Self-improving Research Compiler

rewrite the following I just dropped off my rent for next month at the office. I created a full post about where I got so far here: https://www.danielkliewer.com/blog/2026-07-14-recursive-research-compiler-knowledge-compiler-sdk I am building a self-improving research compiler system from my blog using this. Think of the problems with RAG, it is compute heavy and non-deterministic with high latency. All things which cost money, time and accuracy. This new method creates a solution which will save people money. It is like this, the big AI companies are trying to make you dependent on API access to run these RAG systems. Corporations are waking up and have started building sovereign systems to stop paying them per token.

:::writing{variant="standard" id="58391"} I just dropped off my rent for next month at the office. I also wrote a full post documenting where I have gotten so far: https://www.danielkliewer.com/blog/2026-07-14-recursive-research-compiler-knowledge-compiler-sdk I am building what I am calling a **self-improving research compiler system** using my blog as the foundation. The idea comes from looking at the limitations of current RAG systems. Traditional RAG is powerful, but it requires expensive computation at runtime, introduces latency, and can be non-deterministic. Every query requires retrieval, context assembly, and reasoning again — which costs money, time, and can impact consistency. The approach I am experimenting with flips this model: instead of repeatedly paying the compute cost at runtime, you compile the knowledge ahead of time into a reusable intelligence layer. This creates the potential for systems that are faster, cheaper, and more predictable. The larger trend is that many companies are realizing they do not want to be permanently dependent on external AI APIs for every interaction. Organizations are beginning to build more sovereign AI systems — owning their models, data, and infrastructure instead of paying per token forever. I see this as the next evolution: moving from runtime intelligence consumption toward compiled intelligence systems. :::