Production-Oriented AI Engineering

Add evaluation, failure handling, and operational documentation to an AI feature intended for real use.

Problem statement · Illustrative

An AI feature that already works in a demo needs evaluation, failure handling, and operational documentation before it can be treated as more than a prototype.

Primary user workflow · Illustrative

Accept input → run the AI path → apply evaluation or guardrails → return result or fallback → record operational notes.

Functional scope · Illustrative

Evaluation criteria, security and data-handling notes, failure modes, tests for AI workflows, and deployment/ops documentation.

Technical components · Illustrative

Existing or sample AI feature, evaluation cases, fallback path, logging, and ops notes.

Data requirements · Illustrative

Non-production sample data. Sensitive data handling rules must be written even when using synthetic inputs.

Testing expectations · Illustrative

Success case, unsupported or unsafe input case, dependency failure fallback, and documented evaluation results.

Known limitations · Illustrative

Does not grant access to Vasiva client systems. Does not certify production compliance for regulated domains.

What counts as completion · Illustrative

Evaluation suite, failure handling, security/ops notes, and a demonstration of reliability trade-offs.

Example or assigned project work—not a published student achievement or employment guarantee. Student work is not assumed for commercial use without appropriate agreements. Sections marked illustrative are representative examples, not a fixed commercial brief.