Technical interviews can feel less like problem-solving and more like performance under pressure. The good news: “going blank” is usually a process problem, not a talent problem. Here’s a repeatable game plan you can practice to stay structured and calm in live coding and technical assessments.

1) Use a 5-Step Script (Say it out loud)

Interviewers aren’t just grading correctness—they’re evaluating how you think. Try this script for every problem:

1. Restate the problem in your own words (confirm inputs/outputs).
2. Ask clarifying questions (constraints, edge cases, allowed tools).
3. Propose a brute-force approach and estimate time/space.
4. Optimize using a known pattern (hash map, two pointers, sliding window, BFS/DFS, heaps).
5. Validate with a walkthrough + edge cases, then code.

Tip: If you freeze, jump back to step 2 or 3. Having a “fallback step” is a mental reset.

2) Train Pattern Recognition (Not Random Grinding)

Instead of doing 100 disconnected problems, group practice by patterns:

• Arrays/Strings: two pointers, sliding window, prefix sums
• Hashing: frequency maps, “seen” sets, grouping
• Trees/Graphs: DFS/BFS, topological sort, union-find
• Heaps: top-k, streaming/merge patterns

After each problem, write one line: “This was a sliding window because…” That sentence is what you’ll recall under stress.

3) Narrate Like a Collaborator (Even If You’re Not Sure)

Silence reads as stuck. If you’re uncertain, say:

• “I’m considering two approaches: A vs B. Here’s the trade-off…”
• “Let’s test with a small example to see which invariant holds.”
• “My current complexity is O(n^2); I think we can reduce it with a map.”

This turns uncertainty into signal: you’re deliberate, not lost.

4) Make Your Code Interview-Friendly

Even strong solutions can look shaky if the code is hard to follow.

• Use clear variable names (left, right, freq, windowSum)
• Add tiny comments only at transitions (e.g., “// expand window”)
• Code in small checkpoints (write helper, then main loop)
• Do a final sweep: off-by-one, null/empty input, return type

5) Build a “Recovery Routine” for When You Get Stuck

Getting stuck is normal. What matters is recovery speed.

• Re-run the sample input manually
• List edge cases (empty, single element, duplicates, negatives)
• Ask: “What data structure would make lookups O(1)?”
• If needed: request a hint professionally (“Am I interpreting constraints correctly?”)

If you had to pick one moment where interviews go off the rails for you—understanding the problem, choosing the approach, or translating to code—which is it, and what usually triggers it?