Show HN: Skill capsules" for LLMs, a "poor man's continual learning""Continual learning" is considered one of the "blockers" for LLMs: they can't learn on the job, don't improve over time, etc. In particular, Dwarkesh Patel describes it as a number of problem which has to be solved to get to AGI.Many academic article propose some kind of a memory system for LLM which might be considered a form of "continual learning". But most evals focus on memorizing facts which is just not very useful (it's better to fetch facts via tool use than to store it in neural memory) and these proposals might not fit well into common LLM API use patterns.In this article I'm proposing a "new" method called "skill capsules" which is highly pragmatic, easy to understand and evaluate and might integrate well into existing tooling.Skill capsule is a concrete object - it's a bunch of vectors, basically. You can insert it somewhere into a middle of LLM context and it improves performance on a particular skill, e.g. get tool calls more reliable, use particular writing style, coding