Jani Tulonen

Designed and iterated prompt systems across ChatGPT, Claude, and Gemini for creative, analytical, and technical use cases. Developed advanced generative image workflows with measurable improvements in output quality and creative control. Produced commercial-ready graphic designs (t-shirts, book covers) using AI-assisted tools. Active contributor on AI training/annotation platforms including Outlier AI and Aligner. Continuously studied prompt engineering theory, LLM behavior, and AI training methodologies. Pursuing Google Prompt Engineering Essentials certification to formalise expertise.

30+ years delivering technical installations, fault diagnosis, and system maintenance in demanding environments. Developed deep systematic thinking and safety-first problem-solving; managed complex multi-variable troubleshooting; built strong documentation and process habits critical for AI training data quality and workflow optimization.

Forty years of active music practice — composing, arranging, and producing music. This practice informs understanding of generative AI outputs and fosters pattern recognition, iterative refinement, and structured creativity.