Question 1

What are reasoning models and when should you use them?

Accepted Answer

**Target Audience:** Engineers who know how a regular LLM API call works and need to decide where a "thinking" model belongs in a product.
**Difficulty:** Medium
**Verified with:** Node 22.22.0 and Python 3.12.3 (the example is deterministic arithmetic and stub answers; no real model is called). Product facts are cited inline with the source and the date checked (October 2026).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so

Question 2

What should you log and trace in an LLM application?

Accepted Answer

**Target Audience:** Engineers building their first production LLM feature who need to decide what goes into logs, metrics and traces; also interview candidates who will be asked "how would you debug a bad answer?".
**Difficulty:** Medium
**Verified with:** Node 22.22.0 and Python 3.12.3 (the log-record builder below, identical output in both). Prices in the example are made-up round numbers, not any provider's price list.

> **How to read this doc:** Every idea is explained in plain language fi

Question 3

When should you split work across multiple agents instead of one?

Accepted Answer

**Target Audience:** Engineers deciding whether an agent feature needs a "multi-agent architecture", and candidates who will be asked to defend that choice either way.
**Difficulty:** Hard
**Verified with:** Node 22.22.0 and Python 3.12.3 (the example below, identical output). Published figures were checked in October 2026: Anthropic's engineering posts "Building effective agents" (December 2024) and "How we built our multi-agent research system" (June 2025), and secondary coverage of Cognition'

Question 4

How do you evaluate and debug agent trajectories?

Accepted Answer

**Target Audience:** Engineers building tool-using agents who can already evaluate a single LLM response and now need to evaluate, and debug, multi-step runs with real side effects.
**Difficulty:** Hard
**Verified with:** Node 22.22.0 and Python 3.12.3 (the trajectory scorer below). The τ-bench definitions and results, and the LangChain agentevals match modes, were checked via web search in October 2026; the agentevals per-mode rules were only found in secondary sources and are marked as such.

Question 5

What are common RAG failure modes and how do you debug them?

Accepted Answer

**Target Audience:** Engineers who run or are about to run a RAG feature in production and need a systematic way to turn "the bot got it wrong" into a specific, fixable cause.
**Difficulty:** Hard
**Verified with:** Node 22.22.0 and Python 3.12.3 (the chunk-boundary demo and the triage harness below). The request logs in the triage are hand-written examples of each failure type, not data from a real system. Research findings are cited inline.

> **How to read this doc:** Every idea is explained

AI ENGINEERINGDECODED.

Medium

What are reasoning models and when should you use them?

What should you log and trace in an LLM application?

Hard

When should you split work across multiple agents instead of one?

How do you evaluate and debug agent trajectories?

What are common RAG failure modes and how do you debug them?