Software Engineer Interview Prep Podcast

Prabuddha Ganegoda
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Ace your Software Engineer interviews with confidence. This podcast helps you organize your thinking, strengthen problem-solving skills, and prepare effectively for real technical interviews. Topics covered include: Programming (Java & Python) Data Structures & Algorithms System Design AI for Software Engineers Interview strategies & mindset Whether you're targeting Big Tech, startups, or senior engineering roles, each episode helps you think clearly, solve better, and perform at your best.

  1. 4 days ago

    Cracking the Senior System Design Interview: RADIO, NFRs, Scale and CAP

    Senior system design interviews don't test whether you know what a load balancer is. They test how you think under pressure: how you handle ambiguity, weigh brutal trade-offs and defend every box you draw. In this deep dive we unpack the framework used to evaluate senior engineers, architects and principal candidates. You'll learn: - The RADIO framework (Requirements, API, Data model, Infrastructure, Optimize) and how to split your 45 minutes - The one question that instantly signals seniority - REST vs gRPC, API versioning, and why offset pagination breaks at scale - Choosing a database by access pattern, and justifying every component with the NFRs - Why skipping non-functional requirements is the number one reason senior candidates fail - Peak vs average TPS, P99 tail latency, latency budgets, RPO and RTO, and compliance - Sticky sessions, sharding, hot shards, read replicas, CQRS and event streaming - The math of the nines, active-active vs active-passive, circuit breakers, bulkheads and graceful degradation - Exponential backoff with jitter to survive the thundering herd - The CAP theorem, the consistency spectrum, and why banks must choose CP to prevent double spending Chapters 00:00 Introduction 00:49 They test judgement, not definitions 02:22 The roadmap 03:36 The RADIO framework 04:47 Requirements in five minutes 06:00 The seniority signal 06:47 API design and versioning 08:20 Offset vs cursor pagination 09:05 Choosing the data model 10:18 Justifying infrastructure with NFRs 11:28 Network boundaries 11:50 Attacking your own design 12:39 Observability and cost 14:37 The URL shortener trap 15:23 The NFR cheat sheet 15:46 Peak vs average traffic 16:33 Tail latency and fan-out 17:44 Latency budgets 19:16 RPO and RTO 20:02 Compliance: GDPR, PCI DSS, SOX 21:37 Scaling out and sticky sessions 23:13 Sharding and the hot shard 24:49 Cross-shard query trade-offs 25:58 Read replicas and replication lag 27:08 CQRS 28:41 Event streaming and idempotency 31:02 The nines of availability 33:04 Active-active vs active-passive 34:37 Circuit breakers 36:09 Bulkheads 37:18 Graceful degradation 38:26 Thundering herd, backoff and jitter 40:25 The CAP theorem 43:09 The consistency spectrum 45:32 The FinTech exception: double spending 47:05 Why a rejected transaction beats a duplicate 48:13 Recap: every design is a trade-off 49:23 Final thought #SystemDesign #SoftwareEngineering #DistributedSystems #InterviewPrep #TechInterviews #SoftwareArchitecture Interview Prep Podcast

  2. 4 days ago

    Kafka in Production: Failure Scenarios for Staff-Level Interviews

    A single misconfigured setting in Kafka doesn't just slow a page down. It can silently vaporize financial transactions. In this deep dive we walk through real production failure scenarios and the exact reasoning interviewers look for in staff-level system design interviews. You'll learn: - Why acks=1 loses data, and the four configuration layers for zero data loss - Consistency vs availability: why a healthy cluster refuses writes on purpose - Pushing from 400,000 to 2 million events/s with batching, linger.ms and compression - How retries reorder a debit and a credit, and how idempotent producers fix it - Rebalance storms, cooperative sticky assignment and static membership - Hot partitions and the irreducible trade-off between ordering and scale - How deleting and recreating a topic silently skips hours of data - A 3 AM role-play: 85 under-replicated partitions, a disk at 96%, and why you never restart the broker - Exactly-once with Kafka transactions, and exactly-once into PostgreSQL - Tiered retry topics and dead letter queues - Split brain, KRaft quorums and vanishing tombstones - System design at scale: multi-tenant topics, quotas, event-driven sagas and change data capture with Debezium Ideal for backend and platform engineers preparing for senior and staff-level interviews. Chapters 00:00 Distributed systems have no X-ray 01:08 Why Kafka interviews matter 02:19 acks=1 and the 200 missing payments 03:27 Four layers of zero data loss 05:21 The CAP theorem trade-off 06:31 Throughput: taxis vs buses 07:42 batch.size, linger.ms and compression 09:38 When retries reorder messages 11:38 Idempotent producers 12:48 Message keys and partition ordering 13:12 Flash sale: buffer exhausted 14:22 Decoupling with a local buffer and circuit breaker 16:18 Rebalance storms 18:13 Eager vs cooperative sticky rebalancing 19:25 Static group membership 20:12 Hot partitions and the hot key problem 23:18 Silent data loss after recreating a topic 25:20 auto.offset.reset and topic versioning 26:08 3 AM: 85 under-replicated partitions 28:54 Why you never restart the broker 29:42 Disk at 96%: the 15-minute response 31:36 Throttled reassignment, Cruise Control, tiered storage 33:36 Duplicates in consume-transform-produce 34:47 Kafka transactions 37:11 Exactly-once into PostgreSQL 39:56 Head-of-line blocking from retries 41:08 Tiered retry topics and DLQs 42:42 Split brain 44:38 KRaft and quorum math 45:27 Log compaction tombstones 48:33 Multi-tenant topic design 50:07 Tenant tiers and client quotas 51:40 Event-driven sagas 53:15 Compensating transactions 54:51 Change data capture with Debezium 57:13 Recap 58:46 Will offsets still matter in five years? #Kafka #SystemDesign #DistributedSystems #SoftwareEngineering #InterviewPrep #BackendEngineering Interview Prep Podcast

