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Udacity

Harness Engineering with Claude and Claude Code

via Udacity

Overview

Build the engineering skills to put Claude and Claude Code to work on real systems. You'll choose the right Claude model for a job by weighing intelligence, speed, and cost, then design agent architectures that perceive, reason, and act. Using the Claude Agent SDK, you'll build production agents driven by stop-reason loops and engineer context strategies that keep long conversations affordable. You'll configure Claude Code for a multi-surface monorepo team, author reusable Claude Skills, and stand up a multi-shift quality monitoring system with layered orchestration. A capstone ties it together: you run, verify, and defend the design of four working systems. Experience with Python, Typescript, and APIs is assumed.

Syllabus

  • Introduction to Harness Engineering with Claude and Claude Code
    • Set up your workspace for the course: configure your Anthropic API keys, get Claude Code running, and preview the harness engineering skills you'll build.
  • Introduction to Claude 4 Model Architecture
    • Explore the Claude 4.5 model family—Haiku, Sonnet, and Opus—each optimized for a different balance of intelligence, speed, and cost for efficient AI applications.
  • Select Claude 4 Models with Claude API
    • Learn to select the best Claude 4 model—Haiku, Sonnet, or Opus—using the API, matching model strengths to task complexity for faster, cost-effective, and high-quality AI solutions.
  • Introduction to Agentic System Design
    • Discover agentic AI: systems that perceive, reason, and act to achieve goals through a perception-reasoning-action loop, core components, and agent design patterns.
  • Design Agent Architectures
    • Learn to design agent architectures for automating complex tasks using multi-agent systems, enabling speed, specialization, resilience, and scalable AI-powered workflows.
  • Introduction to Claude Agent SDK
    • Learn to build autonomous AI agents with the Claude Agent SDK—set goals, assign tools, manage permissions, and automate complex workflows using natural language instructions.
  • Build Production Agents with Claude Agent SDK
    • Learn to build production AI agents with Claude Agent SDK that use tools to read, process, and write files, automating complex document workflows with clear prompts and structured outputs.
  • Build a Claims Intake Agent with a stop_reason-Driven Loop
    • In this lesson, you'll build a working claims intake agent across three cumulative exercises, starting from a stop_reason-driven agentic loop and ending with a model that decides on its own when to clarify, route, or escalate.
  • Engineer a Long-Conversation Context Strategy for a Retail Support Copilot
    • In this lesson, you'll build a context-engineering harness for a long-running retail support copilot — pruning verbose tool output, keeping a persistent block of case facts, compressing resolved conversations on a token budget, and assembling it all so the facts that matter sit where the model reads them best.
  • Introduction to Claude Code
    • Discover how to use Claude Code as an agentic AI assistant—reading your project, writing code, scaling tasks with subagents, and applying custom knowledge via CLAUDE.md and skills.
  • Configure Claude Code
    • Learn to build sophisticated AI systems by configuring Claude Code with modular agents and reusable skills for task delegation and domain-specific workflows.
  • Introduction to Claude Skills
    • Learn to create and structure Claude skills—modular files that encode expertise—enabling AI agents to perform tasks consistently to your team's standards.
  • Create Claude Skills
    • Learn to create and use Claude Skills to give agents reusable expertise. Build agents that discover, combine, and apply skills for complex tasks, with structured, type-safe outputs.
  • Configure Claude Code for a Multi-Surface Monorepo Team
    • In this lesson, you'll stand up a version-controlled Claude Code configuration for a 12-person retail team working in one monorepo — a modular CLAUDE.md hierarchy with @import standards, path-scoped rules that load per file surface, a read-only /review slash command, a forked /deploy-check skill that keeps its verbose output out of the main session, and a decision doc that names when to use plan mode, direct execution, and the Explore sub-agent. You assemble it across four cumulative exercises, and a Python validator certifies the finished configuration against 35 acceptance tests.
  • Build a Multi-Shift Quality Monitoring System with Claude Orchestration
    • Across four cumulative exercises, you'll assemble a Layer 3 Claude orchestration that wakes up on a schedule, looks at only what changed since last time, and survives a mid-run crash without losing its work: tiered hot/warm/cold state with atomic writes, a push-work-down invocation pipeline, an fsync'd manifest with a resume-vs-fresh recovery rule, and a fork-with-merge scratchpad workflow.
  • Harness Engineering with Claude and Claude Code Project
    • Stand up, run, and verify four reference systems from the course, then defend each one's design in a reflection brief grounded in your own run output.

Taught by

Abdellah Iraamane, Valerie Scarlata, and Sufian Kaki Aslam

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