AlgoMindset Blog
Practical, no-fluff guides on AI engineering interviews, system design, and FAANG interview prep.
MCP vs A2A: The Two Protocols in Every 2026 Agent Stack, Explained
Model Context Protocol connects one agent to its tools. Agent2Agent connects agents to each other. Interviewers increasingly expect you to know which layer each one owns, what breaks without them, and how they compose in a real architecture. Here is the comparison nobody has written clearly.
AI Agent Memory Architectures: Short-Term, Long-Term, and Checkpointing — What Interviews Actually Test
Every agent demo dies the same death in production: it forgets. Context windows overflow, sessions end, processes crash. Designing agent memory — working context, episodic recall, durable checkpoints — is now a standard AI system design interview topic. Here is the architecture, layer by layer.
Google's Agent2Agent (A2A) Protocol, Explained: How AI Agents Talk to Each Other
MCP standardized how a single agent talks to tools and data. A2A standardizes how separate agents — possibly built on completely different frameworks — discover each other and delegate work. Here is what the protocol actually contains and why interviewers are starting to ask about it.
LangGraph Tutorial: Building Stateful, Multi-Step AI Agent Workflows (Free)
Plain LangChain chains run in a straight line. Real agents loop, branch, and retry. LangGraph models an agent as an explicit graph with shared state — here is how the core pieces fit together, with a minimal worked example.
LangChain Tutorial: Building Your First AI Agent (Free, Step-by-Step)
LangChain gets a reputation for being over-abstracted, but the core ideas — chains, tools, memory, retrieval — are straightforward once you see them without the framework jargon. This is a free, from-scratch walkthrough of all four.
The 12 Coding Interview Patterns That Cover Almost Every FAANG Question
There are thousands of possible coding interview questions and roughly a dozen underlying patterns. Learn to recognize which pattern a question is testing and you stop re-deriving solutions from scratch under time pressure — here is the full list, with what actually signals each one.
5 Follow-Up Questions AI System Design Interviewers Always Ask (And How to Answer Them)
The initial design is rarely what separates a hire from a no-hire in an AI system design loop — it is how you handle the follow-up. Here are the five questions that come up constantly across RAG, agent orchestration, and inference serving rounds, with what a strong answer actually sounds like.
AI Engineer System Design Interviews in 2026: The Complete Prep Roadmap
RAG pipelines, agent orchestration, and LLM inference serving have become the new bar for senior AI engineering interviews. Here is how to prepare for all three without wasting weeks on the wrong material.