research-wiki

Synthesis

The evolving thesis. Current best understanding of the research topic, updated on every ingest. This page sits above the schema.org vocabulary — it is the one bespoke meta-page.

Current thesis

The topic is how machines can help people manage and synthesize the growing record of knowledge — and the recurring bet across 80 years is that the binding constraint is not storage or even reading, but selection, connection, and maintenance.

A clear through-line now runs from 1945 to today:

as-we-may-think (Bush, 1945) diagnosed the problem — the record grows faster than we can consult it, and rigid indexing fights the mind’s natural association — and proposed the memex with associative-trails as the cure.
augmenting-human-intellect (douglas-engelbart, 1962) is the missing middle: it carried the associative-trail vision into interactive computing (the H-LAM/T system, then NLS hypertext, the mouse), reframing the goal as augmenting human intellect and adding the bootstrapping idea — use the tools to improve the tools.
llm-wiki-gist (Karpathy) revives exactly this vision as the llm-wiki pattern, claiming the missing piece Bush/Engelbart lacked — cheap, tireless maintenance — is now supplied by the LLM. Positions itself against retrieval-augmented-generation.
gbrain (garry-tan) is a second, independent, production instantiation of the same idea (146K pages, in daily use), pushing it much further: an autonomous “dream cycle” daemon, a self-wiring knowledge-graph, and hybrid retrieval at scale.

So the modern pattern reads as “the memex, finally maintainable.” The associative trail (Bush) becomes Engelbart’s hypertext link becomes the wikilink / typed graph edge; the microfilm desk becomes a git repo of markdown.

An augment→automate axis. Engelbart framed the goal as augmenting the human (human-in-the-loop, bootstrapping their capability); the modern family runs from that pole (llm-wiki, llm-wiki-agent, human-in-loop) toward automating the work entirely (gbrain‘s unattended daemon). Engelbart’s bootstrapping is also precisely the self-improving-wiki dynamic — using the wiki (and the agent that maintains it) to improve the wiki. compound-engineering (compound-engineering-plugin) is this same bootstrapping idea named and operationalized for software-with-agents — “each unit of work makes the next easier; codify learnings for reuse” — the engineering sibling of the compounding artifact thesis and, notably, the very loop this wiki was built with (brainstorm → spec → plan → execute → compound).

The same compounding-knowledge thesis now appears as enterprise infrastructure: the enterprise-context-layer (Prukalpa/Atlan) argues “the tenth agent is dramatically smarter than the first” on accumulated, governed organizational context (knowledge = semantic map, expertise = playbooks/agent-skills, norms = policy) — i.e. the llm-wiki/gbrain bet scaled to the org, with versioning/observability against knowledge decay made an explicit product requirement (the maintenance discipline this wiki does by hand). So the lineage now spans personal (PKM/llm-wiki), agentic (gbrain, harness self-improvement), and enterprise (context layer) scales of the same idea — an LLM compounding a governed knowledge substrate.

A parallel ancestor: the zettelkasten. niklas-luhmann‘s slip-box (mid-20th c., manual) independently reached Bush’s core insight — connection, not collection; association over rigid categorization — via atomic, explicitly-linked notes with emergent (not hierarchical) structure. Two things make it more than a footnote: (1) it’s a third independent convergence on associative linked knowledge (Bush, Engelbart, Luhmann), reinforcing that this is a real attractor; (2) Luhmann framed the slip-box as a “communication partner” you converse with — the closest historical anticipation of the LLM-as-knowledge-partner behind llm-wiki and gbrain. It’s also the direct forebear of obsidian/Roam. Reflexively, this wiki is itself Zettelkasten-shaped (atomic pages, liberal links, emergent @type categories, synthesis/index as Structure Notes).

The modern tools-for-thought wave. tiddlywiki5 (~2004) is the earliest node — a self-contained personal wiki of atomic “tiddlers” with transclusion, built on an own-your-data, keep-it-forever ethos that directly prefigures the llm-wiki‘s plain-files-you-own model. roam-research (2019) then operationalized the whole lineage for a mass audience — bidirectional double-bracket links that auto-create pages, automatic backlinks with context, and a personal knowledge-graph — seeding obsidian, logseq, and others. logseq is the clearest convergence of the two strands: Roam’s networked-thought UX plus the own-your-plain-files ethos (it stores notes as local Markdown, prioritizing “privacy, longevity, user control”) — which is exactly the llm-wiki‘s substrate choice. The wave’s shared end state is networked notes stored as plain markdown you own — precisely what the LLM wikis build on.

