Prime Radiant

Cross-era prediction simulator

Prime Radiant

Most public reasoning about the long-term future fails for the same reason: it tries to forecast events without first modeling the machinery that produces events. Prime Radiant is an attempt to build that capacity — a retrieval-augmented reasoning stack over a hand-curated catalog of civilizational machines, capable of predicting which new institutions will emerge from the current substrate.

The system learns the Modernity Machine’s transition into the Divergence Machine, then applies that pattern forward: given the DM machines in Day now, what Liveness Machine forms should we expect in Dawn?

Cards on main
182 / ~360
Status
Phase 1
Era span
MM → DM → LM
Method
RAG + primitives

The operational frame

Three world-machine eras

Civilizational machinery clusters into three overlapping operational logics, each running its own Dawn → Day → Dusk lifecycle. In 2026 all three are simultaneously active.

MM

Modernity Machine

~1200–2150

Currently Dusk

Legibility, fiat progress, narrative coherence, bureaucratic states, mass institutions. The dominant logic of the last several centuries — still operational but losing the conditions that originally made it work.

Nation-state Joint-stock company Central bank Mass university Broadcast media
DM

Divergence Machine

~1650–2400

Currently Day

Pluralism, push, distributed information, post-narrative coordination, network-effect capture. Fully turned on as of roughly 2015 — the platform era, the open-source era, the surveillance-capital era.

Platform corporation Cloud infrastructure Open-source ecosystem Decentralized identity Stablecoin
LM

Liveness Machine

~2000–2300 (speculative)

Currently Dawn

Self-organized criticality, recovered embodiment, generative cohabitation with AI, post-capture coordination forms. Barely visible, mostly extrapolated — the class of institutions the substrate is reorganizing to produce.

Rewilding networks Community land trusts Bioregional cooperatives P2P energy grids Decentralized science

System architecture

How it works

A retrieval-augmented reasoning stack: research findings pin the schema; Sonnet generates Machine Cards; DuckDB + VSS stores and indexes them; HippoRAG-lite retrieves relevant subgraphs; Gemma 3 4B reasons inline with typed primitive tokens.

Phase −1 Research Waves 23 findings · 10 waves Phase 0 Schema v0.1 50+ fields · Pydantic Phase 1 ~360 Machine Cards 182 on main · in progress Phase 2 DuckDB + VSS 3 HNSW indices · semantic/state/graph Phase 3 HippoRAG-lite Vector seed → PageRank expand Phase 4 Gemma 3 4B Primitive grammar · autoresearch Phase 5 Cross-era smoke test MM→DM hindcast · DM→LM predict pins schema Sonnet API YAML → DB embeds retrieves validates EMBEDDING SPACES (Phase 2) semantic_emb (768d) — embeddinggemma-300M over description text state_emb (~50d) — deterministic: normalized state variables + era/phase one-hot graph_emb (~64d) — node2vec over the coupling graph
The Prime Radiant pipeline: background research pins the schema; Sonnet generates Machine Cards at scale; DuckDB + VSS stores cards with three HNSW indices; HippoRAG-lite retrieves relevant subgraphs per query; Gemma 3 4B reasons over retrieved context using inline primitive tokens; Phase 5 validates cross-era prediction performance.

Conceptual core

Thinking with Machine Primitives

Analogous to how visual reasoning models cite spatial bounding boxes inline while processing images, Prime Radiant’s reasoning model cites civilizational machines inline while it reasons. Seven typed primitive tokens define the grammar.

Token Purpose Example
<|machine|> Cite an existing machine card <|machine|>JSC-MERCANTILE<|/machine|>
<|coupling|> Assert a relation between two machines <|coupling|>VOC→DUTCH-STATE:supplies<|/coupling|>
<|signal|> Cite a measurable trace from a machine <|signal|>opp_strength@AWS:0.82@2024<|/signal|>
<|stress|> Name a pressure on a machine <|stress|>multicloud_threat@AWS<|/stress|>
<|transition|> Assert a regime change between machines <|transition|>MM-DAY→MM-DUSK@2000<|/transition|>
<|trace|> Assert a phase / cross-era trajectory <|trace|>JSC:mm-day@1700→mm-dusk@1850→..<|/trace|>
<|new_machine|> Propose a machine stub not yet in the graph <|new_machine|>{...JSON stub...}<|/new_machine|>

Project phases

Build plan

Six sequential phases, gated on artifact quality. Phases −1 and 0 are complete. Phase 1 is in progress at 182 cards.

