An Opinionated Guide to Preparing for Tech Interviews

For Backend, Frontend, and Full-Stack Engineers

This guide is based on my experience preparing for interviews, my experience interviewing candidates and based on knowledge from others who have shared their experiences.

  • Clear problem framing
  • Debugging ability
  • Comfort with tradeoffs
  • Communication under ambiguity
  • Real-world system intuition
Three pillars
  1. 1Algorithms & Data Structures (baseline competence)
  2. 2Debugging & Code Reasoning (senior signal)
  3. 3System Design (scope, scale, and judgment)

Data Structures & Algorithms

You are not trying to be clever. You are trying to be: correct, clear, efficient enough, explainable.

What interviewers are really asking
“Can this person reason about code under pressure?”

Core data structures you should know cold:

Arrays & Strings
Common problems: Duplicates, Subarrays, Prefix sums, String normalization
  • Iteration patterns
  • Sliding window
  • Two pointers
  • Frequency maps
  • In-place vs extra space
Hash Maps / Sets
Deduplication, frequency counting, fast lookup, cache-like usage
  • Reach for a map when it's obvious
Stacks & Queues
Order and traversal
  • Valid parentheses
  • Undo/redo
  • Depth-first traversal
  • Monotonic stacks (advanced)
Trees (Binary Trees)
No need to memorize rotations or red-black trees
  • DFS vs BFS
  • Recursion vs iteration
  • Height / depth, LCA
  • Serialization intuition
Graphs (Lightweight)
Often appear in system modeling even when not explicit
  • Adjacency lists
  • BFS vs DFS, cycle detection
  • Topological sorting
Algorithms worth practicing
  • Binary search (variants matter)
  • DFS / BFS, recursion + memoization
  • Iterative vs recursive tradeoffs
  • Basic DP (1D or grid-based)
What good looks like
Narrate thought process, ask clarifying questions, start brute-force then improve step by step
  • Avoid silent coding
  • Avoid jumping to optimal with no explanation
Key takeaway
Interviewers care more about how you think than whether you remember a trick.

Debugging & Code Reasoning

This is where senior engineers stand out—and where most candidates underprepare. TypeScript/JS focus.

What these questions test
  • Execution order
  • Closures, async behavior
  • State mutation
  • Real bugs, not puzzles

Core concepts to master:

Event Loop
Explain why something logs in a specific order
  • Macrotasks vs microtasks
  • Promise.then, setTimeout, async/await
  • Why try/catch doesn't catch async errors
Promises & Async
  • Promise.all vs forEach
  • Unhandled rejections, error propagation
  • Race conditions, AbortController
Closures & State
  • Stale closures
  • Shared mutable state
  • Capturing variables in loops
  • this binding
Timers & Cleanup
  • setTimeout vs setInterval
  • Memory leaks, clearing timers
  • Idempotency
Debugging patterns to practice
  • Why does this catch never fire?
  • Why does this function return stale data?
  • Why is this called multiple times?
  • Why does this async loop finish early?
Key expectation
Explain what the code is doing now, not what it should do.
How to answer debugging questions well
Mirrors real production debugging
  1. Restate the problem
  2. Walk through execution step by step
  3. Identify the root cause
  4. Propose a fix
  5. Explain why the fix works

System Design

System design separates mid-level from senior and staff engineers.

What interviewers are evaluating
  • Problem decomposition
  • Understanding of scale
  • Tradeoff reasoning
  • Knowing where complexity actually lives
Reality check
They are not expecting perfect architectures.

Structure every system design answer:

1. Clarify requirements
Asking questions is a positive signal
  • Who are the users?
  • Read-heavy or write-heavy?
  • Latency vs consistency?
  • Global or regional? Data size?
2. Core components
Start simple
  • Client(s), API layer
  • Data store, workers
  • Caching, auth
3. Data model first
Entities, relationships, keys, indexes
  • Before services
4. Scale & bottlenecks
  • Caching, horizontal scaling
  • Queues, async, rate limiting
5. Failure modes
Strong candidates discuss
  • Partial failures, retries, idempotency
  • Backpressure, observability
Critical
If the data model is wrong, everything else is noise.
Common topics to practice
Map directly to real-world systems
  • URL shortener, feed/timeline
  • Notification system, search autocomplete
  • File upload & processing
  • Feature flags, analytics pipeline
Frontend / full-stack system design
Be ready to discuss
  • Client-side caching, SSR vs CSR
  • API contracts, pagination
  • Error handling, performance budgets
  • Analytics and tracking

Behavioral & Communication

Even technical interviews are heavily influenced by communication.

STAR still matters
Situation → Task → Action → Result. Use real examples.
  • Debugging production incidents
  • Navigating ambiguity
  • Disagreeing respectfully
  • Improving performance or reliability
Especially after layoffs
Candidates who explain impact without bitterness, show ownership without blame, and reflect and grow leave a stronger impression.

How to Practice (Efficiently)

Avoid
  • Grinding hundreds of LeetCode
  • Memorizing solutions
  • Ignoring explanation practice
Do instead
  • Solve 1–2 problems per day
  • Explain solutions out loud
  • Practice without autocomplete
  • Debug broken code
  • Mock interviews with peers

Final Advice

Principles
  • Clarity beats cleverness
  • Debugging skill is underweighted but critical
  • System design is about judgment, not diagrams
  • Asking good questions signals seniority
  • Calm reasoning beats fast typing
Prep value ranking
  1. 1Debugging and reasoning
  2. 2System design structure
  3. 3Core DSA patterns
  4. 4Language trivia
Closing thought
Treat interviews as collaborative problem-solving, not exams.