I recently built a tile map of land use in Flanders, inspired by Bloomberg’s 2018 US land use graphic. Flanders is rendered as a grid of equal-area 2 km squares, each colored by its dominant land-use class, and scrolling through the page morphs the map into a waffle chart where block sizes match the true area of every class. A second view steps through 2013, 2016, 2022 and 2025 so you can watch the land change over twelve years. [read more]

I ran Qwen3.5-9B, a 4-bit quantized model, locally on my MacBook Pro M4 Pro with 24 GB of RAM, pointed a terminal coding agent at it, and asked it to build a checkout page with the Stripe API. It did. No cloud, no API calls to OpenAI, no token costs. Just a model running on my laptop. Here’s how. Qwen 3.5 Qwen3.5 is Alibaba’s latest open-weight language model family. The 9B variant sits in a sweet spot: large enough to be genuinely useful for coding tasks, small enough to run on consumer hardware once quantized. It supports a 256K token context window and performs competitively with much larger models on coding benchmarks. [read more]

What if you could search for salaries not by exact keywords, but by describing a job in natural language? “Senior developer in Brussels with a company car” or “nurse working in Antwerp” — and get relevant results based on semantic similarity rather than string matching. This is exactly what I built with BeSalary: an AI-powered salary search engine that extracts structured data from Reddit posts using local LLMs and enables semantic search through vector embeddings. You can try it live at besalary-wine.vercel.app. [read more]

On http://www.brussel.be/webcam-grote-markt you can find a webcam stream of the Grand Place in Brussels. When I saw this I was wondering if I could build a model to trace individual people and eventually track their behaviour while walking on one of the most touristy spots in Brussels. I set up a website with TensorFlow.js using the coco-ssd model but was slightly dissapointed with the results. After doing some more research I read about transfer learning and decided to try and improve model. [read more]

During last summer I was looking for inspiration to do a long term mountain biking trip that would be challenging but pretty risk free at the same time. I had a time frame of three weeks in November so I started to look into possibilities when quickly my eye fell on a flight to Kathmandu. Nepal ticked off all the boxes I was looking for in my next trip, so without too much overthinking slightly nervous I booked the flights. [read more]