Audience
Research managers, lab scouts, AI operations teams
Chris Royse field notes
A 106-Page Paper In Six Hours Is A Workflow Claim
The interesting part is not speed by itself. It is decomposition, source control, synthesis, review, and evidence capture.
Agents / Channel video / 3:45
Core idea
Multi-agent research only matters if the final artifact has traceable sources, named uncertainties, and a reviewable structure.
Research Production
Watch on YouTube· 3:45
A 106-Page Paper In Six Hours Is A Workflow Claim
This supports the personal-brand story: Chris builds unusual research workflows and then turns them into artifacts.
Watch videoOpen the full video on YouTubeWhat to take from it
The videos are raw build context. These notes translate them into the shortest useful frame for creators, companies, and AI lab readers.
Parallelism does not replace synthesis.
The paper is only useful if the claims survive review.
A fast workflow should still leave receipts.
Continue this thread.
Related notes stay inside the same problem area first, then move to the next useful context.
Watch + read / 21:21
Context Engineering Starts With The Desired Output
Define the current state, define the target state, use memory to strengthen the path, then verify the connection.
Watch + read / 14:54
Stop Dumping Every Corpus Into One RAG Database
The swappable-brain pattern: isolated databases, provenance, cross-database search, and cleaner context for high-stakes work.
Watch + read / 14:41
Multi-Agent Search For Hard Research Questions
A multi-agent search workflow can explore large question spaces, collect evidence, and build research artifacts faster.
Make it concrete.
Send the audience, data type, target task, proof bar, and sharing limits.