Phase −1

Research

Ten background research waves across ontology, causal substrates, cyclical dynamics, world-systems, network theory, and the machine atlas. 23 findings merged into a consolidated synthesis.

Done

Phase 0

Schema

Machine Card schema v0.1: 50+ fields, closed enums, phase-snapshot trajectories, lineage links, cross-era coupling typology. Three hand-authored reference cards validated every field.

Done

Phase 1

Machine Cards

Hand-curated corpus of ~360 civilizational machine classes, spanning MM, DM, and LM eras with phase-snapshot trajectories and cross-era couplings. 182 cards on main; Batches 1 and 2 complete.

In progress — 182 / 360

Phase 2

Storage & Indexing

DuckDB + VSS with three HNSW indices over multi-view embeddings: semantic (768d), state (~50d), graph (~64d). Enables blended and staged retrieval modes.

Not started

Phase 3

Retrieval

HippoRAG-lite: vector seed over the three embedding spaces, expanded via PageRank over the NetworkX coupling graph. Different retrieval modes suit different prediction tasks.

Not started

Phase 4

Reasoning

Gemma 3 4B with the seven-token primitive grammar. Autoresearch loop (prompt-variant search, Opus judge) optimizes against four prediction tasks: generate stubs, score plausibility, classify era, predict transition timing.

Not started

Phase 5

Validation

Cross-era smoke tests: predict LM-Dawn stubs from DM-Day input sets; classify 10 cards on the live/zombie/ghost/necromancy spectrum; run a Calvino-layer narrative constrained by the retrieved subgraph.

Not started

What is a Machine Card?

Two examples from the corpus

Each card is a class description of a civilizational machine — not an instance ("the VOC") but a type ("the joint-stock company"). Cards carry phase-snapshot trajectories, typed state variables, cross-era coupling declarations, and per-field provenance flags.

MM Dawn CANON

Amsterdam Bourse (1602)

commerce pace layer · 1602–1795

Class card for the Amsterdam Beurs — the world’s first formal stock exchange, founded concurrently with the VOC charter in 1602. The Beurs provided the secondary market for VOC share-price discovery and transfer, pioneering options, futures, and short-selling within 86 years of founding.

Functional decline commenced after the Glorious Revolution (1688) as London absorbed the Dutch financial circuit. The original Bourse-as-machine ended with the Dutch Republic dissolution in 1795 — the Euronext Amsterdam successor is a distinct DM-Day form.

Key state variables

  • opp_strength: 0.88 (1602–1688)
  • gravitational_weight: 0.80
  • legibility_coverage: 0.65

Key couplings

  • instruments → Joint-stock company
  • chartered_by → Dutch Republic
  • substrate_provision → Stablecoin issuer [EXTRAP]
DM Day CANON

AWS Cloud Infrastructure (2006)

infrastructure pace layer · 2006–ongoing

Class card for Amazon Web Services — the dominant pay-as-you-go public cloud platform launched 2006. The machine’s identity grammar is the API surface, not the datacenter. Gravitational weight 0.91: the DM-Day substrate machine for a substantial fraction of digital civilization.

Three sub-phases: DM-Dawn 2006–2010 (S3+EC2 irruption), DM-Day-early 2010–2018 (oligopoly formation), DM-Day-mid 2018–2026 (vertical chip integration + generative-AI explosion). Revenue ~$110B 2024, 35% operating margin.

Key state variables

  • gravitational_weight: 0.91
  • opp_strength: 0.82
  • plasticity_demand: 0.90

Cross-era couplings

  • substrate_provision ← Bell System (MM)
  • substrate_provision ← Electrical grid (MM)
  • zombie_dependency ← New Deal admin state (MM)

Browse all 182 cards →