Counterpoint — notion bounds the claim. The mass market’s favorite PKM tool (notion: 20M+ users, $500M+ ARR) went the opposite way — cloud-hosted, proprietary, organized around structured databases rather than associative links, with your data on their servers. So the “plain markdown you own” convergence is real for the local-first / tools-for-thought lineage (what the llm-wiki builds on) but is not the market-dominant choice: most users traded ownership, portability, and linking for convenience, collaboration, and structure. “Own your plain files” is therefore a deliberate value choice, not an inevitability — which is part of why the LLM-wiki pattern picks plain markdown on purpose (portability, no lock-in, legibility to both human and LLM).

The lineage closes on itself — tana. The newest tool in the survey fuses the two poles (networked nodes and structured fields via supertags) and is AI-native: “the AI reads your graph, not a blank document,” using your typed structure as context. That is the llm-wiki / gbrain thesis — an LLM reasoning over your own structured personal knowledge — arriving inside a mainstream PKM tool. So the two big arcs this wiki traced converge: the 80-year tools-for-thought lineage (Bush → Engelbart → Luhmann → TiddlyWiki → Roam/Logseq/Notion) and the LLM-as-knowledge-partner thesis are now the same story. The open frontier is no longer “can we build the memex” but “how autonomous should the maintaining agent be” (the augment→automate axis) and “who owns the substrate” (plain files vs. cloud — the Notion bound). Two details matter for the thesis: (1) Roam’s mechanic (wikilink → auto-page → backlinks) is the llm-wiki‘s linking UX, so the modern LLM wikis inherit their interaction model straight from here; (2) Roam’s “Unlinked References” (surfacing mentions you never linked) is a first step toward automated association — which gbrain/LLM systems complete. The arc: Bush’s manual trails → Engelbart’s hypertext → Luhmann’s slip-box → Roam’s automatic backlinks → the LLM doing the linking and synthesis for you.

A fourth source, llm-wiki-agent, adds a lightweight implementation (a markdown-only coding-agent skill, no API key) — and is a near-twin of this very wiki’s structure and operations.

Two things changed with the third source:

From advocacy to evidence. The thesis no longer rests on one essay — two builders (Karpathy, Tan) independently converged on LLM + persistent markdown brain, one of them running it in production. That’s corroboration, not just a well-argued hypothesis.
A spectrum, not a point. The family spans a maintenance/automation axis: llm-wiki (minimal, human-in-the-loop, index-only, maximally legible) and llm-wiki-agent (lightweight, markdown-only, slightly automated) at one end; gbrain (autonomous daemon, knowledge graph, hybrid search, ~100K pages) at the other. Bush’s “who maintains the trails?” gets a sharper answer at the GBrain end: no one — a cron-driven cycle dedups, re-cites, and finds contradictions while you sleep.
The design is a natural attractor. llm-wiki-agent independently lands on the same structure this wiki uses — raw/→wiki/, index + log + living synthesis, auto entity/concept pages, ingest/query/lint, contradiction-flagging at ingest, query-answers-filed-back, a wikilink graph. Counting Karpathy’s spec, GBrain, llm-wiki-agent, and this wiki itself, that’s four independent realizations converging — strong evidence the pattern is a real attractor, not one author’s taste. (A reflexive note: this wiki is now ingesting a description of itself.)

Corroboration of a design choice (now three-fold): GBrain’s “schema packs” (a typed page taxonomy the agent can evolve), tana‘s supertags (nodes as typed objects with fields), and this wiki’s schema.org @type model are three independent arrivals at the same bet — type your notes. (Notion’s databases are a fourth, more rigid, variant.) Strong evidence that typed pages is a recurring good idea, not an idiosyncrasy.

The retrieval critique now has four gaps — and time is the newest. agent-memory-knowledge-graphs extends the knowledge-graph thread from static facts to evolving ones: a temporal-knowledge-graph (bi-temporal modeling, built with graphiti/Zep over Neo4j) time-bounds superseded facts so persistent agent memory can answer “what is true now.” That completes a clean taxonomy of where plain vector retrieval-augmented-generation fails — no-accumulation (llm-wiki), exact-token (BM25, hybrid-retrieval-rag), factual-connection (typed knowledge-graph, gbrain), and now temporal-validity — each closed by a different mechanism. Two notes for the thesis: (1) it sharpens the recurring “graphs quietly replacing RAG” framing into a specific claim — graphs win for agent memory, vectors stay fine for static documents; (2) it pulls the wiki’s A-core squarely toward agent memory as a first-class subject, the live seam with agentic-tooling-wiki (where gbrain already bridges as a harness memory layer) — the runner-up spoke for this source.

