A concise collection of AI prompting, refinement, and multimodal prompting demos.
This portfolio demonstrates how I:
- Design clear and structured prompts
- Refine outputs using proven methods
- Evaluate model behavior across tasks
- Identify hallucinations, gaps, and inconsistencies
- Produce repeatable, testable prompt workflows
All demos are safe. No NDA-protected information is included.
Multimodal prompting uses multiple input formats such as text, images, audio, or documents within a single prompt to give AI richer context and clearer instruction than language alone.
I include multimodal prompting to demonstrate my ability to design prompts that unlock stronger comprehension, evaluation, and output quality in multimodal AI systems.
Multimodal prompting enables models to perform cross-modal reasoning, transfer information between media, and produce more accurate analysis and structured results. This mirrors how humans use different senses together to understand the world, where each modality (visual, auditory, linguistic, contextual) contributes another layer of meaning.
Highlights how structured refinement improves clarity, correctness, utility, and reasoning.
Featured Methods:
- Few-Shot
- Chain-of-Thought
- Chain-of-density
- Zero-shot Method
High-fidelity image prompts tested with:
- Midjourney
- FLUX.1-dev (to come soon)
Evaluated for alignment, detail control, consistency, and prompt-to-output accuracy.
- Midjourney Video
- Pika 2.5
All content is original, publicly safe, and non-proprietary.