Are You Ready for a Forward Deployed Engineer Interview?

You're ready for a Forward Deployed loop when you can do the seven things below cold: out loud, on a clock, without notes. This is not a reading check; it's a performance check. Read the test for each, try it honestly, and if you stall, the link tells you where to go back.

The rule for grading yourself: if you can only do it while reading the page, you can't do it. Close the tab and try again in a week.

1. Decompose an ambiguous problem, out loud

The test: have someone hand you a vague, non-software prompt like "design something to help X do Y", and give you five minutes. Can you name the user and the outcome, break the problem into 3–5 parts, find and defend the hard one, and keep talking the whole time?

You've got it when you spend your first two minutes not proposing a product, and an interviewer's "just give me something concrete" doesn't rattle you. If you jump straight to a solution or go silent to think, drill it. → Decomposition Drills

2. Run the customer conversation

The test: role-play three lines: a customer asking for the wrong thing, an exec asking why it costs so much, and a skeptical engineer asking why you're there. Can you anchor on their outcome, say no with a because, and translate the tech into their units of money and risk?

You've got it when you can push back on a bad ask without becoming the obstacle, and explain cost in dollars-of-risk a non-engineer nods at. → Client-Simulation Drills · the craft behind it: Customer Outcomes

3. Design and defend a production AI system

The test: "design an AI system for customer X." Can you sketch the obvious architecture in one sentence and then spend your time on evaluation, failure-bounding, and cost/latency, leading with how you'd know it's right before the model?

You've got it when your instinct on a compliance or safety prompt is to talk about how you'd measure correctness continuously and keep a human in the loop before you talk about the retriever. → AI System Design Cases · the concepts: Production

4. Get useful fast in unfamiliar code

The test: open a small repo you've never seen with a seeded bug, and fix it in twenty-five minutes, narrating. Then read the docs of a library you don't know and make one working call in twenty.

You've got it when you trace one path instead of reading everything, form a hypothesis before editing, reproduce before fixing, and use your tools, including an AI assistant, while staying the one who can defend every line. → Codebase / Learning Drills

5. Recognize and target production-grade evidence

The test: take the most impressive AI thing you've built and score it against the production-vs-hobby rubric. Can you say which rows it clears, which it doesn't, and exactly how you'd reshape real work to move it into the left column?

You've got it when you know the difference between "I built a chatbot" and "people depended on this under a real constraint and here's how I knew it worked", and you have a concrete plan to have the second kind of story. → Build the Evidence

6. Clear the coding screen's floor

The test: from an empty file, build a small working program against a plain-language user scenario, in your strongest language, on a timer, narrating. Then extend it once when the requirements change. Can you ship both versions without a rewrite?

You've got it when the first version is simple enough to survive the second ask, and you keep talking while you type. This is the gate that opens before any other signal gets graded; the floor and its sources are on the Interview Method. → The Coding Screen

7. Answer "why here" with a priced tradeoff

The test: deliver your "why do you want to work here?" answer for the specific company you're targeting: its actual products and customers, a thesis about where you create value that an interviewer can push on, and one cost of the role you're accepting knowingly. Then tell a real failure story and take two follow-up questions without repositioning it as a success.

You've got it when the answer could only be about that one company, and the failure story is an actual failure. The question shapes and their sources are on the Interview Method. → Values & Hiring-Manager Drills

The bar the self-check can't measure

Items 1–4 and 6–7 are interview skills, and a few focused weekends of drilling move them. Item 5 is different, and it's the one the offer actually turns on: the evidence itself. No self-check and no website can grade whether you've shipped production AI that real users relied on. You either have that story or you're building toward it.

So read this self-check honestly on two axes:

• Am I interview-ready? If you can do 1–4 and 6–7 cold, yes. Start applying and drilling in parallel.
• Do I have the evidence? If your best project sits in the hobby column, that's the work to start now, in parallel with everything else, because it takes real calendar time to accumulate, and it's what separates a strong interview from an offer. → Build the Evidence

A four-week shape, if you have a job

The self-check tells you whether you're ready; this sizes the path for someone with a day job. Reading is the short part. The drills and evidence take longer, so front-load the reading, drill daily, and start evidence work on day one. The shape below assumes roughly eight to ten hours a week; at four hours, read it as an eight-week plan.

• Week one: read, and start the long pole. Read Foundations and Production in order (skim what you already know). Pick your target door early. Company Differences shows how Palantir, the labs, and Google diverge, so your prep aims at one loop. The same week, open Build the Evidence and act on it: draft the pilot pitch, or pick the real work you'll reshape, and start the decision log.
• Week two: read the craft, start the reps. Read Customer Outcomes, the Interview Method, and Interview Practice, and read one engagement to see the cycle run in a real company. Begin decomposition drills: five minutes, out loud, recorded, graded against the frame, every other day.
• Week three: drill all four rounds. Keep the decomposition reps. Add a codebase drill (a seeded bug in an unfamiliar repo, narrated, on the clock) and one system-design case out loud. Recruit your difficult-customer partner and run the client-simulation drills live. That's the round solo practice can't finish. Add two timed coding-screen reps against the floor (item 6).
• Week four: close the loop. Run the seven tests on this page cold. Draft your "why here" answer and your failure story, and say them out loud (item 7). Re-run the "why here" rep for the specific company the week before its loop, since that answer goes stale by design. Wherever you stall, go back to that page's drills rather than re-reading. If items 1, 3, 4, and 6 are cold and you have one evidence story, start applying.

When to start applying

Don't wait for a perfect score. If you can do 1, 3, 4, and 6 cold and you have one piece of real evidence you can talk about, you're ready to be in loops. The interview itself is the best remaining drill. Keep sharpening 2 and 5 while you interview; they compound. The path is short by design; the evidence is the long pole, so start it first and let the readiness catch up.

Next: AI Systems — Overview. The learning path begins with the system itself.