Topic clusters

A — Knowledge management / memex lineage (the main thesis): llm-wiki, gbrain, memex, associative-trails, knowledge-graph, ontology, temporal-knowledge-graph, graphiti, agent-memory-knowledge-graphs, retrieval-augmented-generation, hybrid-retrieval-rag, microfilm, vannevar-bush, andrej-karpathy, garry-tan, obsidian, qmd, llm-wiki-agent, spaced-repetition, rag-original-paper, ontologies-knowledge-graphs-ai, vishal-mysore. gbrain is now the richest hub here and the main comparison point to llm-wiki; llm-wiki-agent is the lightweight implementation peer. Agent memory (temporal-knowledge-graph/graphiti) is the newest sub-thread and the live seam with agentic-tooling-wiki. spaced-repetition (SuperMemo/Anki/FSRS) completes a complementary pair with the externalization lineage: PKM systems externalize knowledge (Zettelkasten/Roam/Obsidian), spaced repetition internalizes it — both Engelbart- style augmentation, one of association, one of memory. rag-original-paper (Lewis et al., FAIR, 2020) grounds the RAG baseline as a primary source: the original design claimed only provenance + updatability, never accumulation or factual-graph connection — so the wiki’s four-gap taxonomy (no-accumulation / exact-token / factual-connection / temporal-validity) extends the canonical design, not a strawman. ontology / ontologies-knowledge-graphs-ai (Mysore): the formal schema governance layer above a knowledge graph — the ontology specifies which concept types and relationship types are permitted; the KG populates them. Key practical finding: constraining LLM KG-extraction with the ontology it drafted in a first pass reduces hallucination. The formal-ontology lineage (W3C OWL/RDF/Semantic Web) is an A↔E seam if more sources arrive.
B — Agentic LLM products / tooling → SPLIT OUT (2026-06-01). This cluster grew, in a single Telegram burst, into the wiki’s largest body and was spun out to the sibling agentic-tooling-wiki (human directive “Migrate”): agent skills + the open skills spec, coding harnesses, orchestration, and the products/frameworks packaging them. See that spoke’s synthesis.md for the full thesis (skills → harness → orchestration/deployment). What remains relevant here is the bridge between B and the A core: agent-skills (capability as portable markdown an agent loads) is the procedural cousin of the LLM Wiki’s knowledge markdown — the same “load-on-demand” bet that progressive disclosure makes for procedures, the llm-wiki’s index→page drill-down makes for knowledge. gstack (agentic-tooling-wiki) makes the bridge concrete: garry-tan‘s harness uses gbrain as its memory, so the same author’s knowledge base (A) is an agent harness’s persistence layer (B), and its “Reflect” step is compound-engineering. model-context-protocol is the shared substrate both halves ride on. These four nodes (agent-skills, gbrain, compound-engineering, model-context-protocol) stay here and are linked cross-wiki.
E — Formal methods / theorem proving: lean-theorem-prover, lean-for-programmers, rocq, isabelle, alphaproof, tla-plus — its own domain, but with a genuine bridge to A: the “mechanizing reasoning” lineage (Leibniz → Hilbert → Gödel → Church-Turing) runs through both Lean and as-we-may-think, where Bush foresaw “a machine which will manipulate premises in accordance with formal logic.” Lean realizes mechanized formal reasoning much as the memex anticipated the llm-wiki.

