AI Mock Interview Platform: System Design at Scale
Design an AI mock interview platform for one million candidates: real-time voice loop, GPU model serving, stateful sessions, scoring, failover, and cost.
AI Engineering
Production AI systems, agent workflows, evaluation, reliability, and the engineering judgment tested in AI-focused interviews.
17 articles
Context Engineering Interview Guide: Prompts, Memory, Retrieval, Compression, and Context Windows
Context engineering explained for interviews: how to assemble prompts, memory, retrieval, and compression into a token budget the context window can actually hold.
AI Agent Security Interview Guide
Prepare an AI agent security interview answer covering prompt injection, excessive agency, tool abuse, identity, approvals, sandboxing, testing, and response.
How to Evaluate AI Agents: Task Success, Tool Accuracy, Regression Tests, and Human Review
A production guide to evaluating AI agents with end-state task success, tool-call accuracy, regression suites, human review, and release gates.
LLM Observability System Design with OpenTelemetry
Design production LLM observability with OpenTelemetry: trace tokens, latency, cost, tool calls, sampling, privacy, evaluation, and reliable alerts at scale.
Design a Production RAG System in 2026
Design a production RAG system with hybrid search, reranking, evaluation, caching, security, capacity planning, and deployment tradeoffs for interviews.
How to Design a Multi-Agent System: Orchestration, Memory, Tool Calling, and Failure Recovery
A production guide to multi-agent orchestration, scoped memory, safe tool calling, durable checkpoints, recovery, evaluation, and interview trade-offs.
MCP System Design: Secure Multi-Tenant Gateway
Design a secure multi-tenant MCP gateway in TypeScript with tenant isolation, OAuth, policy enforcement, routing, scaling, testing, and interview tradeoffs.
MCP vs A2A vs A2UI: A System Design Guide for AI Agent Architectures
Choose MCP, A2A, or A2UI by architecture boundary, with a protocol decision tree, TypeScript example, failure modes, and interview trade-offs.
AI Coding Interviews in 2026: What Senior Engineers Should Prepare For
Prepare for AI-assisted coding interviews in 2026: architecture judgment, agent supervision, debugging, verification, tests, and senior-level communication.
Fix OpenAI RateLimitError (429): The Complete Guide
OpenAI RateLimitError has two causes that need opposite fixes: insufficient_quota (billing) and rate_limit_exceeded (throughput). Diagnose which, then fix it.
Fix "Token indices sequence length is longer than the specified maximum"
This Hugging Face message is a warning, not the real error — the crash comes later. Fix it with explicit truncation, and watch for the model_max_length sentinel trap.
Resolve "ChromaDB collection does not exist"
Two causes account for almost every ChromaDB 'collection does not exist' — using get_collection instead of get_or_create, and an ephemeral client that never persisted.
Resolve "Hugging Face 401 Unauthorized"
A Hugging Face 401 means the token is missing, invalid, or lacks access. Learn to tell 401 from 403 and 404, and fix gated and private repo access.
Resolve "LangChain ValidationError"
A LangChain ValidationError is a Pydantic error — and it names the exact field. Read loc/type/input, and fix the Pydantic v1 vs v2 mismatch behind most of them.
Resolve "OSError: Can't load tokenizer"
This Hugging Face error means one of two things: a Hub id that can't be found, or a local folder missing tokenizer files. Learn which, then fix it fast.
Fix "SentenceTransformer model download failed"
"Download failed" isn't one error. Triage it by symptom — wrong name, gated auth, network/SSL/proxy, timeout, or a corrupted cache — and apply the right fix.
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