  3. 4 days ago

    How WebSockets Power the Real-Time Web

    Why does a chat message arrive instantly, but the web was never built for it? In this deep dive we unpack WebSockets: how engineers turned a request/response web into an open, two-way line, and what that costs at scale. You'll learn: - Why short polling, long polling and Server-Sent Events fall short (and the math behind 200,000 empty requests per second) - How the WebSocket handshake hides inside a normal HTTP request, and the "cryptographic high-five" that proves the server understood - Why clients mask every frame but servers never do, and the cache-poisoning attack it prevents - Half-open connections, idle timeouts and why heartbeats every 20–30 seconds keep sockets alive - Close code 1006, the "ghost code" every system design candidate should know - The real cost of state: 1 million connections × 20 KB = 20 GB of RAM before a single message - Gateways, pub/sub buses, the thundering herd, and exponential backoff with full jitter - Cross-site WebSocket hijacking, and why tokens never belong in the URL - When NOT to use WebSockets: SSE vs WebSockets vs gRPC - Head-of-line blocking and why QUIC and WebTransport may be next Perfect for software engineers preparing for system design interviews. Chapters 00:00 Intro: the web wasn't built for real time 02:19 Short polling and the 200,000 requests/second problem 03:54 Long polling 04:42 Server-Sent Events 05:31 WebSockets and full-duplex communication 06:19 The handshake: disguised as HTTP 07:55 Sec-WebSocket-Accept: the cryptographic high-five 09:05 Why clients mask frames 09:53 Cache poisoning explained 11:50 Half-open connections 12:38 Idle timeouts at every network hop 13:47 Heartbeats: Ping and Pong 14:36 Close code 1006 15:23 The cost of state 16:57 Scaling with gateways and pub/sub 18:34 The thundering herd 19:46 Exponential backoff with full jitter 20:58 Cross-site WebSocket hijacking 22:32 Ticket-based authentication 23:45 When not to use WebSockets 24:55 The big trade-off: latency vs statefulness 25:43 Head-of-line blocking 26:55 What's next: QUIC and WebTransport #SystemDesign #WebSockets #SoftwareEngineering #InterviewPrep #BackendEngineering Interview Prep Podcast

  4. 8 Jun

    Agentic coding Session 3 - Live Problem-Solving Under Pressure

    The mental model and the toolkit come together here. We cover managing a session in real time — when to course-correct, when to clear and restart — the five failure patterns that quietly tank your work and how to fix each, and a complete worked problem run end to end: explore, plan, implement in a fresh session, verify with tests, and review with an adversarial subagent. Plus scaling techniques and exactly how to demonstrate competence when someone is watching you code.

  5. 8 Jun

    Agentic coding Session 2 — Configuration & Extension Mastery

    This is where the deep technical interview questions live. Claude Code has five extension points — CLAUDE.md, skills, hooks, subagents, and MCP — and knowing which to reach for is a core competency. We break down each one: why CLAUDE.md is always-on context you must keep lean, how skills load knowledge on demand and why the description field decides everything, when hooks give you deterministic guarantees, how subagents isolate heavy work in their own context, and how MCP and CLI tools connect the outside world. Ends with the decision framework that ties them all together.

  6. 8 Jun

    Agentic coding Session 1 — The Agentic Mental Model

    The Agentic Mental Model: what "agentic" means and the loop, the context window as the governing constraint, explore→plan→implement→commit, verification, and precise prompting. Most engineers meet AI coding tools as a smarter autocomplete. Claude Code is something else: an agent that explores, plans, and writes code on its own while you direct and review. This opening episode rewires how you think about the tool. We unpack what "agentic" actually means, why the context window is the one constraint that explains every best practice, the explore-plan-implement-commit workflow, and the discipline of verification — giving the agent a check it can run so it self-corrects. The foundation for everything that follows, and for any interview that asks how you think with an AI agent.

  7. Season 1, Episode 1 Trailer

    S1E1 [Preview] - The Job Changed While You Were Sleeping

    SEASON 1 — "The Shift" Listen to - S1E1 Interview an engineer who transitioned from backend → AI engineer. Their story IS the season premise.

  8. 6 Jun

    S1E1 - The Job Changed While You Were Sleeping

    SEASON 1 — "The Shift" Interview an engineer who transitioned from backend → AI engineer. Their story IS the season premise.

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Ace your Software Engineer interviews with confidence. This podcast helps you organize your thinking, strengthen problem-solving skills, and prepare effectively for real technical interviews. Topics covered include: Programming (Java & Python) Data Structures & Algorithms System Design AI for Software Engineers Interview strategies & mindset Whether you're targeting Big Tech, startups, or senior engineering roles, each episode helps you think clearly, solve better, and perform at your best.

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