System Requirements Document for agentic-ai

1. Introduction

agentic-ai is a technical architecture-visualization product for the Agentic AI stack. Its purpose is to make the integration of the Agentic AI layers legible in a single, explorable view: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory.

The product exists because the core requirement is to understand how prompts, context, inference, and semantic layers are integrated — including the memory. A static picture is not enough; the product presents the architecture as a living instrument: a radial diagram with a central Inference Engine hub, concentric rings for the other layers, and a memory spine threading through every ring, so integration is literally visible as light crossing layers.

The audience is the Agentic AI Architect — the technical practitioner assembling and reviewing a single coherent layered architecture view, who needs every named keyword present as a labeled component, the integration relationships between prompts, context, inference, and semantic layers made explicit, and the semantic-layer detail drawn from the attached documents.

2. System Overview

The current product is a custom-UI, browser-delivered architecture visualization with four pages: Landing, Architecture Diagram, Integration Map, and Semantic Layers. All four are application-owned and reachable without an account (access_requirement: none); no protected work exists in the current scope, so no identity establishment or verification lifecycle is required.

The accepted behavior is:

• A single architecture diagram view that renders all named Agentic AI layers and keywords as labeled components.
• An integration view that shows how prompts, context, inference, and semantic layers connect, including where memory attaches.
• A semantic-layer detail view whose content is sourced from the attached documents describing Semantic layers.
• A public entry that explains what the product is, who it is for, and what it does before the diagram work begins.

The single accepted human actor is the Agentic AI Architect. There are no other accepted human personas, no differentiated permissions, and no role-based visibility: every page is equally reachable and every layer is equally inspectable.

Narrow exclusions. The product is a visualization and comprehension artifact. It does not execute prompts, run inference, train models, host a graph database, manage ontology authoring, or operate a memory store. It does not provide account management, collaboration, sharing, export pipelines, or persistence of architect-specific state. It does not add layers, keywords, or capabilities beyond the seven named terms and the integration relationships among them.

2a. Product Interpretation and Delivery Boundary

Delivery ownership. The product is delivered as a first-party web application with custom UI. All four pages are application-owned and publicly reachable; there is no provider-owned surface, no external destination, and no headless delivery in the current scope. Because no page requires continuity of private actor-specific state, no commitment, and no value transfer bound to a participant, application-owned identity is not established and not required.

Current boundary. Current scope is exactly: the Landing entry, the Architecture Diagram, the Integration Map, and the Semantic Layers detail sourced from the attached documents. Everything the architect needs to see the integration — the radial hub, the concentric rings, the memory spine, the flow strip, the legend, and the detail rail — lives inside those four pages.

Future boundary. Anything that would make the diagram executable, persistent, collaborative, or extensible beyond the seven named keywords is out of current scope and is recorded in Section 11 as future or excluded, not built now.

2b. Source Content Inventory

The attached documents describing Semantic layers details are supplied as an authoritative content_source and domain_context reference. They are the sole source of Semantic-layer detail rendered in the product.

Inventory status. The attached documents were not delivered into this generation as extractable text, so no verified factual entities, collection items, field values, dates, contacts, links, or media references can be enumerated here. The product requirement is therefore stated structurally and truthfully: the Semantic Layers page must render the semantic-layer detail from those documents, and no semantic-layer fact may be invented, substituted with dummy data, or replaced by a generic description. Where the documents supply named semantic-layer components, definitions, relationships, or metadata, those exact items populate the page; where they do not, the page shows only what the documents support.

