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A practical 2026 guide to MCP interview questions, covering interoperability, client-server boundaries, tool design, security controls, and when a plain API is a better choice.
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A practical risk-control workflow for live screen-share interviews: pre-round baseline, in-round operating principles, and a short recap loop that reduces avoidable leaks and disruptions.
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A practical late-2026 guide to AI-aware coding interviews, where public hiring platforms now expose sharply different AI policies and force candidates to prepare for multiple evaluation modes.
Read articlearrow_forwardA practical guide to Claude Code, Codex, and Cursor interview formats in 2026, focused on AI-native workflow leadership, MCP and permission judgment, and why vibe coding collapses under follow-up pressure.
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A practical 2026 guide to AI-mediated first-round hiring, covering AI interviewer assessments, async prompts, screening layers, and what software engineers should change in response.
Read articlearrow_forwardThe definitive guide to surviving hand-rip algorithm rounds at big tech companies. Covers what interviewers actually score, the 6-phase execution framework, common patterns by company, and the 4 silent killers that eliminate correct solutions.
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A practical guide to the 4 layers of AI now present in tech interviews: screening bots, async video scoring, AI-assisted evaluation, and AI-native coding rounds. What each layer means for your preparation and how to adapt without overcorrecting.
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A structured playbook for the 2026 campus hiring season in China. Covers timeline, big tech intern vs full-time differences, resume strategy, algorithm prep, and how AI is changing the screening process.
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Understanding the memory systems that make AI coding agents effective—from context windows to persistent memory, from automatic consolidation to retrieval-augmented recall.
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