rate, and another presented as its share of the hiring decision. Here they are, and where they start.

Posts on Perspective AI, dev.to and a Substack repeated the pair in June and July 2026, and the Aced guide that the dev.to post credits contains neither number; what no one publishes traces the whole chain. Source 42Forward Deployed Engineer Interview Questions: A 2026 Prep GuidePublisherPerspective AISource typeinterview prep siteSource 43Forward Deployed Engineer interview questions (2026): every round, with real examplesPublisherDEV CommunitySource typeinterview prep siteSource 44Cracking the Forward Deployed AI Engineer InterviewPublisherAI Engineering Insider (Substack)Source typeinterview prep siteSource 45Forward Deployed Engineer Interview: The Definitive 2026 Guide (FDE)PublisherAced (formerly Exponent)Source typeinterview prep site

What to do with that: nothing. Prepare for this round the way you prepare for coding, because the round exists and reports describe it, not because of a number someone made up.

Your next step

Reading a method is not the same as running one against a customer who answers only what you ask. Sign in free and you get scored 10-minute runs of the building permits case every day, plus one scored run at full length, with a scorecard that quotes what you said. Run it, then reread the strong and stalled runs above and see which one you sounded like.

Then read your scorecard’s lowest line. If it is Walking skeleton, read The walking skeleton. If it is Stakeholders and success metrics, read Stakeholders and success metrics. If it is Clarify before solving, read Clarify before you solve.

Pro has the rest of what this page shows a slice of: the full strong run in Worked case: a city’s building permits, with the moment each step earned its score; product prompts like shared interests worked from the user to the code in Product-sense prompts; and 3 cases whose customer answers only what you ask. See what Pro includes.

GlossaryForward deployed engineerA software engineer who builds and ships production systems inside a customer’s problem and environment, accountable to that customer’s outcome.More on Forward deployed engineerGlossaryAgentA system in which a model chooses steps and tool calls to complete a task, within limits the design sets.More on AgentGlossaryWalking skeletonThe thinnest end-to-end version of a system that performs one small real function across its main components, built first and then extended.More on Walking skeletonGlossaryDecomposition roundAn open-ended interview in which you work out loud from a vague problem with several possible solutions to a concrete approach and a first working version.More on Decomposition roundGlossaryDeployment strategistA customer-facing role that works out the customer’s questions and scope beside FDEs; at some employers the title means a product-manager or quota-carrying role instead.More on Deployment strategistGlossaryForward deployed software engineerPalantir’s title for its FDE role, called Delta internally; OpenAI and EY also post FDSE titles, each with its own duties.More on Forward deployed software engineerGlossaryRe-engineering roundAn interview in which you learn, debug or extend code or a library you have never seen, against the clock and out loud.More on Re-engineering roundGlossaryLaunch criteriaThresholds agreed with a customer before building that decide whether a system goes live.More on Launch criteriaGlossaryWindow functionA SQL function computed over rows related to the current row, such as a running total, without collapsing them.More on Window function

More posts on this topic

Each takes one part of this guide further.

Questions people ask

What is a decomposition interview?

An open-ended interview in which you get a vague problem with more than one reasonable solution and work out loud to a concrete approach and a first version that works. Palantir calls the skill navigating open-ended questions, and its careers site says open-ended technical questions are a key part of its interview process.Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

Which companies use a decomposition interview, going by what they publish and what candidates report?

Palantir is the one employer we found that names it in its own material. Its early-talent application timeline lists a decomposition interview in the virtual onsite, beside a learning interview. We found no other employer that publishes a decomposition round. Candidate reports place it elsewhere too. One candidate’s report on Aced lists a decomposition round in their February 2026 loop for an entry-level Databricks FDE role.Source 2Students | Palantir Careers (timeline image: RecruitingTimeline_V3.jpg)PublisherPalantirSource typecompany hiring pageSource 27Databricks Forward Deployed Engineer Interview ExperiencePublisherAced (formerly Exponent)Source typecandidate’s personal write-up

How long is the decomposition interview?

Palantir’s early-talent timeline describes its virtual onsite as two one-hour interviews, learning and decomposition. That is the only length we found an employer publish, so practice both a short version of your answer and one that fills a full hour.Source 2Students | Palantir Careers (timeline image: RecruitingTimeline_V3.jpg)PublisherPalantirSource typecompany hiring page

Is a decomposition interview a case interview or system design?

Some of each. Palantir’s advice for open-ended questions is to set out the alternatives and trade-offs, then arrive at a concrete approach and deliver a functioning idea first. So open like a case, with the user, the goal and the options, and finish like a design, with data, an interface and a first version you could build.Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

Do candidates report writing code in a decomposition interview?

At least one has. One candidate reported, in March 2025, a Palantir FDSE decomposition interview that moved from designing a system where users share interests to implementing a search function. Before their interview, in January 2023, another wrote on Blind that it “involves no coding and decomposition questions,” and a Blind commenter in July 2022 wrote that “you might need to write some pseudocode to explain your thoughts better.” Be ready to write a schema, a query or a short function when asked.Source 23Palantir FDSE Interview Experience (REJECTION~) (post by u/bosslee21)PublisherReddit r/csMajorsSource typecandidate report on RedditSource 31Update: interview experience - Palantir new grad FDSE interview (Blind)PublisherBlindSource typecandidate report on BlindSource 36Palantir Decomposition Question (Blind)PublisherBlind (Teamblind)Source typecandidate report on Blind

What is the decomposition interview pass rate, and why do prep sites quote one no one can source?

No employer publishes one, and none of the candidate reports or hiring-leader statements in our research gives one. The earliest appearance of the figure prep sites repeat that we found is an explainx.ai table dated May 2026 that cites no underlying data.Source 41Forward Deployed Engineer Preparation Guide: Complete Interview & Career Path Roadmap 2026Publisherexplainx.aiSource typeinterview prep siteSource 45Forward Deployed Engineer Interview: The Definitive 2026 Guide (FDE)PublisherAced (formerly Exponent)Source typeinterview prep site

How do I practice for a decomposition interview?

Practice out loud, against a clock, on prompts with a vague customer and sometimes a dataset. Palantir’s own preparation advice includes finding a public dataset and thinking of something interesting to do with it. Then run a case against a customer who answers only what you ask, and compare what you said with a model answer.Source 1Palantir Careers | Navigating Open-Ended QuestionsPublisherPalantir TechnologiesSource typecompany hiring page

Keep reading

Guides

Lessons

Questions