Meta

Meta was among the first major companies to standardize the AI-enabled coding round, and their CoderPad setup has become the reference point candidates compare everything else to.

The platform

The interview runs in CoderPad with a selection of AI models — candidates have reported GPT-4o, GPT-5, Claude Sonnet/Haiku, Gemini, and Llama. The environment gives you a codebase, an AI chat panel, and the problem statement, all loaded before you start. One consistent report: the built-in AI feels noticeably worse than tools like Claude Code or Cursor, so set expectations accordingly and lean on your own verification.

The format

The typical interview follows a defined problem arc:

A useful pacing strategy: the bug-fix phase is simple and fast, so don't spend your whole budget there. Keep the AI for volume; keep the approach decisions yourself.

How the hour is typically spent

The round is 60 minutes and replaced one of the two traditional coding interviews when it rolled out in late 2025. Reported pacing:

Minutes	Phase	Notes
0–6	Orientation	Get around the three panels — file explorer, editor, AI chat — and find how to run the tests
6–25	Fix the bug	Existing code, small fix. Often faster by hand than by prompt
25–55	Implement the feature	The bulk of the work, frequently 120+ lines. AI use explicitly encouraged here
55–60	Optimize	Harder inputs. Reportedly not disqualifying if you don't finish

Two things follow from that table. Finding how to run the tests is a first-six-minutes task, not something to discover at minute 40 — it's what makes every later phase verifiable. And since the last phase is partially discounted, protect the middle: a working feature with a stated optimization plan beats a half-refactored one.

Meta evaluates on four axes: problem solving, code quality, verification, and communication. Only the first is about getting an answer.

What interviewers watch

Meta candidates report interviewers encouraging you to:

• Explain what changes you want to make before you make them.
• State the time/space complexity of your intended solution.
• Check that the AI's solution/implementation edits are correct, and say what you're planning next.

In practice this means: form a plan, say it, prompt with codebase-specific vocabulary, and read every AI diff out loud as it lands. The interviewer is evaluating control and verification, not prompt cleverness.

One candidate's report of the actual experience: a simple bug fix at the start (no AI), then an AI-enabled puzzle-solver type question. They attributed their success to having practiced on Meta's own platform — which is exactly why the next section matters.

Practice environment

Meta offers a practice session on their platform before the real interview. Always take it. Thirty minutes of getting comfortable with the CoderPad AI interface — its quirks, its latency, its refusal patterns — is worth more than another hour of reading.

Tactical checklist

1. Orient: find the entry point and the data model in the first five minutes.
2. Plan all three phases before touching the AI.
3. Fix the phase-one bug by hand — it's usually a 30-second change and earns credibility.
4. For each feature prompt: name the class, the method, the approach, and the data structures.
5. Run the tests after every generation. Never layer on broken code.
6. Before optimizing, run the full suite; after, run it again.