Latest / The Tech Career Podcast with Fexingo: Engineering Jobs, Interviews, and FAANG Career Strategy / How to Ace a FAANG Engineering Take-Home Assignment
Transcript
- Lucas: So you've prepped your coding questions, you've studied system design, and maybe you've even done a few behavioral rounds. But there's one FAANG interview stage that a lot of engineers underestimate: the take-home assignment. Luna: Yeah, it's that project they send you after the phone screen — sometimes before the on-site. And it's not just a coding test; it's a full mini-project. Lucas: Exactly. And I've seen really strong coders bomb this part — not because they couldn't write good code, but because they treated it like a LeetCode problem. So today I want to walk through a real example from a candidate I coached recently. Luna: Let's hear it. What was the assignment? Lucas: This was for a senior backend role at Meta. The assignment: build a simple url shortening service with an API. They gave a spec — about three pages. The candidate, let's call him Dan, spent about thirty hours on it. He built a full microservice with Redis caching, a custom load balancer, the works. Luna: Wait — that sounds impressive. What went wrong? Lucas: He didn't read the spec carefully enough. The assignment said: 'Use in-memory storage only — no external dependencies.' Dan used Redis. That's an external dependency. The reviewer saw that and flagged it as a failure to follow instructions. Luna: Ouch. So it wasn't about technical skill — it was about reading comprehension. Lucas: Exactly. And that's the first lesson: the spec is not a suggestion. It's a contract. If they say no frameworks, use pure Python. If they say no external databases, use a dictionary. Follow it to the letter. Luna: But why would they limit you like that? Isn't using Redis a sign of good engineering? Lucas: Sure, in production. But the take-home is testing whether you can work within constraints and deliver a clean, working solution that matches the spec. They want to see your process, not your perfect system. Dan's solution was over-engineered for the ask. Luna: So what's the right approach then? How should you structure your time? Lucas: I recommend a three-phase framework. Phase one — requirements. Spend the first hour re-reading the spec, writing down every explicit requirement and every implicit one. Then list your assumptions. Send a brief email to the recruiter to confirm any ambiguities. Luna: I like that — shows you're thorough and communicative. What's phase two? Lucas: Architecture. Spend about two hours on a design doc. Not a formal Google Doc — just a markdown file that explains your high-level design: components, data flow, API endpoints, trade-offs. Write it as if you're presenting to a senior engineer. This is where you show your thinking. Luna: And phase three is implementation, right? Lucas: Yes, but with a strict time box. I tell candidates to budget no more than eight hours for coding. That forces you to make pragmatic decisions — not build the perfect system. If you're spending thirty hours, you're over-investing. Luna: And I'd add: don't forget the README. That's where you explain how to run the code, any assumptions, and what you'd improve with more time. Lucas: Absolutely. The README is your cover letter. Dan actually did a pretty good README — he listed what he'd add next, like persistent storage and rate limiting. But he still got dinged on the Redis issue. So the lesson is: spec first, everything else second. Luna: Okay, so we've covered Meta. What about Apple? I've heard their take-home assignments are quite different. Lucas: Yeah, Apple tends to give more open-ended assignments. Instead of 'build a URL shortener,' they might say 'build a simple iOS app that displays a list of items from an API, with pull to refresh and caching.' They leave the design decisions up to you. So you have to make deliberate choices and justify them in the README. Luna: Right, and they're looking at your judgment — whether you choose the right architecture for the problem size, not just the most complex one. Lucas: Exactly. And another thing — both Meta and Apple expect you to handle errors gracefully. Don't just assume the API returns perfect data. Show that you've thought about timeouts, network failures, malformed responses. Luna: That's something a lot of candidates miss. They're so focused on the happy path that they forget the edge cases. I've seen take-homes that crash on a simple empty response. Lucas: Yeah, and that's an instant red flag. So here's a practical checklist before you submit: one — does the code compile and run with a single command? Two — have you included a sample input and output? Three — does your README explain trade-offs? Four — did you explicitly list all assumptions? And five — have you tested the failure cases? Luna: That's a solid list. And I'd add: get a second pair of eyes if you can. Even a non-technical friend can spot typos in the README that make you look sloppy. Lucas: Good point. Look, the take-home is your chance to show how you work on a real project — not just solve an algorithm puzzle. It's the closest thing to a real day on the job. If you treat it with the same care you'd give a production PR, you'll stand out. Luna: And if today's tech conversation gave you something usable, here's a thought — listener support is what keeps this show ad-free and focused on real career strategies. If you find value in episodes like this, you can support us at buy me a coffee dot com slash fexingo. It's a simple way to say the show matters. Lucas: Yeah, we really appreciate that. It helps us keep doing deep dives like this without any sponsors. So now, back to the assignment — one thing I want to emphasize about the README: include a section on what you'd do differently with more time. That shows you're thinking like an engineer, not just a coder. Luna: That's a great tip. It signals that you're aware of real-world constraints and you prioritize. So, to wrap up: what's the single biggest mistake you see? Lucas: Over-engineering. Candidates try to impress with fancy tech stacks and over-optimized solutions. But the reviewers want to see that you can deliver a clean, correct, maintainable solution that exactly meets the spec. Nothing more, nothing less. Luna: And don't forget to check the deadline — I've heard of people missing the submission window because they were too busy perfecting the code. Lucas: Right. Submit early if you have to. A working solution on day six is better than a perfect one on day seven that never gets sent. So, final takeaway: treat the spec like a legal document, time-box your work, and write a README that tells a story. Do that, and your take-home will open doors. Luna: Well said. And for anyone prepping right now, good luck — and read the spec twice.