Get in Touch

Course Outline

Day 1 | Foundational Principles and Initial Implementation

Module 1 | Operational Mechanics of AI Coding Utilities

Curriculum Overview:
• Comprehension of context window parameters and associated constraints
• Session state management and information retention mechanisms in AI models
• The Plan → Execute → Review operational workflow
• Capabilities and technical limitations of automated coding assistants
• Established practices for effective human-AI collaboration

Module 2 | Ecosystem Analysis of AI Coding Solutions

Curriculum Overview:
• Comprehensive survey of the current AI coding landscape
• Comparative analysis of primary platforms, including Cursor, GitHub Copilot, and Claude Code
• Criteria for selecting appropriate models and tools based on specific operational requirements
• Evaluation of strengths and limitations across various coding assistants
• Strategic guidelines for integrating these technologies into development teams

Module 3 | Structure of Effective Prompts

Curriculum Overview:
• Essential components required for high-quality prompts
• Methods for establishing clear context and defining task objectives
• Specifications for output formats and operational constraints
• Standardized prompting frameworks and templates
• Techniques for enhancing consistency and accuracy in prompt engineering

Module 4 | Initial Development: Construction from Base State

Curriculum Overview:
• Project initialization within a directory structure
• Establishment of initial application architecture and scaffolding
• Management of project dependencies and configuration files
• Iterative refinement of generated code outputs
• Validation procedures for the final solution

Day 2 | Codebase Integration, Customization, and Oversight

Module 5 | Operations Within Established Codebases

Curriculum Overview:
• Navigation and comprehension of unfamiliar code structures
• Utilization of AI tools for querying and analyzing existing projects
• Mapping application architecture and dependency chains
• Generation of technical documentation and executive summaries
• Acceleration of personnel onboarding into active development cycles

Module 6 | Routine Development Tasks: Remediation, Enhancement, and Testing

Curriculum Overview:
• Application of AI tools for bug identification and resolution
• Implementation of new features and system enhancements
• Authoring and optimizing automated test suites
• Validation of generated code modifications
• Optimization of productivity in daily software development activities

Module 7 | Customization: Conceptual Framework

Curriculum Overview:
• Review of project-specific rules and configuration parameters
• Introduction to AGENTS.md standards and persistent memory protocols
• Operational scope of personalization mechanisms
• Best practices for configuring AI assistant behaviors
• Overview of advanced implementation strategies

Module 8 | Safeguards, Risk Assessment, and Professional Judgment

Curriculum Overview:
• Review and validation protocols for AI-generated code
• Identification of common failure modes and technical limitations
• Recognition of prompt injection vulnerabilities and security implications
• Criteria for determining tasks suitable for automation
• Application of professional judgment and maintenance of accountability in software engineering for government

Requirements

Participation requires no previous experience with programming languages or artificial intelligence applications. However, a foundational understanding of code structures or Git version control systems is advantageous to facilitate optimal engagement. Attendees must maintain an active, licensed subscription to supported AI-assisted development platforms, such as Claude Code, Cursor, or GitHub Copilot. The curriculum is specifically designed for government professionals seeking to integrate intelligent automation into their workflows. This instruction targets individuals with no prior development background, including non-coders, intermittent developers, and technical-adjacent staff in quality assurance, data analysis, product management, and operations roles.
 14 Hours

Number of participants


Price per participant

Testimonials (2)

Upcoming Courses

Related Categories