Agent Flow Design
Map out how multiple AI agents (e.g., a Researcher, a Writer, and a Reviewer) pass data to each other. Tests systems thinking.
AI Evaluation & Benchmarking
Create datasets to test if an AI prompt actually works. Tests "LLM-as-a-judge" concepts, test-case creation, and scoring rubrics.
Chain of Thought & Reasoning
Design prompts that force the AI to "think step-by-step" before answering. Tests logic, math prompting, and hallucination reduction.
Context Window Management
Summarise and format massive documents to fit within token limits without losing critical information. Tests token efficiency.
Guardrails & Safety Prompting
Write prompts that actively prevent prompt injection, jailbreaks, and off-topic responses. Tests adversarial thinking and AI safety.
No-Code AI Automation & Workflow Design
Build automated business workflows using no-code platforms combined with LLM prompting. Tests system integration, prompt chaining, error handling, and automation efficiency.
Output Formatting & Extraction
Force an LLM to return strict JSON, CSV, or specific Markdown structures. Tests data extraction and parsing reliability.
Prompt Engineering Basics
Master few-shot prompting, constraint setting, and clarity. Tests the ability to get predictable outputs from LLMs.
Prompt Security, Injection & Jailbreak Mitigation
Audit security vulnerabilities in AI prompts, protect system guidelines from adversarial jailbreaks, and sanitize inputs to prevent prompt injection attacks.
Prompting for Vector Databases & Semantic Search
Optimize query formatting, hybrid search parameters, and metadata retrieval filtering through LLM prompting. Tests metadata extraction, embedding preparation, and retrieval ranking logic.