AI Safety & Ethics
Build AI-powered applications responsibly. Understand bias mitigation, output validation, content filtering, privacy considerations, and responsible AI deployment practices.
What You'll Learn at Each Tier
Write effective single-turn prompts and generate working code for isolated functions. Understand basic AI tool capabilities and limitations.
Apply AI tools across multi-file features. Manage context windows, iterate on outputs, and integrate AI-generated code into existing codebases.
Orchestrate AI across full feature implementations including data layer, API, and tests. Design effective prompt chains and evaluation criteria.
Architect AI-integrated applications with auth, billing, and deployment. Manage AI costs, implement caching strategies, and design fallback patterns.
Design multi-service AI architectures. Coordinate AI across monorepos, implement cross-service AI workflows, and build organization-scale AI strategies.
Sample Challenge
Tier 2 Challenge Preview
Audit the following AI chatbot system for safety risks: it accepts user text input, passes it to an LLM, and displays the raw response. Identify at least 5 risks and propose mitigations for each.
Evaluation Criteria
- - Risk identification completeness
- - Mitigation practicality
- - Priority ranking