I hope you enjoy the fun. Everyone challenge was cool in its own right, but some were more fun.
I discuss connecting to external LLMs, adaptors, routing & redaction.
For those curious about how this thing actually runs in the real world, we briefly step away from LLMs and…
With this post, we explain how to see inside our LLM discussions, when things go wrong.
Deeper in the machinery - calling tools, and avoiding the apocalypse.
Where Failure Becomes… Well, Mostly More Failure (But Also Progress)
Normalisation is the unglamorous but essential work of turning messy human questions into clean, predictable input that an LLM can…
A side‑project turned laboratory, this chapter dives into how I stopped copy‑pasting my way through AI work and built a…
Part II dives into the messy reality of turning human questions into something an AI can actually understand. It’s where…
This chapter kicks off the real build: turning messy family data into something an AI can reason about without inventing…