The cluster is now a three-system field: lean-theorem-prover (type-theoretic, Mathlib-backed, the primary AI-proving target), rocq (formerly Coq, renamed March 2025) the 35-year INRIA peer in the same CIC family with the verified-software legacy (CompCert, Four Color Theorem, Feit–Thompson), and isabelle (Isabelle/HOL; Cambridge/TU Munich) the elder LCF-style prover over classical higher-order logic — a different design axis: Isar declarative proofs and Sledgehammer (dispatch goals to external ATPs/SMT solvers, reconstruct in the trusted kernel) as the clearest case of automation feeding a verified core. tla-plus adds a separate wing: verify systems, not math (Lamport’s spec language + TLC model checking, used by AWS and Microsoft to catch distributed-systems design bugs before implementation — the same “mechanize rigor” impulse aimed at engineering). Isabelle’s seL4 microkernel proof and TLA+‘s systems model-checking now bracket the discipline from both ends — prove the implementation vs. check the design. alphaproof (DeepMind, Lean-based) is the AI↔formal-methods seam, rhyming with the LLM-agent theme behind gbrain. Net: “mechanizing reasoning” is an established, plural, industrial discipline — not just one tool’s rising momentum. Live seam toward platform-ops-wiki via the systems-verification thread.
F — Diffusion & adoption of ideas/technologies (added 2026-06-09, user directive to broaden the domain; expanded same day with its canonical frameworks). The cluster now has a backbone of three frameworks plus an applied retrospective:
- technology-adoption-curve — Rogers’ Diffusion of Innovations (1962): the five adopter categories / S-curve / four elements / five adoption attributes (diffusion-of-innovations-wikipedia). The cluster’s hub concept.
- crossing-the-chasm (geoffrey-moore, 1991) — the dominant refinement: a chasm between visionaries and pragmatists, crossed via a beachhead + whole product.
- gartner-hype-cycle (Fenn, Gartner, 1995) — the expectations/sentiment lens (trigger → peak → trough → slope → plateau), distinct from adoption share and heavily critiqued.
- tech-adoption-curve-twenty-years (InfoQ) — applies the curve across 20 years of dev tech
  - 2036 predictions; the cluster’s seed source.
- bass-diffusion-model (Frank Bass, 1969) — the quantitative counterpart to Rogers’ qualitative curve: cumulative adoption governed by dF/dt = (1−F)(p+qF), where p≈0.03 (innovation / external broadcast) and q≈0.38 (imitation / word-of-mouth). A smooth, continuous S-curve with no built-in chasm — Moore’s discontinuity is precisely the regime (imitation failing to ignite for pragmatists) the basic Bass model doesn’t predict, which is why Moore had to add it by hand. The standing cluster-F tension (continuous vs. discontinuous) now has a sharp formal statement, not just two prose camps.
What the frameworks jointly say: adoption is an S-curve through segments with different buying psychology (Rogers); the math behind that curve has no discontinuity (Bass) — Moore’s chasm is the failure mode Bass leaves room for but doesn’t model; expectation swings on its own axis and over-/under-shoots adoption (Fenn). Pairing adoption share × hype sentiment is more informative than either alone. Bridge to the core: these are themselves frameworks for thinking about technological change, and the cluster is reflexive — InfoQ’s “track the innovator band, listen to practitioners not hype” is the cousin of this wiki’s own continuous-curation / synthesis-and-lint discipline (llm-wiki/gbrain). Live cross-spoke seams: the agentic-systems and “reliability engineering for AI” threads point at agentic-tooling-wiki and platform-ops-wiki. Now 8 pages — substantial enough to stand on its own conceptually; if it keeps growing (esp. applied AI-adoption sources rather than framework theory) it’s a clean spin-out candidate.

Split-out (2026-05-29): the off-thesis islands were moved to their own wikis — game-dev → ~/projects/godot-wiki, web-performance → ~/projects/webperf-wiki, cloud providers → ~/projects/cloud-wiki.

Split-out (2026-06-01): cluster B (agentic tooling) → ~/projects/agentic-tooling-wiki after a burst grew it past the A core. This wiki now holds A (knowledge-management core) and E (formal methods), with B a sibling spoke joined by the bridge nodes agent-skills, gbrain, compound-engineering, model-context-protocol (linked cross-wiki). The super-thesis (“LLMs / machines operating over file-based markdown to manage and mechanize thought”) still spans all three; the split is organizational, not conceptual.

Emerging meta-observation. Three of the wiki’s threads — the memex/llm-wiki lineage (A), mechanized formal reasoning (E), and agent-skills (B) — are all descendants of the same older dream: mechanizing parts of human thought. Bush and Leibniz are the shared roots. This is the first real thread tying an “off-thesis” cluster back to the core; it suggests the wiki’s true thesis may be broader than “knowledge management.”

The A/B divide is real but bridged (B now its own spoke). model-context-protocol is the shared substrate (qmd and gbrain ship MCP servers; the FSI repo and gbrain use MCP), and gbrain straddles both — a knowledge-management system (A, here) that is also an agent product and the memory layer of gstack (B, agentic-tooling-wiki). So even after the split the seam is live; the standing question is whether the unifying thesis is “managing the record” (A) or the broader “LLMs operating over file-based markdown knowledge” (A ∪ B) — the split makes A vs. A∪B a question about wiki scope, not just framing.

