Cognitive and Soft Skills Development

This topic develops the capacity to learn from feedback, which is fundamental to skill development in prompt engineering. It covers different feedback sources including quantitative metrics (accuracy, speed, cost), qualitative user feedback (satisfaction, ease of use), and expert feedback (colleagues, advisors). Learners practice extracting actionable insights from feedback that sometimes...

This topic develops the capacity to learn from feedback, which is fundamental to skill development in prompt engineering. It covers different feedback sources including quantitative metrics (accuracy, speed, cost), qualitative user feedback (satisfaction, ease of use), and expert feedback (colleagues, advisors). Learners practice extracting actionable insights from feedback that sometimes conflicts or is ambiguous. The topic addresses emotional responses to feedback, particularly negative feedback, and how to manage defensiveness while remaining open to improvement. Learners develop habits of iterative experimentation and refinement, where each cycle of implementation, measurement, and feedback builds toward better solutions. The topic emphasizes the distinction between responding to feedback (making ad-hoc changes) and learning from feedback (understanding underlying principles). Learners also learn to solicit specific feedback that helps them improve, asking for concrete suggestions rather than vague praise or criticism. Finally, the topic covers feedback loops that encourage reflection on what worked and why, building mental models of cause and effect that improve judgment over time.

This topic develops critical thinking as applied to prompt engineering challenges. It covers problem analysis frameworks including problem statement clarification (what exactly needs to be solved?), constraint identification (what are the limitations?), and stakeholder analysis (who needs what and why?). Learners practice decomposing ill-defined problems into concrete, tractable subtasks suitable...

This topic develops critical thinking as applied to prompt engineering challenges. It covers problem analysis frameworks including problem statement clarification (what exactly needs to be solved?), constraint identification (what are the limitations?), and stakeholder analysis (who needs what and why?). Learners practice decomposing ill-defined problems into concrete, tractable subtasks suitable for prompting. The topic also covers assumption testing, where learners explicitly identify assumptions about model capabilities, data characteristics, and success criteria, then test them empirically. Reasoning about tradeoffs is emphasized, such as deciding between accuracy and speed, between generalization and specialization, or between simplicity and sophistication. The topic introduces logical fallacies and biases that can mislead prompt engineers, such as confirmation bias (seeking only evidence confirming pre-existing beliefs) and availability bias (over-weighting easily recalled examples). Learners practice asking productive questions like "What would disprove this approach?" and "What am I assuming without evidence?"

This topic cultivates creative thinking as a skill distinct from technical knowledge. It covers divergent thinking exercises where the goal is to generate many possible solutions without immediately judging them, which can overcome the tendency to default to familiar approaches. Learners practice techniques such as analogy mapping (how do solutions...

This topic cultivates creative thinking as a skill distinct from technical knowledge. It covers divergent thinking exercises where the goal is to generate many possible solutions without immediately judging them, which can overcome the tendency to default to familiar approaches. Learners practice techniques such as analogy mapping (how do solutions in other fields address similar problems?), constraint relaxation (what if we removed this limitation?), and combination of existing ideas in novel ways. The topic addresses how creative thinking and critical thinking interact, with critical thinking evaluating ideas and creative thinking generating them. Learners examine how prompting itself can be creative, such as using metaphors or role-playing to unlock novel approaches in LLMs. The topic also covers conditions that enhance or inhibit creativity, including psychological safety, openness to failure, and time for incubation and reflection. Learners practice moving from novel ideas to implementable approaches, recognizing that creativity without execution is merely daydreaming.

This topic develops communication competencies essential for prompt engineers working in teams and organizations. It covers explaining technical concepts in accessible language, using examples and analogies to build understanding, and tailoring explanations to audience knowledge levels. Learners practice writing prompts that are clear and unambiguous, recognizing that clarity in prompt...

This topic develops communication competencies essential for prompt engineers working in teams and organizations. It covers explaining technical concepts in accessible language, using examples and analogies to build understanding, and tailoring explanations to audience knowledge levels. Learners practice writing prompts that are clear and unambiguous, recognizing that clarity in prompt design directly translates to LLM performance. The topic also covers storytelling and narrative frameworks that make technical information memorable and compelling. Learners examine how to give and receive feedback effectively, asking clarifying questions, and offering constructive suggestions. The topic addresses documentation communication, creating written materials that are useful to current and future readers. Learners also practice communication in cross-functional settings where they may need to translate between technical and business perspectives, such as explaining why a prompt enhancement improves user satisfaction or reduces costs.

This topic addresses the reality that prompt engineering is a rapidly changing field where models improve, new techniques emerge, and understanding of how to prompt effectively deepens frequently. Learners develop habits of continuous learning including regular engagement with research and practitioner communities, experimentation with new approaches, and reflection on successes...

This topic addresses the reality that prompt engineering is a rapidly changing field where models improve, new techniques emerge, and understanding of how to prompt effectively deepens frequently. Learners develop habits of continuous learning including regular engagement with research and practitioner communities, experimentation with new approaches, and reflection on successes and failures. The topic covers metacognition—thinking about thinking—and how to evaluate one's own understanding and identify knowledge gaps. Learners practice growth mindset, viewing challenges as opportunities to develop rather than threats to avoid. The topic also addresses change resistance and how to navigate the emotional aspects of rapid evolution, including the feeling of obsolescence when new approaches supersede previously learned techniques. Learners develop learning goals, such as understanding each new model release or trying one new prompting technique monthly. The topic emphasizes that adaptability is not only about acquiring new knowledge but about maintaining sufficient flexibility in worldview to appreciate perspectives different from one's own and to change course when evidence warrants.

This topic acknowledges that prompt engineering increasingly occurs in teams rather than isolation. It covers collaborative workflows where prompt engineers share work, review each other's designs, and iterate together on shared problems. Learners practice pair prompting (two engineers working on the same prompt) for complex challenges or learning opportunities. The...

This topic acknowledges that prompt engineering increasingly occurs in teams rather than isolation. It covers collaborative workflows where prompt engineers share work, review each other's designs, and iterate together on shared problems. Learners practice pair prompting (two engineers working on the same prompt) for complex challenges or learning opportunities. The topic addresses how to document prompts and designs in ways that enable others to understand and build upon them, and how to provide feedback that is constructive rather than critical. Learners examine diverse team compositions including prompt engineers with different specialties (domain experts, system designers, evaluators) and cross-functional teams including engineers, designers, and product managers. The topic covers how to manage disagreement productively, recognizing that different approaches may each have merit depending on context. Finally, the topic addresses knowledge transfer practices such as mentorship, brown-bag sessions where team members share learnings, and captured case studies of successful and failed approaches.