2c. Page Content and Component Coverage

Landing

• Information and state. Product identity for agentic-ai; a statement of what the product is (an integrated architecture view of the Agentic AI stack); who it is for (the Agentic AI Architect); and what it does (renders all seven named layers and keywords and shows how they integrate, including memory). No user-specific state; the page is identical for every visitor.
• Primary action. Enter the architecture view — a single cyan-outlined call to action that navigates to Architecture Diagram.
• Supporting actions. Navigate directly to Integration Map and Semantic Layers from the same entry context.
• Domain entities. Layer (the seven named layers), Keyword (the seven named terms), Integration relationship.
• Component responsibilities. Full-viewport dark canvas; oversized Space Grotesk headline reading "The Agentic Stack, Integrated"; monospace subline listing the seven keywords; the hero radial diagram occupying the right 60% of the viewport with a glowing cyan central hub labeled "Inference Engine", five concentric rings for Context, Prompt, Graph, Ontology, and Semantic layers, and a magenta vertical memory spine cutting through all rings; a HUD readout in the top-right corner showing live layer counts; thin cyan flow lines pulsing outward from the hub.
• States. Loading: the hero canvas initializes with the ring geometry and hub label present before flow animation begins. Empty: not applicable — the page has no data-dependent emptiness. Success: headline, keyword subline, CTA, and hero diagram all render whole and readable at 375px, 768px, and 1280px. Error/recovery: if the WebGL hero cannot initialize, the page falls back to a static layered arrangement of the same rings, hub, and memory spine, with the headline, keyword subline, and CTA fully intact and functional.

Architecture Diagram

• Information and state. The complete Agentic AI layer inventory rendered as labeled components: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory. Each layer is labeled with an uppercase 11–12px micro-label at 0.18em tracking above a thin cyan rule. The central hub is labeled "Inference Engine". The memory spine is visually distinguished in magenta.
• Primary action. Select a layer node to inspect it — the right-rail detail panel updates in place, with no modal and no page change.
• Supporting actions. Hover a node to brighten its integration segments; scroll to scrub the zoom from whole-system overview down to a single layer; read the left-rail layer legend with cyan/magenta coding.
• Domain entities. Layer, Node, Ring, Memory spine, Integration edge, Layer metadata (node IDs, parameter counts, latency readouts).
• Component responsibilities. Full-bleed dark canvas as the primary surface; radial layout with the Inference Engine hub at center and concentric rings for Context Engineering, Prompt Engineering, Graph Engineering, Ontology Engineering, and Semantic Layers; vertical memory spine running through all rings; left rail layer legend; right rail detail panel that updates on node hover/click; glassy HUD panels with 1px cyan borders and monospace metadata; continuous slow orbit of the outer ring on a 30s loop; gentle parallax on the diagram as the cursor moves.
• States. Loading: ring geometry, hub label, and layer micro-labels render before orbit and flow animation start. Empty: not applicable — the layer set is fixed and always present. Success: all seven named layers and keywords are visible as labeled components, the memory spine visibly crosses every ring, and selecting any node updates the detail rail. Error/recovery: if a layer's metadata is unavailable, the node and its label still render and the detail rail shows the layer name and its integration edges without fabricated metadata values. Reduced motion: orbit freezes and the diagram switches to a static layered layout with the same labels, spine, and detail rail behavior.

Integration Map

• Information and state. The integration relationships among prompts, context, inference, and semantic layers, with memory's attachment points made explicit. The end-to-end path is presented as Prompt → Context → Graph → Inference → Semantic → Memory → back to Prompt.
• Primary action. Trace the end-to-end integration path and select a handoff segment to see which layers it connects.
• Supporting actions. Hover a segment to brighten it; read the horizontal end-to-end integration strip below the fold, which scrolls left-to-right as a ticker showing each layer's handoff as a labeled capsule; read the left-rail legend for cyan/magenta coding.
• Domain entities. Integration relationship, Handoff segment, Flow path, Memory attachment point, Layer.
• Component responsibilities. Animated cyan light sweeps traveling along integration flow lines from Prompt → Context → Graph → Inference → Semantic → Memory and looping back; the active segment brightening on hover; the horizontal integration strip as a ticker with labeled capsules readable in full as they pass; the memory spine rendered in magenta at every cross-layer junction where memory participates.
• States. Loading: the flow path and capsule labels render before the light sweeps begin. Empty: not applicable — the integration path is fixed by the accepted layer set. Success: every handoff in the path is labeled and traceable, and memory's attachment points are visible at each junction. Error/recovery: if the ticker cannot animate, the capsules wrap into rows so each handoff remains fully readable. Reduced motion: the ticker wraps into rows and the light sweeps become static highlighted segments.

