Economics graduate. Chef. I have spent years working with data and working in kitchens. Both taught me to think in systems. Now I am building AI tools to solve a problem I actually lived.
Two things most AI builders do not have. Real kitchen experience and an Economics degree. I am using both.
Eating well on a tight budget is genuinely hard. As a recent graduate working kitchen shifts, I know exactly what it feels like to open the fridge at the end of the week with barely anything left and no idea what to cook. I am building AI systems to solve that, for me and for everyone in the same position.
BSc Economics, University of Leicester (2:1). Modules in Econometrics, Applied Econometrics, Business Data Science and International Finance. I have built time series models to forecast GDP trends, run R-based simulations testing autocorrelation effects, and presented data-driven recommendations to stakeholders in a business consulting competition.
Currently working at The Cricketer's Arms. I lead services, control stock, reduce waste and train new team members in a fast-paced kitchen. Kitchens run on systems and I have been building and following them under pressure every shift. Peel everything first, then chop. Prep in batches. Every step has an order designed to remove wasted effort. That instinct for process carries directly into how I build AI automation.
Each one built to solve a real part of the budget eating problem. All free tools. All documented publicly.
Input your budget, days, dietary requirements and nearest supermarket. Get a full personalised meal plan with costs, calories, protein and cooking instructions, emailed to you automatically.
Upload a photo of your fridge. AI identifies what you have and generates recipes using only those ingredients. No food waste. No unnecessary shopping.
Log every meal automatically. Track calories, protein, carbs and cost per meal over time. All data flows into Google Sheets with no manual entry required.
An Economics-led cost per serving model built in R. Models real food costs across common meals, budget ranges and supermarkets. This is where the degree earns its place.
The advice was simple. Learn the tools, solve a real problem, post what you build. That is exactly what I am doing.
Not a hypothetical. Not a tutorial project. Something I actually lived and wanted solved. Budget eating as a graduate working shifts was that problem.
Not a plan. Not a deck. A working thing that actually does something useful. System 1 went from idea to working email automation in two days.
Every system, every hour, every mistake goes on LinkedIn and GitHub. The build log is the portfolio. The work speaks for itself.
Data analysis, cost modelling and structured thinking are things most AI builders skip. I am bringing them in from day one, especially in System 4 where I model real food costs in R.
No paid tools. No prior experience with most of these. Just figuring it out and building anyway.
I am posting every system, every mistake and everything I learn publicly on LinkedIn. Come follow along.