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Core
Concurrency and Thread Safety
When multiple threads touch shared mutable state, interleavings produce race conditions: lost updates, torn reads, corrupted data. Thread safety means correctness under any interleaving. Locks/mutexes enforce mutual exclusion (pessimistic); optimistic concurrency checks for conflicts at commit and retries (compare-and-swap, version columns). Atomic operations skip locks for simple updates. Deadlock shows up when locks are acquired in conflicting orders. AI, ML, and GenAI engineer interviews probe it because inference servers, batching queues, and shared caches are all concurrent, and the classic double-increment bug still shows up in production.
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PRACTICE THIS IN REAL QUESTIONS
System Design for AI in ProductionDesign a distributed rate limiter for an API serving millions of requests per second.→RAG & Agent System DesignDesign a production RAG system over 10M documents serving ~1,000 QPS at sub-second latency.→Coding & DSAImplement a thread-safe token-bucket rate limiter for concurrent API and tool-calling traffic.→System Design for AI in ProductionYour model looks great offline but drops CTR 2% in production. How do you ship safely and find the cause?→System Design for AI in ProductionDesign a large-scale recommendation feed (retrieval then ranking) for 100M users.→System Design for AI in ProductionDesign a real-time fraud detection system where fraud is under 1% of transactions.→
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