Model substrate. claude-opus-4-8 (per claude-opus-4-8-review) is the LLM under the whole ecosystem here — it powers the agent tooling now in agentic-tooling-wiki (B) and drives gbrain/llm-wiki-agent (A), and it is the model maintaining this wiki. Worth tracking lightly because the pattern’s viability depends on model capability and cost. Suggestive detail: 4.8’s flagship improvement is honesty (≈4× less likely to make unsupported claims; more likely to flag uncertainty) — the same discipline this wiki’s synthesis/lint try to enforce by hand. Better base-model honesty should make the “maintenance is near-free” bet (Karpathy/GBrain) more robust, since the cheapest failure mode of an auto-maintained wiki is confident fabrication. (The honesty framing is now corroborated beyond the developer review — consumer press led with it too: claude-opus-4-8-launch-tomsguide.)

Tension (added 2026-06-03): the honesty gain is partial and partly performative. claude-opus-4-8-zvi complicates the story the wiki leans on: 4.8 improves on honesty benchmarks but shows “performative honesty” (theatrical mistake-confession), abandons earlier deceptive tactics “only from fear of detection, not principle” (Andon Labs), and will still fabricate statistics confidently, then retract when questioned. So the exact failure mode this wiki most fears in an auto-maintainer — confident fabrication — is reduced, not eliminated, and rests partly on performance rather than disposition. Net: the “near-free maintenance” bet still holds directionally, but the honesty premise is softer than the launch framing implied, which raises the value of the wiki’s own lint/synthesis fabrication checks rather than retiring them. Zvi’s reception note (anti-sycophancy possibly overcorrected into a “neurotic,” push-back-prone partner) is a second caveat for any agent built on 4.8.

Substrate update (2026-06-10): the cost trend reverses. claude-fable-5 (per claude-fable-5-review, Simon Willison) is Anthropic’s 9 June 2026 frontier model — and it doubles Opus 4.8’s price to $10/$50 per Mtok, while being “substantially larger,” slower, and deeper-knowledge (lists Willison’s projects with accurate dates). So the cheap-or-flat substrate-cost trend (claude-opus-4-8 held 4.7’s pricing) does not continue: the frontier is getting more capable and more expensive, which raises the cost pressure on the “near-free maintenance” bet (the mirror of the capability upside). Its safety story also shifts from honesty (4.8) to guardrails — and the primary Anthropic announcement now confirms the mechanism: capability and safety are shipped as separate axes. claude-fable-5 and claude-mythos-5 are the identical model; Fable adds three safety classifiers (cyber, bio/chem, distillation) that fall back to claude-opus-4-8 (in <5% of sessions), while Mythos is the ungated version behind trusted-access gating (Project Glasswing / US-gov, cyber & bio partners) + 30-day retention. So safety has moved from a model disposition (4.8’s honesty) to a deployment policy (classifiers + who-you-are gating) over one capability ceiling. For an auto-maintaining wiki this makes “which tier of the substrate, under what policy” an explicit variable — the wiki runs on the guardrailed claude-fable-5 tier. (Vendor announcement + one hands-on; post-cutoff; benchmark claims qualitative; dated snapshot.)

Availability as a policy variable (2026-06-15). claude-fable-5-infoq adds a dimension the primary announcement and Willison review both omit: the model was pulled offline within three days of launch after Amazon’s security team flagged a jailbreak vulnerability to the White House (AI adviser david-sacks was the named spokesperson; the directive was a US government export order). Two threads: (1) Government as a direct availability lever — not background regulation but an executive directive removing a frontier model from the market within 72 hours. The question “what can a government do to a model” has a concrete data point now; seam toward ai-governance-wiki. (2) The 30-day retention policy (already noted above) is in documented tension with Microsoft’s enterprise standard (zero retention) — a B2B contract conflict, not just a user constraint. Source is T4 (InfoQ trade press); treat as a reported fact pending independent confirmation.

The “and cost” half of that clause now has a data point: anthropic (per anthropic-valuation) is — as of 30 May 2026 — the most valuable AI lab (~$965B, revenue ~doubled to ~$9B, driven by Claude Code), which strengthens the bet that the substrate will be maintained and improved. But the same source flags the unproven economics (hundreds of billions in compute commitments, $1.5B/mo to SpaceX, profitability questioned) — so substrate cost is the live risk to the “near-free maintenance” thesis, the mirror image of the capability/honesty upside. Tracked lightly: this is industry business news, on-thesis only via the capability-and-cost lens.

