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Course Outline

Day 1 Agenda Module 1 — Overview of Claude Code and AI-Enhanced Engineering • Comparative analysis of Claude Code against conventional AI utilities • Application of AI agents within software engineering frameworks • Optimization of productivity and operational workflows • Implementation of AI-supported development lifecycles for government operations • Identification of risks, constraints, and requirements for human oversight • Conduct of live technical demonstrations Module 2 — Fundamentals of Prompt Engineering • Structural components of effective prompts • Differentiation between zero-shot and few-shot prompting methods • Techniques for iterative prompt refinement • Principles of prompt chaining • Utilization of structured outputs and data formatting • Procedures for prompt verification and quality assurance Module 3 — Application of Prompts in Software Development • Strategies for code generation and refactoring • AI-supported debugging processes • Automated documentation creation • Assistance with pull request evaluations • Analysis of legacy code systems • Standards for secure and maintainable AI-generated code Module 4 — Application of Prompts in Testing and Quality Assurance • Generation of test cases • Analysis of edge-case scenarios • Design of tests suitable for automation • AI-assisted defect analysis • Creation of Gherkin syntax and test scenarios • Implementation of quality verification workflows Module 5 — Facilitation of Agile Collaboration via Prompting • Development of user stories and acceptance criteria • Refinement of project requirements • Support for Agile communication channels • Preparation of stakeholder summaries • Assistance with retrospective sessions • Preparation for backlog refinement activities Module 6 — Responsible AI Practices, Security, and Verification • Mitigation of hallucinations and associated AI risks • Maintenance of confidentiality through secure prompting protocols • Adherence to AI governance principles within government contexts • Implementation of verification checklists • Awareness and prevention of prompt injection threats • Clarification of human review responsibilities Module 7 — Collaborative Team Prompt Laboratory • Development of reusable team-level prompts • Design of role-specific AI workflows for government applications • Protocols for prompt sharing and peer review • Establishment of an initial Team Prompt Library • Execution of interactive collaborative exercises Day 2 Agenda Module 1 — Advanced Capabilities of Claude Code • Configuration of CLAUDE.md files for persistent project context • Automation of AI-driven workflows • Implementation of best-of-N generation strategies • Creation of reusable AI commands • Techniques for context engineering • Optimization of AI-assisted engineering processes Module 2 — Advanced Prompt Engineering Techniques • Utilization of chain-of-thought prompting methodologies • Application of multimodal prompting • Implementation of constraint-based prompting • Execution of advanced prompt chaining • Management of large-context data sets • Integration of conversational engineering workflows Module 3 — Version Control, Parallel Development, and Multi-Agent Workflows • Strategies for Git integration • Execution of parallel AI development workflows • Use of worktrees and isolation of AI tasks • Orchestration of multi-agent systems • Implementation of human-in-the-loop checkpoint procedures • Management of development conflicts Module 4 — Architecture, Model Context Protocol (MCP), and Advanced DevOps • Introduction to the Model Context Protocol (MCP) • Integration of Claude with external government tools • AI-supported architecture analysis • Maintenance of Architecture Decision Records (ADR) • Troubleshooting CI/CD pipelines using AI assistance • Management of incident postmortems and operational workflows Module 5 — Scalability of Claude Code and Codebase Health • Management of tokens and contextual limits • Development of AI-compatible project structures • Strategies for long-term codebase maintainability • Automation of documentation processes • AI scalability strategies for federal IT environments • Establishment of team-wide engineering workflows Module 6 — Capstone: Definition of Claude Code Processes • Design of scalable AI-assisted workflows • Integration of prompts, commands, and context files • Design of team AI processes for government entities • Development of cross-role collaboration models • Creation of comprehensive workflow blueprints Module 7 — Advanced Team Prompt Laboratory • Development of advanced prompt libraries • Execution of complex role-specific workflows • Validation of prompts in real-world scenarios • Facilitation of cross-team collaboration exercises • Establishment of the second iteration of the Team Prompt Library

Requirements

Day 1: Foundational Concepts

• Introduction to standard software delivery lifecycles
• Overview of development, quality assurance, and agile methodologies
• Access to Claude is recommended to facilitate practical application exercises for government agencies

Day 2: Advanced Technical Competencies

• Prerequisite completion of Day 1 or demonstrated equivalent professional experience
• Prior engagement with Claude Code tools and prompt engineering principles
• Fundamental proficiency in Git version control
• Familiarity with Continuous Integration/Continuous Deployment (CI/CD) frameworks is advised to ensure operational readiness

 14 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Testimonials (1)

how to engage with the Office environment and set up repetitive tasks

Matthew Wallace - Group CBS
Course - Claude AI for Workflow Automation and Productivity

Upcoming Courses

AI-Assisted Software Engineering with Claude Code

2026-09-21 09:30
14 hours
Chattanooga, TN – Regus Tallan Financial Center
$ 2703 (Online)
$ 3903 (Classroom)

AI-Assisted Software Engineering with Claude Code

2026-10-05 09:30
14 hours
Topeka, KS - Omni Circle
$ 2703 (Online)
$ 3903 (Classroom)

AI-Assisted Software Engineering with Claude Code

2026-10-19 09:30
14 hours
Trenton, NJ – Base Camp Trenton
$ 2703 (Online)
$ 3903 (Classroom)

AI-Assisted Software Engineering with Claude Code

2026-11-02 09:30
14 hours
Tucson, AZ - Regus – One South Church Downtown
$ 2703 (Online)
$ 3903 (Classroom)

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