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Dynamic programming questions test whether you can find the recurrence and overlapping subproblems — the hardest pattern to fake under interview pressure.
Dynamic programming is the technique of solving a problem by combining answers to overlapping subproblems, storing each answer so it is computed once. In an interview the difficulty is almost never the code, which is usually short — it is finding the state definition and the recurrence that relates one state to its predecessors. Once those two are stated correctly, the implementation tends to follow in a few lines.
The strongest signal you can send is to define the state in words before writing anything: "dp[i] is the best answer considering the first i items". Interviewers are explicitly checking whether you can go from a recursive brute force, to memoisation, to a bottom-up table, because that progression demonstrates understanding rather than a memorised template. Being able to reduce a two-dimensional table to a single row when only the previous row is needed is a common and well-received optimisation.
14 coding · 3/6/5 easy/medium/hard
Look for a question asking for a maximum, minimum, or count of ways, where a greedy choice can be shown to fail and the same subproblem is reachable by multiple paths. That combination is the signature of overlapping subproblems.
Top-down memoisation is usually faster to reach correctly under time pressure because it follows directly from the recursive definition. Mention that a bottom-up version exists and what it would save, and convert only if asked.