Architecture and proof navigator
Routes a question through concepts, articles, laboratories, products, and proof statements for engineers, architects, executives, and hiring teams.
OVERLIFT ARCHITECTURE · GOVERNED INTELLIGENCE
Make the path smarter. Keep truth and authority exact.
The OverLift demo and Agentic AI Glossary & Learning Center now share one intelligence fabric: typed plans, bounded context, CATS retrieval, graph traversal, temporal qualification, Q-Lens path comparison, misconception repair, uncertainty, abstention, receipts, replay, and measured admission.
ONE FABRIC · TWO EXPERIENCES
Shared intelligence does not mean shared authority.
The OverLift demo explains architecture and product proof. The Learning Center adapts explanations and next steps. Both preserve canonical doctrine, sources, lifecycle, private progress, and exact replay.
Misconception-aware learning planner
Uses learner-authored goals, private progress, confusion signals, prerequisites, and reviewed doctrine to select a better explanation without inventing mastery.
Proposal authority only
Retrieval, ranking, comparison, personalization, clarification, explanation, and abstention may adapt. Doctrine, consent, policy, official state, mastery, and commit do not.
TEN-STAGE SYSTEM SPINE
From literal question to replayable decision.
- Frame typed intentDefinition, comparison, learning path, lifecycle, safety, temporal evidence, local-first, real-time, proof, architecture, or product.
- Bind bounded contextAudience, goal, experience, available time, privacy, selected concept, private progress, and confusion signals.
- Retrieve reviewed candidatesExact identity, lexical discovery, C17/Wasm, graph, local semantic proposals, CATS, and Tier-S.
- Traverse typed graphsConcepts, prerequisites, comparisons, articles, architectures, laboratories, products, and proof.
- Qualify source and timeReview date, lifecycle, provenance, version, freshness, and what was knowable.
- Compare Q-Lens pathsSeveral grounded routes, counterforces, entropy, margin, and effective path count remain visible.
- Project authorityCandidate intelligence is separated from doctrine, consent, policy, official state, mastery, and commit.
- Admit, clarify, or abstainUnknown vocabulary, missing constraints, close paths, low support, or consequential action stop unsafe certainty.
- Explain from admitted evidenceVisible language comes only from selected canonical terms, reviewed lessons, and route-backed proof.
- Seal receipt and replayThe request, context, evidence IDs, path scores, decision, and output reproduce exactly.
SHARED TECHNIQUE CAPITAL · SEPARATE AUTHORITY
Saros, Veil, Vellucent, Veluris, and the Learning Center contribute different strengths.
The fabric reuses their best governed techniques without pretending their evidence, consent, doctrine, or official state are interchangeable.
Temporal evidence and measured admission
Source-versus-learned separation, as-of truth, uncertainty, heterogeneous evidence, challenge sets, receipts, replay, and promotion only after measured improvement.
See Saros proof →Typed questions and human answer quality
Question planning, bounded context, local retrieval, Q-Lens path comparison, abstention, temporal continuity, and evaluation for directness, specificity, warmth, and repetition.
See Veil proof →Candidate versus accepted state
Immutable source, protected meaning, exact diffs, reviewer authority, accepted derived revisions, receipts, replay, and rollback.
See Vellucent proof →Consent-aware social intelligence
Fresh events and venues, explicit preferences, safety, private context, social-plan comparison, and abstention—without turning recommendation into disclosure, contact, compatibility, or relationship authority.
See Veluris proof →Canonical doctrine and adaptive explanation
Reviewed concepts, misconceptions, prerequisites, lifecycle state, private progress, contextual explanations, learning paths, and a permanent boundary against invented mastery.
Open the Learning Center →One inspectable architecture navigator
Concepts, articles, architectures, laboratories, products, and proof statements become traversable while the selected path, uncertainty, authority, and replay remain visible.
Run the full laboratory →MEASURED ADMISSION
Smarter behavior must earn promotion.
The frozen baseline currently contains 36 reviewed cases across definitions, comparisons, misconceptions, prerequisites, product proof, lifecycle state, temporal evidence, authority, hostile language, clarification, and abstention.
Canonical identities with source, lifecycle, and relationship metadata.
Prerequisite-aware paths with private progress and no manufactured mastery.
Route-backed editorial relationships with zero orphans.
Deterministic evaluation including safe clarification and abstention.
OVERLIFT GOVERNED INTELLIGENCE FABRIC · R10L/R10M
Ask a real question. Inspect the paths, uncertainty, authority, and exact replay.
This shared fabric powers the OverLift demonstration and the Agentic AI Glossary & Learning Center. It compiles a typed goal, binds bounded context, retrieves reviewed concepts, traverses the portfolio and prerequisite graphs, compares Q-Lens paths, repairs known misconceptions, clarifies or abstains, and seals the result.
FROZEN EVALUATION
Preparing 36 reviewed cases…
Canonical doctrine, consent, policy, official state, verified mastery, and deterministic execution remain outside learned authority.
ANSWER
Q-LENS PATH COMPARISON
Several grounded routes remain visible.
Scores guide selection; they never become source truth.
REVIEWED EVIDENCE
Canonical concepts and lifecycle state.
Every admitted concept keeps its identity, review date, lifecycle, and official sources.
ROUTE-BACKED PROOF
Continue through the content graph.
ADAPTIVE LEARNING
Suggested reviewed lessons.
Private adaptive signal · never a mastery claim
Inspect the 10-stage trace, misconception repair, and receipt
Reviewed correction
Deterministic receipt
Ready
This laboratory reads same-origin, source-reviewed static assets only. It performs no provider request, message send, tool execution, account mutation, doctrine rewrite, consent grant, product-state commit, or learner-mastery promotion.
Full Intelligence Spine · CATS C0–C7 · T0–T7 · Tier-S
One route vocabulary. One proof vocabulary. One deterministic authority path.
CATS chooses a qualified route. T0–T7 describe execution and proof. Tier-S challenges the route and the complete result. Semantic Bridge, Q-Lens, deterministic fusion, authority projection, and the deterministic compiler remain separate, inspectable stages.
Governed inputT0 groundCATS C0–C7Tier-ST0–T7 executionSemantic BridgeQ-LensFusionAuthorityCompilerReplay
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Full Intelligence Spine · CATS C0–C7 · T0–T7 · Tier-S
One route vocabulary. One proof vocabulary. One deterministic authority path.
CATS chooses a qualified route. T0–T7 describe execution and proof. Tier-S challenges the route and the complete result. Semantic Bridge, Q-Lens, deterministic fusion, authority projection, and the deterministic compiler remain separate, inspectable stages.
Governed inputT0 groundCATS C0–C7Tier-ST0–T7 executionSemantic BridgeQ-LensFusionAuthorityCompilerReplay
Loading the deterministic Full Intelligence Spine…