Building an Agentic Researcher at StackOne
How I built an AI agent that finds agentic use-cases and gets better with feedback.
AI Engineering Production ML
Writings
How I Serve My LLM So That My LLM Serves Me
Here is how I optimized the serving of my fine-tuned LLM to efficiently evaluate it on the Tau benchmark.
AI Engineering Production ML LLMs Inference
Principles of Speed: More GPU Memory Utilisation ≠ Better Performance
How to make your GPU utilisation go up by taking your GPU Memory usage How to make your GPU train an LLM fast(er)
AI GPUs
Panic Coding on My Phone in a Lightning Storm
How I spent the last day of my Dubrovnik holiday fixing my broken FPL bot while dodging lightning bolts and BBQ duties.
AI MCP FPL
Building an FPL MCP Server
How I built a Fantasy Premier League MCP Server to automate my terrible FPL career.
AI MCP FPL
Building an Eval-Driven AI Feature at StackOne
How I built an AI agent that translates provider errors into clear resolution steps, starting with evals from day one.
AI Engineering Evals Production ML
Time-Series Training Partitions
The training partition is a crucial component of an evaluation. It is used to assess generalisation performance on unseen data and ensure that the model is not overfitting to the training data. Here is a (probably) new way of partitioning time-series data for training and testing.
Evals Time-Series ML