Common Core Cummins

Explain how transformer architecture and attention mechanisms allow large language models to process and generate language.

Write structured prompts using reusable patterns and frameworks to get consistent, high-quality AI output.

Apply responsible AI practices including bias awareness and safety guardrails when using GenAI tools.

Configure Copilot modes, repo-level instructions, and scoped rules to control AI behavior within a codebase.

Resolve conflicts between multiple layered AI instructions using precedence rules.

Use AI agents to review, refactor, and coordinate changes across a codebase, both guided and autonomous.

Write INVEST-compliant user stories and translate them into prompts that scaffold working code.

Build a requirements traceability matrix connecting user stories to code output.

Produce professional project documentation including a README, bug report, and release readiness checklist.

Apply architecture-first thinking to map system flows and convert ideas into structured architectural outputs.

Identify code smells and apply SOLID principles and design patterns to refactor code safely.

Perform change-impact analysis and dependency mapping before modifying a codebase.

Build a regression testing strategy to confirm refactors haven't broken existing functionality.

Complete a capstone lab applying prompting, agents, and refactoring skills to a real codebase, ready to transition into a specialization track.