Description

Have AI Build Automation That Runs in Production. This course examines how to delegate the process of building real, operational automation systems to artificial intelligence (Generative AI) and teaches methods for monitoring, managing, and troubleshooting them. This course is structured to use generative AI to build and develop automation systems that actually run in a real environment. The text and scripts of this course are written by artificial intelligence based on the instructor’s real operational records, and all its statistics and figures have been carefully reviewed. The course is narrated using a synthetic voice and the slides are also generated through the instructor’s proprietary system. In the summer of 2026, a humanities student asked artificial intelligence to take over the complete management of investments and deposits without human intervention, and the result of this process was implemented on a real account with real money. Interestingly, not a single line of the system code was written by the instructor, but the instructor only set the initial capital and the allowed range, and other settings, limits, and stop conditions were written by the AI ​​itself and approved after review. The course is designed based on three real automation projects: automated trading of crypto assets (on a real account from August 19, 2026 to September 6, 2026), a software pipeline that converts articles into videos and automatically publishes them on YouTube and social networks, and another pipeline that creates and reviews Kindle e-books. A large part of the course time is devoted to reviewing stories about failures, errors, and challenges of these systems, rather than just design. Cases such as a 246 yen order that didn’t exist, a day that was completely lost due to a misconfigured line, a 25% profit that the AI ​​refused to take, and an incident where system tests mistakenly sent notifications to the main channel are all extracted from the instructor’s actual system records. During the course, students will have access to nine practical documents and guides, including the first AI request sent and responses, a requirements template, limits and stop conditions, a generic version of the risk policy, a pre-production checklist, audit prompts with two critical findings, machine inspection cases for videos, e-book creation rules, an incident timeline, and specialized worksheets.It should be noted that this course is not investment advice in any way, does not promote any exchange or product, and does not promise guaranteed profits. The instructor’s real account performance during the course was even weaker than simple, fixed purchases at specific time intervals; therefore, the main goal of this course is to teach the decision-making, review, and monitoring of system errors that the person assigning the project must do. Each lesson is set between 1 and 4 minutes, and most lessons include a decision note indicating who made the final decision: the instructor, AI, or AI with instructor approval. Nothing that cannot be confirmed in the documented records is included in the course. Also, questions from learners are received in the Q&A section and answered based on the instructor’s real records.

What you will learn

• Write down the three main decisions that humans make when building an AI system (requirements, constraints, and stopping conditions) to solve personal problems.
• Distinguishing between “the system works” and “the system doesn’t crash” and applying AI testing, monitoring, and self-healing to bridge this gap
• Following the design of three real automation systems (auto-trading, video publishing, and e-books) and assembling their personal version
• Proactively build inspection cases based on real errors (such as non-existent order, lost day due to a setup line, and 25% profit trap)
• Identifying red lines related to laws and responsibilities (investment advice, distance selling laws, and AI information disclosure) and achieving a publishable format

This course is suitable for people who:

• People who have tried to build something using generative AI but abandoned the process because it didn’t run, stalled, or encountered errors
• People who want to perform their tasks automatically without the need for constant supervision but don’t know what decisions need to be made before delegating work.

Course Details Have AI Build Automation That Runs in Production

• Publisher: Udemy
• Lecturer:かねもちの人 电视れれますますます
• Training level: Beginner to advanced
• Training duration: 1 hour and 36 minutes
• Number of lessons: 37

Course syllabus as of 2026/9

Prerequisites for the Have AI Build Automation That Runs in Production course

• You have asked a generative AI (ChatGPT, Claude and so on) to do something for you.
• No programming knowledge is needed. No equipment is needed (the handouts are text files).

Course images

Sample course video

Download link

Download file – 445 MB

Rapidgator link

Download File – 445 MB

File(s) password: www.downloadly.ir

File size

445 MB