Level 1 — U-ASDLC Associate Certification
Certified U-ASDLC Associate (CUA)
About this course
This level moves from understanding → guided application.
Intended audience
Junior Developers, Analysts, QA, Scrum Team Members
What you'll learn
- Apply Agile SDLC phases using human + AI agent collaboration
- Work with defined agent roles(Planner, Builder, Tester, Reviewer, etc.)
- Translate requirements into agent- ready tasks and prompts
- Understand Scrum, Kanban, and hybrid flows in AI - enabled teams
- Execute within guardrails and predefined orchestration patterns
Outcomes
- Operate as a productive team member in AI-augmented projects
- Use AI agents responsibly within an SDLC
- Follow orchestration playbooks and team workflows
- Support delivery without breaking governance or quality controls
Syllabus
Module 2 — Prompt Architecture & Agent Design (Professional Level)
Teach learners to design robust, bounded, and testable agents using architectural principles rather than ad-hoc prompting.
Core outcomes
- Design reusable agent prompt templates
- Apply software design principles to agents
- Prevent prompt drift and hallucination loops
1. Prompt Engineering as Architecture
- Prompts as contracts
- Inputs, outputs, constraints
- Idempotency and repeatability
2. Agent Design Principles
- Single Responsibility Principle for agents
- Explicit scope boundaries
- Stateless vs stateful agents
3. Prompt Patterns
- Chain-of-Thought vs Plan-and-Execute
- Reflection and self-critique loops
- Tool-augmented prompts
4. Error Control
- Guardrails and failure modes
- Retry logic and escalation
- Human-in-the-loop triggers
Assessment
- Prompt design analysis
- Fault-finding exercise
- Agent spec authoring task
Exam & assessment model
Closed-book, scenario-first, audit-ready. Each level is independently certifiable.
Global assessment principles (locked)
- Closed-book exams (except where explicitly stated)
- Scenario-first questions (real SDLC / AI orchestration contexts)
- AI-augmented allowed only where explicitly permitted and evaluated
- Passing requires competence across all dimensions, not just one
- No single assessment decides pass/fail (anti-cramming design)
Assessment pillars
| Pillar | Purpose |
|---|---|
| Knowledge Exam | Verify conceptual & theoretical mastery |
| Scenario Analysis | Test judgment, trade-offs, and decision-making |
| Practical Artifact | Prove ability to build/design/orchestrate |
| Oral / Review Defense | Confirm authorship, reasoning, and clarity |
Level model
Audience: Developers, analysts, QA, product owners
Goal: Safely integrate AI into SDLC workflows
| Component | Weight |
|---|---|
| Written Exam | 30% |
| Scenario Case Study | 30% |
| Practical SDLC Artifact | 40% |
1. Written Exam
- MCQs + short written answers
- Topics: AI-assisted planning; agent boundaries & responsibilities; prompt hygiene; human-in-the-loop controls
2. Case Study
You inherit a team using ChatGPT directly in production commits. Redesign the workflow.
- Single extended scenario
- Evaluates: risk mitigation; SDLC redesign thinking; practical realism
3. Practical Artifact
- Deliverables: backlog (epics → stories); agent role definitions; review checkpoints; failure handling notes
- AI use allowed — must be documented
Certification awarded
U-ASDLC AI-Augmented SDLC Associate
Note
This level certifies operational competence under supervision.