B-Trees or LSM-Trees: Your Database Already Chose
Every database picks a side in the same trade — quick to write, or quick to read. Almost every performance surprise you have had follows from which side it picked.
11 pieces on the systems I build, the models I break and the way I learn. Newest first is rarely the best order — start from a tag.
Every database picks a side in the same trade — quick to write, or quick to read. Almost every performance surprise you have had follows from which side it picked.
A phone is a copy of your data that vanishes without warning, holds changes for hours, and comes back disagreeing with everyone else. Most mobile bugs are really that problem, unlabelled.
Picking MongoDB takes five minutes. Deciding what one record should contain takes months to get wrong and is painful to undo.
Trying again after a failure is the most obvious safety net there is, and the easiest one to build backwards. It hinges on one question: did the first attempt actually fail?
The Model Context Protocol looks like a way to hand an AI some plugins. Treat it that way and you get tools that shine in a demo and go round in circles in real use.
Getting an AI running on your own laptop takes four minutes. Everything that makes it actually usable afterwards is queueing, memory and patience — plain old engineering.
Anyone can copy your prompts in a weekend. Nobody can copy the thing that tells you, precisely, whether your last change made the product better.
When an AI answers badly from your own documents, everyone blames the search. In every system I have debugged, the search was fine. The documents were the problem.
A tiny AI running on my laptop beats a giant one at a single job. That sounds like a story about size. It is really a story about picking a small enough job.
Anthropic found a small, editable workspace inside Claude that carries silent intermediate thoughts. Here is what the J-lens reveals, why it matters, and what it does not prove.
A clear first-principles guide to KV cache: why it exists, how it works, and what tradeoffs matter in real production systems.
What I read, built and got wrong.