A Reusable Template & the Top Pitfalls
Carry a phase backbone, stock questions, an estimation checklist, a component palette, and tradeoff lenses, and actively counter the five classic pitfalls.
A backbone you can reproduce in 60 seconds
Under interview pressure, working memory shrinks. The fix is a one-page template you have internalized so well you can reproduce it in the first 60 seconds of any round, without it sounding like a recited script. The template is a backbone you hang the specific prompt on, not a monologue you deliver.
The phase backbone (45-minute budget)
1. Scope & requirements ~5 min functional + non-functional, clarify
2. Estimation (back-of-env) ~2 min QPS, storage, bandwidth
3. API + data model ~5 min the contract and the schema
4. High-level design ~15 min box-and-arrow, request path
5. Deep dive(s) ~10 min the 1-2 hard parts
6. Bottlenecks & wrap-up ~3 min scale, failure, tradeoffs, what next
Stock clarifying and NFR prompts
Open with: who are the users and how many, read-heavy or write-heavy, what is the consistency requirement, what latency is acceptable, what is the scale (DAU, QPS), and what is explicitly out of scope. Asking these is problem navigation points on the rubric.
The estimation checklist
So you never freeze on numbers: DAU to QPS (DAU x actions/day / 86,400, then x2 or x3 for peak), storage (records/day x bytes/record x retention), bandwidth (QPS x payload size), cache size (hot set, often the 20% that serves 80%), and server count (QPS / per-box throughput).
The component palette
Pull from these without inventing: load balancer, API gateway, app/service tier, cache (Redis), message queue (Kafka), CDN, object store (S3), search index (Elasticsearch), and database with replicas and shards. When you need a box, it is almost always one of these.
Trade-off lenses
Reach for: CAP/PACELC, push vs pull, sync vs async, SQL vs NoSQL, normalize vs denormalize.
The top pitfalls, each with its counter
- Solutioning before scoping: naming Kafka before you know the requirements. Counter: spend the first 5 minutes on requirements, always.
- Unbounded feature list: trying to design everything. Counter: pick the core 2 to 3 features and defer the rest out loud.
- Generic NFRs: "it should be scalable and fast." Counter: attach numbers (100K QPS, p99 under 200ms).
- Designing in silence: thinking without narrating. Counter: talk continuously.
- No wrap-up: running out of time with no summary. Counter: reserve the last 2 to 3 minutes to name bottlenecks and next steps.
Interview nuance: The template must bend to the prompt. If the interviewer says "assume you know the requirements, go straight to the storage design," skip phases 1 and 2 and say so. Rigidly marching through a memorized order when the prompt does not want it is itself a red flag.
Each snippet is from a real round. Which classic pitfall is the candidate committing?
Recap: Carry a phase-and-time backbone, stock clarifying/NFR prompts, an estimation checklist, a component palette, and trade-off lenses, and actively counter the five classic pitfalls, adapting the template to the actual prompt.
Apply
Your turn
The task this lesson builds to.
Write a one-page personal cheat template (phases, clarifying questions, estimation checklist, component palette, trade-off lenses) you could reproduce in the first minute of any round, and list the 5 pitfalls you will actively avoid.
Think about
- What is the minimal template that starts any round without sounding scripted?
- Which pitfalls most commonly cause failure, and how do you counter each?
- How do you adapt the template to the actual prompt's constraints?
Practice
Make it stick
A second problem on the same idea, so it survives past today.
Adapt your one-page template to a 35-minute clock (a compressed onsite slot, not 45) for the prompt 'Design a URL shortener like Bitly,' and show the running order and time budget you would actually use, including where you cut.
Think about
- Which phases are cheap to lose but expensive to miss, and which can safely compress?
- Which two estimation numbers actually drive a design decision for a URL shortener?
- Where does the single deep dive belong for this specific system?