I’m actively learning and experimenting with AI-assisted coding and data analysis to accelerate how product ideas move from concept to impact.
This GitHub captures how I’m building capability through training and hands-on practice, using AI and code to improve feedback loops between customer insight, design, and delivery.
- Applying AI-assisted workflows to product discovery and decision-making
- Automating analysis of customer usage and feedback
- Prototyping internal tools and feature ideas to reduce friction and speed up learning
- PowerShell for automation and experimentation
- KQL and Power BI for querying and understanding product data
- Python (early-stage) for analysis and synthesis
- Prompt design for turning raw inputs into insights and design artefacts
The AI shift changes how product teams learn and deliver. I’m deliberately developing hands-on skills to work faster, validate earlier, and increase the leverage of product work.
👉 More context and background on LinkedIn.
As a Product Manager (started as an Engineer) here are some of the languages I developed through in the past and maintain a knowledge in. In the dynamic realm of cloud computing, I am gaining experience in leveraging leading cloud platforms and technologies to architect, deploy, and manage scalable, highly available, and fault-tolerant systems. Delvered through the following frameworks.
