Udemy - Agentic Harness Engineering - Harness Design for AI Engineers

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2.4 GB
  • Uploaded Byfreecoursewb
  • Downloads58
  • Last checkedJul. 10th '26
  • Date uploadedJul. 09th '26
  • Seeders 1
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Infohash : AEF5C29E888DC7DDE9EE42151E8FF5EF0A064684

Agentic Harness Engineering: Harness Design for AI Engineers

https://WebToolTip.com

Published 7/2026
Created by Fikayo Adepoju
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 23 Lectures ( 4h 35m ) | Size: 2.4 GB

Harness Engineering for Long-Running, Code Executing, and Persistent AI Agents like Claude Code, Codex, and OpenClaw

What you'll learn
⚡ Build a Complete Harness: Design and implement a multi-layered agent harness from scratch using raw Python and custom execution loops.
⚡ Implement Multi-Session Memory: Utilize the AGENTS[dot]md memory file standard alongside vector-indexed retrieval for persistent, cross-session recall.
⚡ Defeat Context Rot: Implement advanced compaction hooks and tool call offloading middleware to sustain model performance over long runs.
⚡ Secure Code Execution: Engineer isolated Docker sandboxes with execution timeouts, command allow-lists, and restricted outbound networks.
⚡ Optimize with LangSmith Tracing: Build a rigorous evaluation harness to profile agent traces, diagnose failures, and measure benchmark pass rates.
⚡ Orchestrate Long-Horizon Tasks: Deploy the "Ralph Loop" to intercept premature agent exits and enforce goal-driven, autonomous continuity.

Requirements
❗ Python Proficiency: Strong comfort with advanced Python syntax, file handling, and structural logic.
❗ LLM Foundations: Basic familiarity with Large Language Models, chat APIs, and the fundamental mechanics of prompting.
❗ Environment Tools: Comfort using the command line (Bash) and a local development machine with Docker installed for sandboxing.

Files:

[ WebToolTip.com ] Udemy - Agentic Harness Engineering - Harness Design for AI Engineers
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction
    • 1. Introduction.mp4 (52.2 MB)
    • 2. Course Materials.html (5.4 KB)
    2 - Agent Harness - All the Parts
    • 10. Harness Component 5 - The Memory.mp4 (32.6 MB)
    • 11. Harness Component 6 - The Observability.mp4 (24.3 MB)
    • 12. How Every Harness Component Connects Together.mp4 (25.3 MB)
    • 13. Decomposing a Real-World Harness - Claude Code.mp4 (95.0 MB)
    • 3. The Raw Model Problem.mp4 (116.3 MB)
    • 4. Demo - Exposing the Gaps.mp4 (123.6 MB)
    • 5. Defining the Harness - The 6 Core Components.mp4 (90.2 MB)
    • 6. Harness Component 1 - The Loop Architecture.mp4 (84.9 MB)
    • 7. Harness Component 2 - The Tools.mp4 (76.5 MB)
    • 8. Harness Component 3 - The Context.mp4 (183.0 MB)
    • 9. Harness Component 4 - The Environment.mp4 (98.1 MB)
    3 - Designing the Harness Conversation Loop
    • 14. Harness Project Setup.mp4 (86.3 MB)
    • 15. Writing the Bare Conversation Loop.mp4 (107.6 MB)
    • 16. Using Kimi Models - A Powerful Cheaper Alternative.mp4 (76.8 MB)
    • 17. System Prompt as a First Harness Primitive.mp4 (195.8 MB)
    • 18. What's Missing - Mapping the Gaps.mp4 (104.7 MB)
    4 - The File System Layer
    • 19. Why we need a File System first.mp4 (16.4 MB)
    • 20. Building the File System Abstraction.mp4 (322.5 MB)
    • 21. Adding Git Support for Versioning.mp4 (199.8 MB)
    • 22. Injecting Durable Memory at Session Start with AGENTS.md.mp4 (168.9 MB)
    • 23. Hands-On Task Multi-step Research and Report.mp4 (167.7 MB)
    • Bonus Resources.txt (0.1 KB)

Code:

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