Interview PrepFree

AI Harness Engineering

The Complete Interview Preparation Handbook

Runtime, Control Layer, Guardrails, MCP, Evals, and Observability for Production AI Agents. 19 chapters covering the second half of every AI agent — what sits between the model and the real world.

19 chapters10 parts~12hIntermediate to Advanced

What you'll learn

  • The 7-layer harness architecture
  • MCP and tool calling patterns
  • Memory, state & context windows
  • Sandboxing and safe execution
  • Agent evaluation & benchmarking
  • Safety, guardrails & governance
  • Tracing and observability
  • Multi-agent orchestration

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19 chapter summaries
10 structured parts
Interview Q&A per chapter
Key traps & expert framing

Course Curriculum

10 parts · 19 chapters

Part 1

Foundations

01What Is AI Harness Engineering?02Core Agent Concepts03Anatomy of a Harness — The Seven Layers

Part 2

Context and Instruction Engineering

04Instruction Engineering for Agents05Skills and Reusable Behaviors

Part 3

Tools, Actions, and MCP

06Tool Calling and Safe Action Design07MCP — The Agent Integration Standard08Harness MCP Server and Platform Integration

Part 4

Memory, State, and Retrieval

09State, Memory, and Context Windows10Retrieval and Grounded Reasoning

Part 5

Sandboxed Execution Environments

11Isolation, Sandboxing, and Fast Execution

Part 6

Verification Loops and Quality Engineering

12Guides, Sensors, and Self-Correction

Part 7

Evaluation and Benchmarking

13How to Evaluate an Agent14Failure Modes and Reliability Engineering

Part 8

Safety, Guardrails, and Governance

15Agent Safety and Guardrails16Secure Agent Operations and Enterprise Governance

Part 9

Observability, Runtime, and Cost

17Tracing and Observability18Runtime Engineering and Cost Control

Part 10

Multi-Agent Systems and Orchestration

19Multi-Agent Design and Durable Orchestration