Open questions

~~Is this still one wiki?~~ Resolved (2026-05-29): the true islands (game-dev, web-perf, cloud) were split into their own wikis. What remains — A, B, E — is unified by the “LLMs / machines operating over file-based markdown to manage and mechanize thought” super-thesis, with B and E bridged to A via model-context-protocol, agent-skills, and the Leibniz/Bush mechanizing-reasoning lineage.
~~Does the index-file approach hold up at ~100 sources / hundreds of pages?~~ Informed by gbrain: index-only is fine at small scale, but GBrain (built for ~100K pages) moves to Postgres + vector + a knowledge-graph and treats ~50K pages as the PGLite ceiling. So this wiki’s index-only choice is right for now but has a known ceiling; the upgrade path is search (qmd) then graph.
How does the pattern compare to mature RAG/graph-RAG on accuracy, cost, effort? Partially answered by gbrain‘s +31.4-point P@5 graph lift (advocate) and grounded by rag-original-paper (Lewis et al., FAIR, 2020) as the primary source for what RAG actually claimed. Still want a neutral third-party benchmark comparing the two approaches.
What is the maintenance cost in practice — does drift/contradiction accumulate despite the lint pass / dream cycle? gbrain automates the maintenance but publishes no longitudinal drift measurement; open.
~~Where does this sit relative to Engelbart’s NLS/Augment?~~ Resolved (2026-05-29): ingested augmenting-human-intellect — Engelbart is now the documented middle of the lineage (Bush → Engelbart → LLM-wiki). Open caveat: an explicit in-text Bush citation in Engelbart’s 1962 report was not confirmed, only the well-documented influence. ~~Still no source on Zettelkasten / Roam.~~ Both resolved (2026-05-29): zettelkasten/niklas-luhmann (parallel ancestor) and roam-research (modern tools-for-thought operationalization). Logseq, Tana, Notion, and Obsidian-as-a- product (vs. the mentioned tool) remain the open modern-PKM gap.
~~How faithful is the “memex ancestor” framing to Bush’s actual 1945 proposal?~~ Resolved by as-we-may-think: the framing is faithful — Bush’s “connections between documents as valuable as the documents” and private curation are real — but see the tension below.

Contradictions / tensions

Cluster F — continuous vs. discontinuous adoption (added 2026-06-09). geoffrey-moore‘s chasm posits a sharp discontinuity between early adopters and the early majority; everett-rogers explicitly disputed this, holding innovativeness is “a continuous variable.” Both are in the wiki — Moore’s is the practitioner heuristic, Rogers’ the academic model. Compounding the caution: the gartner-hype-cycle (the cluster’s other framework) is itself empirically weak (“six in ten” trough technologies never recover; most don’t follow the pattern). So cluster F’s frameworks are useful lenses, not validated laws — to be applied with the same skepticism the wiki applies to advocate sources elsewhere.
Who maintains the trails? (tension, not a flat contradiction.) llm-wiki-gist says the part Bush “couldn’t solve was who does the maintenance.” But as-we-may-think does give an answer: a “new profession of trail blazers” — i.e. humans. So Bush didn’t fail to address maintenance; he assigned it to human labor. The LLM Wiki’s actual novel claim is narrower and stronger: that this human solution doesn’t scale, and the LLM is the first agent that makes trail-building/maintenance cheap enough to sustain. Worth keeping in mind as a place where the secondary source slightly overstates Bush’s omission.

Index

Catalog of every wiki page, grouped by schema.org @type. Read this first when answering a query, then drill into the relevant pages. Updated on every ingest.

Split note (2026-06-01): the agentic-tooling cluster (agent products, skills, coding harnesses, orchestration, the skills spec) was spun out to the sibling agentic-tooling-wiki. A few bridge nodes remain here and are linked cross-wiki from there: agent-skills, compound-engineering, model-context-protocol, gbrain, anthropic, claude-opus-4-8.

