Video summary

Coding interviews have become insane

Main summary

Key takeaways

News and Commentary

Overview

The video argues that software hiring—especially technical coding interviews—has become dramatically more extreme and less representative of real-world development. It contrasts “simpler” past hiring methods (e.g., basic problems like Two Sum plus small coding projects) with today’s multi-stage interview gauntlets, which often aim to filter candidates who rely on AI tools.

Core Theme: More Extreme, Less Representative

The creator claims interviewing has become contradictory and confusing:

  • Interviewing increasingly focuses on “maximizing tokens,”
  • AI-assisted work may be limited or penalized (e.g., coding “by hand”),
  • Yet candidates can also be rejected for using AI too much,
  • This creates the feeling that the “essence” of real engineering is gone.

Examples of Interview Processes

LeetCode is not dead (in hiring)

The creator investigates whether algorithm-style testing remains central and concludes it is still a core part of hiring at many companies.

OpenAI Platform Engineer (4 stages + homework)

A cited interview process is described as intentionally brutal:

  1. 48-hour homework assignment
    • Build a webhook delivery system.
  2. Senior engineer line-by-line grilling
    • Close scrutiny of reasoning and implementation choices.
  3. System design stage
    • Described as extremely hard—for example, designing an in-memory database using basic SQL commands.
  4. Outcome
    • The candidate ultimately didn’t get hired due to insufficient experience, but the creator frames the process as harsh by design.

Anthropic Infrastructure Engineer (“interview gulag” report)

Reported (via Reddit) as an “interview gulag,” the process includes:

  • Round 1: Online test (two coding tasks)
    • LRU cache in Python
      • Possibly requires manual implementation (e.g., hash map + doubly linked list rather than built-ins).
    • Task management system
      • Priorities, assignments, dependencies, plus thread safety, error handling, and complexity analysis—within 90 minutes.
  • Round 2: Web crawler from scratch
    • The creator claims the exact implementation exists online only via someone connected to the process (not shareable).
  • Additional stages
    • Systems design (e.g., an output API for serving an LLM)
    • Another coding task converting profiling results into trace events, likened to building a flame-graph core.

Chinese tech forums/companies (“god mode”)

The creator claims that in “cutting-edge labs,” interviews may appear to avoid AI usage, but still heavily emphasize:

  • Algorithms,
  • Software engineering principles such as implementing error handling and parallelism manually,
  • These interviews are portrayed not only as “difficult,” but as “god mode.”

Broader Conclusions About Hiring

LeetCode-style testing spreads beyond FAANG

The creator argues this pattern isn’t limited to major tech firms:

  • Nordstrom is specifically mentioned as using LeetCode,
  • Walmart, Target, and Kellogg’s are also referenced as using LeetCode.

AI tools may push more in-person coding

Because AI-assisted fraud tools are said to be widespread, the creator claims some companies are increasing in-person interviews to prevent cheating.

Preparation advice for 2026

The video suggests candidates should expect:

  • LeetCode bots + system design
    • Algorithmic coding and system design remain dominant.
  • Companies generally still may not test how well candidates “prompt” or do “vibe coding.”
    • Preparation should therefore prioritize traditional interview skills.

Sponsor / Product Mention: Cursor

The video promotes Cursor cloud agents, claiming they can:

  • Automate environment setup,
  • Generate and commit code changes into a GitHub PR.

The creator demonstrates a small “rubber duck” generation example and shows tracing/PR packaging features.

Presenters / Contributors

  • Video presenter/creator: Unnamed narrator (speaks throughout)
  • Sponsor: Cursor (Cursor cloud agents)
  • Referenced/anonymous contributors: Reddit users (various interview reports); unnamed individuals from OpenAI/Anthropic/Chinese forums not identified by name

Original video