AI workflow foundations
Use structured prompting, task decomposition, and iterative refinement for daily engineering work.
Training Track 01
AI-Assisted Engineering and Developer Productivity
Enable engineering teams to use AI tools more effectively across coding, testing, documentation, and review workflows while maintaining quality, security, and team standards.
Prompt patterns
Review workflows
Testing support
Safe adoption
Program Overview
What this track covers
This program helps teams adopt AI in a controlled, practical way by connecting tools to real software delivery workflows instead of isolated experimentation.
Team guardrails and safe usage
Define what teams can automate, what needs review, and how to work within security and compliance boundaries.
Code review, tests, and documentation
Apply AI to support reviews, test generation, debugging, refactoring, and technical documentation workflows.
Embedding into the delivery lifecycle
Align AI usage with pull requests, engineering standards, retrospectives, and team operating rhythms.
Business Outcomes
What teams should gain from this program
Safer AI adoption
Teams understand where AI adds value and where stronger review or restriction is required.
Better engineering leverage
Developers use AI more effectively for routine tasks without lowering code quality expectations.
Shared operating model
Leads and contributors align on team-level guidance for prompts, review, testing, and collaboration.