Research Direction Evolution

Have I been more busy this past week, I wonder what I have done this past week, I think my blog has had a lot of updates as well

Based on what we've talked about over the past week, yes—you've been unusually productive. A lot of your effort has been focused around converging on a single research direction rather than jumping between unrelated ideas. Here's a rough recap. ### Research direction solidified The biggest change is that you seem to have crystallized what you're calling **Compile-Time AI**. Instead of describing it as "better RAG," you've been refining it into something more like: - Move expensive reasoning, retrieval, entity extraction, and synthesis to an offline compilation stage. - Produce a compiled intermediate representation of knowledge. - Serve answers from that compiled artifact with very low latency. - Treat runtime inference almost like reading from a precomputed executable instead of rebuilding context every request. That idea became the central theme across multiple conversations. --- ### Recursive Research Compiler You also expanded that into what you're calling the **Recursive Research Compiler**. The idea evolved from: > compile one corpus to > compile research that improves the compiler itself. The workflow became something like: ``` Research ↓ Knowledge Compiler ↓ Blog post ↓ New code ↓ Improved compiler ↓ More research ``` You started framing it as a self-improving research system rather than just another RAG pipeline. --- ### Knowledge Compiler SDK You also published work around your SDK and discussed using it as the foundation for this recursive system. The idea shifted toward: - blog posts as source code - repositories as knowledge - generated heuristics - generated reasoning traces - compiled knowledge artifacts instead of raw embeddings alone. --- ### Hermes automation A major planning effort was designing Hermes prompts. Rather than asking Hermes to write one project, you wanted it to: - ingest your existing blog - ingest the Knowledge Compiler SDK - discover missing capabilities - create an entirely new project directory - continually improve itself - generate new research articles - implement new code - cite repositories - build toward a self-improving research agent That's a substantial shift from using an LLM as a coding assistant to using it as a long-running autonomous researcher. --- ### Website improvements You also spent quite a bit of time on your website. Things you worked on included: - publishing multiple new research posts - debugging sitemap generation - Google Search Console verification - domain ownership verification - checking deployment - making sure static exports were correct - monitoring Google traffic You were also watching search indexing and organic traffic. --- ### Writing You rewrote the Compile-Time AI concept several times for different audiences: - email - LinkedIn - podcast outreach - technical explanations - blog copy Each revision got a little sharper. --- ### Core realization One interesting evolution I noticed is that your framing changed. Earlier it sounded like: > "Compile-Time AI is a replacement for RAG." Now it sounds closer to: > "Compile-Time AI is a software architecture where reasoning is treated like compilation." That's a broader claim, and it's much easier for people to understand because it borrows familiar ideas from compilers. --- ### Overall Compared to many previous weeks, this one seems unusually focused. Instead of exploring many unrelated AI ideas, most of your work reinforced the same central thesis: - publishing blog posts - refining the Compile-Time AI concept - building the Recursive Research Compiler - evolving the Knowledge Compiler SDK - designing self-improving Hermes workflows - improving your website's SEO and indexing - preparing outreach content for a wider audience It looks less like a collection of experiments and more like the early stages of a coherent research program centered on compile-time knowledge systems. That kind of focus tends to make subsequent work compound, because each blog post, code change, and prompt builds on the same underlying architecture rather than starting from scratch.