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 Duration 14 hours

Course Outline

Familiarizing Ourselves with Instruments and Initial Construction

Operational Mechanisms of Artificial Intelligence Programming Instruments

Subject matter addressed:
• Comprehending the boundaries and capabilities of context windows
• The concept of statelessness and the method by which artificial intelligence models retain information during a session
• The Plan, Execute, and Review procedural framework
• Identifying areas where artificial intelligence programming instruments demonstrate proficiency and those where limitations exist
• Established protocols for engaging effectively with artificial intelligence support systems

The Current Artificial Intelligence Programming Environment

Subject matter addressed:
• A comprehensive examination of the contemporary artificial intelligence programming sector
• Distinguishing between various platforms, including Cursor, GitHub Copilot, and Claude Code
• Selecting appropriate models and platforms tailored to specific operational requirements
• Analyzing the distinct advantages and constraints of diverse programming assistants
• Practical guidance for implementing tools within software development units

Structure of Effective Prompts

Subject matter addressed:
• Essential elements required for prompt efficacy
• Providing precise context and clear task definitions
• Defining output structures and operational constraints
• Standard frameworks and templates for prompt construction
• Strategies for enhancing the quality and consistency of prompts

Initial Programming: Development from the Ground Up

Subject matter addressed:
• Initiating project development from an empty directory
• Establishing the foundational application architecture and framework
• Managing library dependencies and project settings
• Refining generated code through iterative improvement
• Conducting tests and finalizing the solution

Management of Existing Codebases, Customization, and Assessment

Operating Within a Codebase

Subject matter addressed:
• Navigating and interpreting unfamiliar code structures
• Utilizing artificial intelligence tools to query and analyze existing projects
• Mapping application architectures and dependency relationships
• Generating technical documentation and summaries
• Streamlining the integration process for existing projects

Routine Operations: Correction, Feature Implementation, and Testing

Subject matter addressed:
• Employing artificial intelligence tools to diagnose and resolve defects
• Developing new features and system enhancements
• Authoring and refining automated test suites
• Verifying generated code and modifications
• Enhancing productivity in standard development activities

Customization: Definition and Application

Subject matter addressed:
• Interpreting project regulations and configuration files
• Introduction to the AGENTS.md file and project memory frameworks
• Determining the appropriate application of customization mechanisms
• Recommended practices for configuring artificial intelligence assistants
• An overview of advanced implementation methodologies

Safeguards, Risks, and Professional Judgment

Subject matter addressed:
• Evaluating and verifying artificial intelligence-generated code
• Understanding common failure patterns and system limitations
• Identifying prompt injection threats and security vulnerabilities
• Determining the scope of work suitable for delegation to artificial intelligence
• Exercising human oversight and maintaining accountability in software development

Requirements

Prior coding experience or proficiency with artificial intelligence tools is not required.

Basic familiarity with code structures or Git is beneficial.

A licensed account (Claude Code / Cursor / Copilot) is required.

Intended Audience:

Individuals new to artificial intelligence-assisted development, including non-coders and occasional developers, as well as technical-adjacent roles in quality assurance, data analysis, product management, or operations. No prior development background is assumed.

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