AI / LLM
Prompt Engineering
Prompt engineering is part of how I make AI features useful in real workflows, with attention to structure, reliability, and user intent.
Category
AI / LLM
Proof
3 applied examples
Related roles
0 resume items
Related projects
0 linked projects
How I use it
I treat prompts as part of product design. The prompt matters, but so do the surrounding inputs, constraints, and the UI decisions that shape how the result is used.
That keeps the work grounded in outcomes instead of obsessing over prompt phrasing in isolation.
Where I have applied it
This shows up in AI-enabled product workflows where the feature needs to be understandable, repeatable enough, and worth keeping in the product.
Why it matters
The useful version of prompt engineering is workflow design. It helps convert model capability into something people can trust and actually use.
Proof points
- Applied in AI-enabled SaaS work rather than isolated demos.
- Focused on making model behavior serve a product workflow clearly.
- Used alongside interface and system design, not as a standalone gimmick.
Related skills
Agentic Workflows
Agentic workflows are how I turn model capability into usable systems with clear steps, reliable context, and product value beyond a single prompt.
API Design
API design is where I connect product behavior to durable system boundaries, so frontend needs and backend capabilities stay aligned.