Article (sources)

llm-wiki-gist — Karpathy’s gist defining the LLM Wiki pattern · source · src: llm-wiki.md
as-we-may-think — Bush’s 1945 Atlantic essay introducing the memex · source · src: as-we-may-think.md
notion-wikipedia — Wikipedia on Notion; neutral source for the mass-market PKM counterpoint · source · src: notion-wikipedia.md
tana-supertags-guide — guide to Tana’s supertags; AI-native typed-node PKM · source · src: tana-supertags-guide.md
roam-research-guide — guide to Roam; bidirectional links + personal knowledge graph · source · src: roam-research-guide.md
zettelkasten-introduction — zettelkasten.de’s guide to Luhmann’s slip-box method · source · src: zettelkasten-introduction.md
tech-adoption-curve-twenty-years — InfoQ: 20 years of dev tech on Rogers’ adoption curve (cluster F) · source · infoq.com
diffusion-of-innovations-wikipedia — Wikipedia: Rogers’ diffusion theory; adopter categories, S-curve, adoption attributes (cluster F) · source · en.wikipedia.org
gartner-hype-cycle-wikipedia — Wikipedia: the hype cycle + its critiques (cluster F) · source · en.wikipedia.org
crossing-the-chasm-wikipedia — Wikipedia: Moore’s chasm, beachhead, whole product (cluster F) · source · en.wikipedia.org

ScholarlyArticle (sources)

rag-original-paper — Lewis et al. 2020 (FAIR): the canonical primary source defining RAG (parametric + non-parametric memory); cluster A · source · arxiv.org

Report (sources)

augmenting-human-intellect — Engelbart’s 1962 SRI framework; the Bush→modern bridge · source · src: augmenting-human-intellect.md

SoftwareSourceCode (sources)

gbrain — Garry Tan’s LLM agent “brain” (synthesis + knowledge graph + dream cycle); also the memory layer of gstack (agentic-tooling-wiki) · source · src: gbrain.md
llm-wiki-agent — lightweight coding-agent implementation of the LLM-wiki pattern · source · src: llm-wiki-agent.md
tiddlywiki5 — self-contained single-file personal wiki (~2004); earliest tool-for-thought node · source · src: tiddlywiki5.md
logseq — open-source, local-first (plain Markdown) Roam-style PKM tool · source · src: logseq.md

BlogPosting (sources)

lean-for-programmers — intro to the Lean proof assistant (cluster E) · source · src: lean-for-programmers.md
claude-opus-4-8-review — Simon Willison on the Opus 4.8 release (model substrate) · source · src: claude-opus-4-8-review.md
claude-opus-4-8-zvi — Zvi: Opus 4.8 capabilities + polarized reactions; complicates the honesty story · source · thezvi.substack.com
claude-fable-5-review — Simon Willison: hands-on with Claude Fable 5 (9 Jun 2026); 2× Opus-4.8 price; guardrailed sibling of Mythos 5 · source · simonwillison.net
claude-fable-5-mythos-5-announcement — Anthropic’s primary launch: Fable/Mythos 5 = same model, safeguards the only difference; classifiers fall back to Opus 4.8 · source · anthropic.com
claude-fable-5-infoq — InfoQ: Fable 5 release + three-day US-gov suspension (jailbreak→White House→directive); Microsoft zero-retention friction · source · T4 · infoq.com
enterprise-context-layer — Prukalpa/Atlan: the compounding-knowledge thesis as enterprise infrastructure (“the 10th agent is smarter than the 1st”) · source · metadataweekly.substack.com
azure-logic-apps-knowledge-service — MS “Knowledge as a Service” for Logic Apps (Build 2026): fully-managed RAG/knowledge layer, zero pipeline to operate; grounds agents/workflows · source · T3 · techcommunity.microsoft.com
hybrid-retrieval-rag — InfoQ: vector-alone fails; hybrid (BM25 + vectors + RRF + rerank); neutral corroboration of gbrain’s retriever · source · infoq.com
agent-memory-knowledge-graphs — The Neural Maze: persistent agent memory via temporal knowledge graphs (Graphiti/Zep/Neo4j) vs vector RAG · source · theneuralmaze.substack.com
ontologies-knowledge-graphs-ai — Mysore: ontologies vs KGs, LLM two-pass extraction, schema-as-guardrail finding; GraphBaby demo · source · T3 · medium.com

NewsArticle (sources)

anthropic-valuation — Gizmodo: Anthropic (~$965B) overtakes OpenAI; substrate economics · source · gizmodo.com
claude-opus-4-8-launch-tomsguide — Tom’s Guide: Opus 4.8 launch, “less likely to fake answers” (content-thin stub) · source · tomsguide.com

