Study notes
Things I'm learning, written to be read in one sitting: what SDE2 interviews really ask, the fundamentals behind the answers, and how the job is changing with AI.
Behavioural & career 7 notes
The non-coding rounds: telling your story, owning projects, incidents, conflict, leadership and growth.
Introduction & career
Tell me about yourself, why you're moving, why this company, and what changes at SDE2: the opening questions, what they're really testing, and answers you can adapt.
Projects & ownership
The project deep dive, measuring impact, defending trade-offs, and owning things nobody assigned you: how to prepare the stories that carry an SDE2 loop.
Engineering practices
Good code, code reviews, testing strategy, tech debt, estimates and adopting new tech: how SDE2s answer the 'how do you work?' questions without sounding dogmatic.
Production & reliability
Incidents, debugging what you can't reproduce, postmortems, alerting, peak-traffic prep, designing for failure and sustainable on-call, explained the way an owner thinks.
Collaboration & communication
Disagreements with peers and PMs, difficult people, ambiguity, bad news, influence across teams and explaining tech to non-engineers: the people questions, with the patterns behind good answers.
Leadership & mentorship
Mentoring, onboarding yourself fast, influence without authority, leading a multi-engineer project, deciding with incomplete information and prioritising: what 'multiplier' behaviour looks like in practice.
Growth & mindset
Critical feedback, your biggest mistake, learning on your own, pressure, motivation and the questions you ask at the end, plus a checklist before any behavioural round.
Technical fundamentals 7 notes
The breadth every backend engineer gets quizzed on, from SOLID to sagas, explained with the follow-ups.
OOP & design principles
SOLID with real examples, composition vs inheritance, the patterns you'll actually use, dependency injection, interfaces vs abstract classes, immutability, and spotting bad design.
APIs & the web
What happens when you hit Enter, REST design, HTTP semantics and idempotency keys, REST vs gRPC vs GraphQL, auth with sessions, JWT and OAuth2, pagination, versioning and rate limiting.
Databases
SQL vs NoSQL, how indexes work and when they hurt, ACID and isolation levels, optimistic vs pessimistic locking, N+1 queries, normalisation, replication and sharding.
Caching & performance
Cache-aside and friends, invalidation that actually works, stampedes, penetration and avalanches, what belongs on a CDN, the latency numbers to know, and a method for any performance problem.
Concurrency & the OS
Processes, threads and virtual threads, race conditions, deadlocks, locks and semaphores, event loops and non-blocking I/O, garbage collection, and stack vs heap vs virtual memory.
Networking & distributed systems
TCP vs UDP, load balancers, CAP and PACELC, consistency models, Kafka vs queues, delivery guarantees and the outbox pattern, sagas, and resilience with timeouts, retries, breakers and bulkheads.
Security, DevOps & architecture
The web vulnerabilities every backend engineer must stop, containers vs VMs, Kubernetes essentials, safe deployment strategies, monolith vs microservices, observability, and what 'five nines' really costs.
Engineering in the AI era 4 notes
What an SDE2 is paid for when AI writes the code, and how to build features on top of LLMs.
Mindset & expectations
What an SDE2 is paid for when AI writes much of the code, why design skill matters more not less, how the bar moved, which skills to double down on, and the biggest mistake engineers make with AI.
The AI-assisted workflow
A spec-plan-slice-verify workflow for coding agents, writing prompts that produce correct code, a review checklist for generated code, keeping team quality high, and measuring whether AI is actually helping.
Building AI features
LLM fundamentals for backend engineers: tokens and context, RAG vs fine-tuning, tool calling and agents, evals for non-deterministic output, the main risks, cost control, and a worked design example.
Interviews & positioning
How to answer 'how do you use AI?', how to reframe a design-and-hand-written-code background as a strength, what to ask the interviewer about AI, and a practical 90-day plan to close the gap.
Data structures & algorithms coming soon
Patterns, not puzzles: how to recognise the shape of a problem.
Low- and high-level design coming soon
Object design and system design, worked end to end.