Full-Stack Interview Prep
An interview prep path for full-stack loops. Full-stack interviews test breadth on both sides of the API plus the same coding bar as everyone else. This path balances the legs: TypeScript and framework fundamentals, database and distributed-systems vocabulary, a coding ramp from easy through a couple of hards, the four system designs full-stack loops reach for, and the behavioral themes that prove end-to-end ownership.
Frontend fundamentals
The client half of the breadth check. Interviewers want the language and the rendering model, not framework trivia - know what TypeScript buys you and what your framework costs you.
Backend fundamentals
The server half: indexing, transactions, SQL vs NoSQL trade-offs, and the distributed-systems vocabulary that system design rounds assume. Full-stack candidates most often get dinged here - do not skim this section.
Coding: Easy patterns
Warm-ups that lock in hash maps, two pointers, and linked-list handling. Full-stack loops hold you to the same coding bar as specialist roles - make these reflexive before climbing.
Coding: Medium patterns
Where most full-stack loops get decided. Aim for ~25 minutes per problem with a clean solution and a concrete time/space analysis - then say it out loud, because the narration is graded too.
Coding: Hard patterns
A short hard ramp - enough to handle the one stretch problem some loops include. LRU cache in particular doubles as a systems conversation: eviction, capacity, and what you would change for a distributed version.
System design: the classics
The four bounded designs that dominate mid-level loops. As a full-stack candidate, your edge is covering both ends - talk about the client experience and the storage layer in the same answer.
Behavioral: end-to-end ownership
Full-stack behavioral rounds screen for whether you actually own features front to back or just touch both codebases. Build STAR answers that follow one feature from design through deploy and incident.
- 01BehavioralOwnership (Amazon Leadership Principle)Behavioral · Amazon LP
- 02BehavioralDive Deep (Amazon Leadership Principle)Behavioral · Amazon LP
- 03BehavioralDealing with AmbiguityBehavioral · General
- 04BehavioralLeadership Without AuthorityBehavioral · General
- 05BehavioralLearning from FailureBehavioral · Microsoft
Browse other learning paths
Three role-targeted paths are live: Backend, SRE / DevOps, and ML Engineer. More are on the way - if you have a role you want covered, let us know.
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