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AI School "Conductor": Building IT Products Without Programming Skills

Intensive course: 20 hours (10 sessions of 2 hours each)

This program is built for people who want to stop merely "chatting" with AI and start using AI to create a team of AI agents that can execute any of your requests.

We teach Agentic Engineering and Agentic Orchestration - methodologies where you act as the Conductor (the person managing the company), while autonomous AI agents handle all technical work and marketing.


🚀 How to Join

We are currently accepting applications for the live-mentor cohort. To participate:

  1. Fill out the form: Application Form
  2. Join the Telegram Group: AI School EN
  3. Introduce yourself: Once you've filled out the form, drop a message in the group!

Curriculum

Session 01: Introduction to Vibe Coding and AI + IDE + GitHub Setup

  • Theory (10 min): What is Vibe Coding? Logic is more important than syntax. Tool overview.
  • Practice (110 min):
    • IDE with an AI assistant
    • Git installation
    • Git Baseline: Initializing your first repository. Why "save points" (commits) are your safety net
    • Creating your first project folder
    • Creating your first project
  • Result: A working local page, configured environment, first commit, and first project

Session 02: Free Tokens, Token Savings, Rules and Instructions for AI

  • Theory (10 min): What tokens are, where to get them, and how to save them; what context is and how to avoid overflowing it
  • Practice (110 min):
    • Free access to models
    • API keys and API endpoints
    • Integrating keys into the IDE
    • Context optimization
    • A minimal required set of rules and instructions for AI
  • Result: Unlimited access to previous-generation and latest AI models, with 80% to 99% savings on paid-model tokens

Session 03: Prompt Engineering: Architecture + Specification + Plan

  • Theory (10 min): Describing structure vs. "make it beautiful." How do you understand what to create?
  • Practice (110 min):
    • Choosing a project (with AI)
    • Creating the project architecture (with AI)
    • Creating the project specification (with AI)
    • Creating the development plan (with AI)
    • Creating a visual prototype (with AI)
    • Exporting code into the working environment (with AI)
  • Result: A finished visual prototype and a clear technical description for further development by a team of AI agents

Session 04: Development with a Team of AI Agents: MCP + Skills

  • Theory (10 min): AI agent roles, what MCP and Skills are, and why they are needed
  • Practice (110 min):
    • Installing the required MCPs (with AI)
    • Installing the required Skills (with AI)
    • Assigning roles to AI agents (with AI)
    • Launching a team of AI agents and developing a product (with AI)
  • Result: A personal team of AI agents ready to start executing any task you give them

Session 05: Memory for Your AI Agents: LLM Wiki

  • Theory (10 min): Why AI agents need memory and Andrej Karpathy's method
  • Practice (110 min):
    • Launching memory storage on your own device
    • Creating an LLM wiki (with AI)
    • Configuring the memory compiler (with AI)
    • Connecting an AI agent to the "second brain" (with AI)
    • Integrating the "second brain" into any other projects
  • Result: Your AI agents do not forget anything, save context, and automatically update your "second brain"

Session 06: Databases + Authentication

  • Theory (10 min): What kinds of databases exist and why they are needed
  • Practice (110 min):
    • Choosing a suitable database (DB)
    • Creating the DB (with AI)
    • Configuring the DB (with AI)
    • Setting up authentication for users
    • Integrating the DB into your project (with AI)
  • Result: You get a database that stores information about your users, and your users can connect to your product using email or any other accounts

Session 07: Launching Your Own AI Agents / Alternatives to OpenClaw

  • Theory (10 min): What autonomous AI agents can do, and how and where they can be used
  • Practice (110 min):
    • Creating and deploying an AI agent (with AI)
    • Connecting an LLM to the AI agent
    • Connecting the AI agent to Telegram
    • Giving the AI agent a routine (with AI)
    • Giving the AI agent its first tasks
  • Result: You get a personal AI agent with its own specification for completing specific tasks, and you communicate with it through Telegram

Session 08: Deploying Your Product

  • Theory (10 min): What production deployment is and where to host your product
  • Practice (110 min):
    • Deploying a web application (with AI)
    • Choosing hosting
    • Choosing a domain
    • Setting up CI/CD automation (with AI)
    • Creating an APK (with AI)
    • Preparing deployment to Google Play and the App Store
  • Result: Your product is available to users through an HTTPS URL or as an APK file

Session 09: AI Marketing

  • Theory (10 min): Why marketing agents are needed and how to structure a marketing team
  • Practice (110 min):
    • Setting up Skills for marketing agents (with AI)
    • Getting API keys from social networks
    • Setting up SEO tools (with AI)
    • Setting up market research tools (with AI)
    • Launching a team of AI marketers on a server (with AI)
  • Result: You get a team of AI marketers that will automatically create content and collect feedback

Session 10: Product Presentation - Graduation Project

  • Theory (10 min): How to prepare your product presentation and pitch
  • Practice (60 min):
    • Creating a description of your product (with AI)
    • Creating a presentation (with AI)
    • Creating a video overview for your project (with AI)
    • Preparing a product pitch (with AI)
    • Preparing answers to questions (with AI)
  • Graduation (50 min):
    • Presenting your project (either independently or with AI)
  • Result: You will have your own working product with a finished presentation, which you can use yourself, sell to third parties, or submit for a grant

Why Study at AI School?

  1. 0% boring theory: We do not teach Python or JavaScript syntax.
  2. 100% control: You learn to manage the tools that write code for you.
  3. Efficiency: You learn how to spend pennies on tokens where others spend thousands.
  4. Calendar-based group training: You take on additional accountability, which helps you avoid procrastination.
  5. Real result: Training does not end until you create a real product that you can sell or use yourself.

Built for those who want to build the future, not just watch it happen.

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