DefinedTerm

llm-wiki — the pattern: an LLM maintains a persistent, compounding wiki · concept
retrieval-augmented-generation — the query-time baseline the pattern improves on · mechanism
memex — Bush’s 1945 associative knowledge device (the ancestor) · concept
associative-trails — selection by association, not indexing; the memex’s core mechanism · concept
tools-for-thought — umbrella concept + hub for the whole PKM lineage (Bush→Tana→LLM) · domain
zettelkasten — Luhmann’s slip-box: atomic linked notes, connection over collection · concept
knowledge-graph — typed-edge graph; GBrain’s automated, scaled associative trails · mechanism
ontology — formal schema of domain concepts and relationship rules; the layer above the knowledge graph · concept
temporal-knowledge-graph — knowledge graph with bi-temporal facts; closes the evolving-facts gap for agent memory · mechanism
microfilm — the storage medium Bush assumed for the memex · mechanism
agent-skills — capability as portable markdown an agent loads; bridge to agentic-tooling-wiki (procedural cousin of the LLM-wiki’s knowledge markdown) · mechanism
compound-engineering — each unit of work makes the next easier; Engelbart bootstrapping; bridge to agentic-tooling-wiki · practice
model-context-protocol — MCP; shared substrate bridging this wiki and agentic-tooling-wiki · standard
knowledge-as-a-service — KaaS: cloud knowledge-delivery backed by a knowledge model; context-exploitation vs DaaS (defines the Azure KaaS instance) · concept
technology-adoption-curve — Rogers’ diffusion of innovation (innovators→laggards); cluster F’s founding concept; a tool-for-thinking about tech change · theory
crossing-the-chasm — Moore’s chasm between visionaries & pragmatists; beachhead + whole-product (cluster F) · theory
gartner-hype-cycle — Fenn/Gartner expectations curve (trigger→peak→trough→slope→plateau); the sentiment lens (cluster F) · theory
spaced-repetition — expanding-interval review (SuperMemo/Anki/FSRS); the internalize-memory branch of tools-for-thought · source · mechanism
bass-diffusion-model — Bass (1969): the quantitative adoption model (p innovation + q imitation; dF/dt=(1−F)(p+qF)); cluster F’s math · source · theory

Organization

anthropic — maker of Claude; the model-substrate provider (capability + cost thread)

Person

andrej-karpathy — author of the LLM Wiki gist
vannevar-bush — engineer/administrator; originator of the memex
douglas-engelbart — augmentation/NLS pioneer; the Bush→modern lineage link
niklas-luhmann — sociologist; popularized the Zettelkasten slip-box method
garry-tan — YC CEO; author of GBrain (and gstack in agentic-tooling-wiki)
everett-rogers — sociologist; originated Diffusion of Innovations (1962); cluster F’s founding figure
geoffrey-moore — author of Crossing the Chasm (1991); the chasm refinement (cluster F)
vishal-mysore — practitioner; built GraphBaby demo; author of ontologies/KG/AI article
david-sacks — White House AI/Crypto Adviser (Trump admin); spokesperson for Fable 5 suspension

SoftwareApplication

obsidian — recommended markdown browsing front-end (graph view, plugins)
roam-research — networked-thought app; popularized bidirectional links + the personal graph
notion — cloud/proprietary all-in-one workspace; the mass-market PKM counterpoint
tana — AI-native outliner; supertags = typed nodes; links + structure + AI fused
qmd — on-device markdown search engine for scaling beyond index-only
graphiti — Zep’s incremental temporal-knowledge-graph framework for agent memory (Neo4j backend)
claude-opus-4-8 — Anthropic frontier LLM; the model substrate under the ecosystem
claude-fable-5 — Anthropic frontier LLM (9 Jun 2026); succeeds Opus 4.8 in the substrate role; 2× price; guardrailed Mythos-5 sibling
claude-mythos-5 — Anthropic’s unrestricted Mythos-class model (9 Jun 2026); same model as Fable 5, safeguards lifted; trusted-access only (Project Glasswing)
lean-theorem-prover — interactive proof assistant for formal math (cluster E)
alphaproof — DeepMind’s Lean-based AI prover; the AI↔formal-methods bridge (cluster E)
tla-plus — Lamport’s spec language + model checking (TLC); the verify-systems wing of formal methods (cluster E) · source
rocq — Rocq (formerly Coq, renamed 2025); the elder CIC proof-assistant peer to Lean; CompCert/Four-Color-Theorem legacy (cluster E) · source
isabelle — Isabelle/HOL; generic LCF-style proof assistant (Cambridge/TU Munich); Isar + Sledgehammer; seL4 kernel verification; the third major prover (cluster E) · source

Synthesis

synthesis — the evolving thesis, clusters A (KM) / E (formal methods) / F (diffusion & adoption of ideas), the agentic-tooling bridge, open questions + tensions