Question library
Explained questions for the decisions developers make.
What should I study first?
Preparation works best when later topics build on earlier ones. JavaScript scope and async behavior support Node and React; database rules support backend correctness and system design. Follow the sequence, but spend extra time where you cannot yet explain a concept without reading the answer.
What if I do not know an answer?
An honest answer can still show strong engineering judgment when part of a topic is unfamiliar. Clearly separate facts you know, assumptions you are making and details you would verify. This lets the interviewer assess your reasoning without being misled by confident guesses.
How do I explain my own work?
A project answer should connect a real business problem with your specific contribution and its outcome. The problem → responsibility → action → result structure keeps the story clear without hiding technical details. Add the reason for an important decision and the trade-off you accepted.
How do I answer a debugging question?
A debugging answer is an investigation plan that narrows a symptom to a cause using evidence. It should explain what you would measure, what the result would mean and what you would do next. Separate reducing user impact now from proving and preventing the underlying defect.
How should I explain a technical concept?
A good interview explanation gives the listener a usable understanding of a concept, not just a memorized definition. Start with what it is, why it exists and how it works at a basic level. Then connect the idea to an example, a mistake or a trade-off so the interviewer can follow your reasoning.
How can I reduce dependence on AI?
Reducing AI dependence means being able to understand, test and change a solution without treating generated output as authority. Use AI as a source of candidate ideas, then establish correctness through your own reasoning and evidence. The goal is independent judgment, not avoiding useful tools entirely.
AI, machine learning, deep learning, and generative AI
Artificial intelligence, or AI, is the broad field of making software perform tasks such as recognizing speech, finding patterns, or understanding language. Machine learning, or ML, learns patterns from examples instead of requiring a rule for every case.…
LoRA, QLoRA, and PEFT
PEFT means parameter-efficient fine-tuning: update a smaller subset of parameters instead of the whole model. LoRA trains small low-rank adapter matrices attached to selected model operations. QLoRA combines adapter training with a quantized frozen base model…
vLLM and GPU serving
vLLM is an inference-serving system designed for efficient model execution. Serving techniques such as batching and attention-memory management help multiple requests share expensive hardware. GPU optimization is matching workload, memory, scheduling, and…
Difficulty is an editorial estimate. Completion means you chose to mark a question as understood.