This simulation explores how large language models (LLMs) enhance productivity, clarity, and workflow across professional environments.
To demonstrate the real-world impact of integrating LLMs into common workplace tasks, including:
- Document generation
- Summarization
- Communication support
- Data interpretation
- Knowledge workflows
This project models a side-by-side comparison of human-only versus LLM-assisted workflows to highlight speed, quality, and output differences.
- Python 3.10
- Jupyter Notebooks
- Pandas, NumPy, Matplotlib
- OpenAI API (GPT)
- Comparative timing and output validation methods
- Timed task scenarios with and without LLM assistance
- Qualitative and quantitative productivity metrics
- Clear visualizations of gains in efficiency and consistency
- Custom prompts and evaluation for business relevance
- AI consulting demonstrations
- Internal organizational AI pilot studies
- Workforce augmentation analysis
- Executive decision support for AI adoption
This simulation is part of the broader ANGEL Project, which promotes emotionally intelligent, human-aligned AI systems that increase health, sustainability, and dignity.
“Tools that help people think more clearly and act with less stress are not luxuries — they are survival mechanisms for the species.”
— Robin Macomber