Semantic Layers

• Information and state. Semantic-layer detail sourced from the attached documents describing Semantic layers. Content is presented in a document-derived column layout with monospace metadata blocks. No semantic-layer fact appears that the attached documents do not support.
• Primary action. Read the semantic-layer detail and follow its stated relationships to the other layers.
• Supporting actions. Navigate to Architecture Diagram to see the semantic layer in its ring position, and to Integration Map to see its handoff in the end-to-end path.
• Domain entities. Semantic layer component, Semantic layer definition, Semantic layer relationship, Document-sourced metadata block.
• Component responsibilities. Document-derived column layout; schematic diagrams and code-like monospace blocks rather than illustrations; monospace metadata blocks carrying the document's own identifiers and values; cross-references from each semantic-layer component to its position in the radial diagram and its handoff in the integration path.
• States. Loading: the column layout and metadata block frames render before document content is placed. Empty: if the attached documents supply no detail for a given semantic-layer component, that component is shown as named with an explicit statement that the attached documents provide no further detail — no placeholder or invented content. Success: every semantic-layer fact on the page traces to the attached documents, and each component cross-references its diagram position and integration handoff. Error/recovery: if document content cannot be retrieved, the page states that the semantic-layer detail is unavailable and offers navigation back to Architecture Diagram and Integration Map, which remain fully functional.

3. Functional Requirements

FR-1 — Public entry and product orientation (explicit) As an Agentic AI Architect, I should land on a public entry that explains what agentic-ai is, who it is for, and what it does, so that I understand the product before entering the architecture view.

• Trigger/input: the architect opens the product.
• Observable result: the Landing page renders the product identity, the audience statement, the seven-keyword subline, and a single cyan-outlined call to action into the architecture view.
• Access state: publicly reachable, no account required.
• Failure/recovery: if the hero canvas cannot initialize, the page falls back to a static layered arrangement with headline, keyword subline, and CTA intact.
• Continuation: the architect enters the Architecture Diagram.

FR-2 — Single architecture diagram with all named layers and keywords (explicit) As an Agentic AI Architect, I should see a single architecture diagram that renders all the keywords I named — Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory — as labeled components, so that no layer of the integration is missing from the view.

• Trigger/input: the architect opens the Architecture Diagram.
• Observable result: the radial diagram renders the Inference Engine hub at center, concentric rings for Context Engineering, Prompt Engineering, Graph Engineering, Ontology Engineering, and Semantic Layers, and a magenta memory spine running through all rings, each labeled with an uppercase micro-label above a thin cyan rule.
• Access state: publicly reachable, no account required.
• Failure/recovery: if a layer's metadata is unavailable, the node and label still render and the detail rail shows the layer name and its integration edges without fabricated values.
• Continuation: the architect selects a layer to inspect it.

FR-3 — Layer inspection without leaving the diagram (explicit) As an Agentic AI Architect, I should select a layer node and see its detail in a right-rail panel that updates in place, so that I can inspect a layer without losing the whole-system context.

• Trigger/input: the architect hovers or clicks a layer node.
• Observable result: the glassy HUD detail panel with a 1px cyan border slides in from the right rail and shows the layer's monospace metadata (node IDs, parameter counts, latency readouts); no modal opens and no page change occurs.
• Access state: publicly reachable, no account required.
• Failure/recovery: if metadata is unavailable for the selected layer, the panel shows the layer name and its integration edges and states that metadata is unavailable.
• Continuation: the architect selects another layer or moves to the Integration Map.

FR-4 — Integration relationships among prompts, context, inference, and semantic layers (explicit) As an Agentic AI Architect, I should see how prompts, context, inference, and semantic layers are integrated, so that I understand the connections rather than only the layer inventory.

