← Selected work

Product & data case study

GiftPot

A live consumer product used as a practical laboratory for AI-assisted execution, structured data and payment operations.

Visit the live product ↗

01 · Why it matters here

Product building as evidence of ownership, not a career change.

GiftPot is included in this portfolio because building and operating a live product has strengthened how I think about data, ambiguity, controls, edge cases and the relationship between a commercial decision and the systems that have to support it.

I use AI-assisted development to extend my technical capability while remaining responsible for the product logic, testing, production behaviour and decisions about what should happen when something does not reconcile cleanly.

02 · Data & payments

Working with production data makes abstract technical concepts concrete.

The product uses relational data alongside payment workflows. That has required practical work with tables, structured queries, transaction states, reconciliation logic and production troubleshooting.

My SQL positioning is intentionally pragmatic: I work with SQL-based relational systems and use AI-assisted querying where useful to answer product questions, diagnose issues and validate outputs. I do not position myself as a database engineer or advanced SQL specialist.

03 · What it demonstrates

01Structured problem solving

Breaking product and payment problems into states, dependencies and validation checks.

02Data confidence

Working directly with relational production data rather than relying only on pre-built reports.

03AI as a technical multiplier

Using AI to extend implementation capability while retaining judgement and ownership.

04High ownership

Testing, debugging and operating a live product where edge cases have real consequences.