TrajectoryOS and RAG++
TrajectoryOS and RAG++ move the trajectory thesis into personal knowledge and life-state modeling. Instead of retrieving similar documents, RAG++ retrieves prior successful transitions from comparable state regimes.
Paper workspace
Live draft structure
Artifacts
Research draft source
Mapped as a privacy-sensitive architecture draft rather than a public manuscript.
source-only
Editable source
Architecture and research drafts exist. Full release requires a privacy pass because the topic touches personal trajectory modeling.
Source anchors
Comp-Core/backend/cc-trajectory/docs/research/trajectory_os_paper.md
Comp-Core/backend/cc-trajectory/docs/research/RAG_PLUS_PLUS_PAPER.md
Comp-Core/backend/cc-trajectory/docs/RESEARCH_PAPER_TOPOLOGICAL_LIFE_MODELING.md
Method tags
Ingest intersections
Status
Architecture and paper drafts exist; public release needs a privacy pass before details are exposed.
Key claims
01
Retrieval can happen in state space, not only semantic space.
02
Personal trajectory modeling must treat self-report as noisy evidence.
03
Privacy review is required before publishing full details.
Public reading note
Summary only; full release requires privacy pass.
Standard skeleton
What this paper must keep proving
problem
Personal planning systems flatten life into tasks and documents instead of modeling state, momentum, friction, and transition history.
method
Model human trajectory as a dynamical system and retrieve prior successful transitions from comparable state regimes.
implementation
cc-trajectory research docs, RAG++ state retrieval, and topological life-modeling drafts.
data
Personal trajectory signals and self-reports are privacy-sensitive; public release should expose theory and synthetic examples first.
evaluation
Transition-prediction quality, retrieval usefulness, privacy safety, and whether embodied signals improve state inference.
references
Dynamical systems, Bayesian state estimation, personal informatics, retrieval-augmented generation.
openQuestions
How to present the theory publicly without exposing personal-state data or overclaiming ground truth.
Checkpoints and references
Proof chain
Claim checkpoint
central-claim slot
Every central claim must point to a proof anchor or remain labeled as speculative.
Implementation checkpoint
implementation-map slot
Every method should identify the code path, harness, schema, or protocol that embodies it.
Evidence checkpoint
evidence-manifest slot
Every reported result should point to run IDs, packet IDs, data snapshots, commits, or review artifacts.
Reference checkpoint
references slot
Every external claim should resolve to a cited paper, benchmark, standard, or documented prior system.
Release checkpoint
release-gate slot
Every PDF needs a named condition before it can move from draft to citation-ready.