What LinkedIn Tests

LinkedIn pulls its coding problems from a small, stable pool that barely moves year to year, and that one fact should reshape how you prep. Number of Islands, a Premium question, Word Ladder, a Premium question, Find Leaves of a Binary Tree, a Premium question, Nested List Weight Sum: these come back loop after loop. The high-frequency list does most of the work for you. Drill the recurring set and you walk in already recognizing the prompt, which is about the rarest edge there is in a coding loop.

The phone screen has a quirk worth rehearsing before you schedule it. You code in CoderPad, but candidates report nobody runs it. You write a complete, syntactically clean program, then walk your own test cases through it by hand. That flips the run-it-live screen other companies rely on, and it rewards visible reasoning over a green checkmark. The signal is consistent: LinkedIn weighs how clearly you think and narrate at least as much as code that happens to compile.

The LinkedIn angle

On the phone screen, the dry-run carries as much weight as the code itself. Nobody executes what you write. So the interviewer watches you trace inputs through it line by line, catching your own bugs in your head. Write the full solution, then narrate two or three test cases through it the way the round actually runs. Two interviewers is common here, one leading and one calibrating quietly, so a near-silent second person is normal, not a bad sign. A sloppy trace reads worse than a missing optimization. Get fluent at finding your own off-by-one before anyone has to point at it.

The AI-enabled coding round

Over 2025, one onsite coding seat reportedly turned into an AI-enabled round. It is the newest and least-settled part of the loop, so weigh it accordingly. Picture CoderPad with an AI assistant panel switched on: you pick the model, it cannot edit your code for you, and you copy its output in by hand. The grade is about judgment, not recall. How sharply you prompt the assistant, and whether you verify what it returns instead of pasting the first answer. Production concerns like concurrency count too, and this round usually lets you run code, unlike the phone screen. Older guides flatly banned AI, so the stance has moved fast over the last year, and it may still vary by team. The dedicated lesson works the confirmed problems end to end.

The LinkedIn angle

The assistant is a tool, and the round grades how well you wield it. Lean on it, then own every line it hands you. Pick the most capable model offered and prompt it specifically. Then check its output the way you would a teammate's pull request: run it against edge cases and say why you trust or distrust each part. Paste a confident wrong answer unchecked and you have walked straight into the trap the round sets. The follow-ups weigh more than the first working version. They pull toward real-system thinking, race conditions, malformed input. Since the format is new and still settling, rehearse working a problem with an assistant in the room, then route the deep prep to the AI coding round lesson.

What the coding rounds favor

LinkedIn keeps the components of a normal loop but tilts them toward design and data-structure craft. Graph traversal is the single largest family, fed by Number of Islands and Word Ladder. Almost level with it sits a heavy design and OOD band, the part that most marks a loop as LinkedIn's, with two Premium questions as the recurring faces. Arrays and strings carry the phone screen. Trees and BST surface through the signature problems, and heaps show up as Kth Largest and merge-k work. Dynamic programming and intervals round out the tail. LinkedIn doesn't publish these numbers; the split below is how often each family comes up, so read the shares as relative weight.

Read the chart as a map of where your first hours go. Graphs lead, design runs a close second and is the family a generic LeetCode grind underweights, and the array-and-string fundamentals back the screen. The six lessons in this section follow roughly that shape. Each opens with how LinkedIn frames the family and the variants it favors, then works the most recurring problems end to end with the follow-up the interviewer layers on. Where a lesson leans on a base data structure, the full walkthrough lives in the free Foundations course so these pages can stay on what is specifically LinkedIn.

The LinkedIn angle

Put your prep hours into the design and OOD band. That is where strong algorithm coders get blindsided. Plenty of candidates clear Number of Islands and then freeze on a Premium question, or on a from-scratch [a Premium question](/guides/companies/linkedin/coding/design-and-ood) that has to stay fast on every operation. LinkedIn hands you the data structure to build from nothing, then defends it under follow-ups about thread-safety and scale. The signature problems hide here too. Shortest Word Distance gets pushed straight to its preprocess-once design version, and LRU gets extended to LFU with a ranking call. Spend real hours building these by hand. The rest of the surface is standard patterns illustrated with LinkedIn's favorite examples.

How these lessons are organized

The six lessons run from the largest family down to the round that is LinkedIn's own. Start with graphs and trees, the biggest cluster and the one the phone screen draws from most. Then work through the patterns toward the design craft and the AI round, which no pure-pattern list captures.