• Trigger/input: the architect opens the Integration Map.
• Observable result: the integration relationships among Prompt, Context, Inference, and Semantic layers are rendered as labeled handoff segments along the end-to-end path.
• Access state: publicly reachable, no account required.
• Failure/recovery: if a handoff label cannot be resolved, the segment still renders and is marked as unresolved rather than being given an invented label.
• Continuation: the architect traces the full path including memory.

FR-5 — Memory's place in the integration (explicit) As an Agentic AI Architect, I should see where memory connects across the layers, so that the integration view includes memory rather than treating it as a separate concern.

• Trigger/input: the architect views the Architecture Diagram or the Integration Map.
• Observable result: the magenta memory spine visibly crosses every ring in the radial diagram, and memory's attachment points appear at the cross-layer junctions in the integration path, with the path looping from Memory back to Prompt.
• Access state: publicly reachable, no account required.
• Failure/recovery: if the spine cannot animate, it renders as a static magenta vertical element crossing all rings, preserving the same information.
• Continuation: the architect follows the loop back to Prompt or inspects the Semantic Layers detail.

FR-6 — End-to-end integration path as a readable strip (explicit) As an Agentic AI Architect, I should read the end-to-end integration path Prompt → Context → Graph → Inference → Semantic → Memory → back to Prompt as a labeled strip, so that I can follow the handoff sequence in order.

• Trigger/input: the architect scrolls below the fold on the Integration Map.
• Observable result: a horizontal integration strip scrolls left-to-right as a ticker, showing each layer's handoff as a labeled capsule that is readable in full as it passes.
• Access state: publicly reachable, no account required.
• Failure/recovery: if the ticker cannot animate, the capsules wrap into rows so every handoff remains fully readable.
• Continuation: the architect selects a handoff segment to see which layers it connects.

FR-7 — Semantic-layer detail from the attached documents (explicit) As an Agentic AI Architect, I should see the Semantic layers detail drawn from the attached documents, so that the semantic layer in the diagram is backed by the source material I supplied.

• Trigger/input: the architect opens the Semantic Layers page.
• Observable result: the semantic-layer detail renders in a document-derived column layout with monospace metadata blocks, and each component cross-references its position in the radial diagram and its handoff in the integration path.
• Access state: publicly reachable, no account required.
• Failure/recovery: if the attached documents supply no detail for a component, the component is shown as named with an explicit statement that the documents provide no further detail; if document content cannot be retrieved, the page states the detail is unavailable and offers navigation back to the diagram and map.
• Continuation: the architect returns to the Architecture Diagram or Integration Map with the semantic layer's position and handoff in mind.

FR-8 — Layer legend with cyan/magenta coding (required_inference) As an Agentic AI Architect, I should read a left-rail legend that codes layers by cyan and magenta, so that I can decode the diagram's color language without guessing.

• Trigger/input: the architect views the Architecture Diagram or Integration Map.
• Observable result: the left rail lists the layers with their cyan/magenta coding, matching the colors used for connective strokes, active nodes, and the memory spine.
• Access state: publicly reachable, no account required.
• Failure/recovery: if the legend cannot render, layer names remain visible as micro-labels on the diagram itself.
• Continuation: the architect uses the legend to read the diagram and map.

FR-9 — Scroll-scrubbed zoom from overview to a single layer (required_inference) As an Agentic AI Architect, I should scrub the zoom from whole-system overview down to a single layer, so that I can move between the integrated whole and one layer's detail without losing my place.

• Trigger/input: the architect scrolls on the Architecture Diagram.
• Observable result: the view zooms from the full radial overview toward the selected layer, with labels remaining readable throughout.
• Access state: publicly reachable, no account required.
• Failure/recovery: if scroll-scrubbed zoom is unavailable, the architect can still select a layer node to bring its detail into the right rail.
• Continuation: the architect inspects the layer or returns to the overview.

FR-10 — Reduced-motion static arrangement (required_inference) As an Agentic AI Architect, I should get a usable static arrangement when I prefer reduced motion, so that the architecture remains fully readable without animation.

• Trigger/input: the architect's system reports prefers-reduced-motion.
• Observable result: the outer-ring orbit freezes, the diagram switches to a static layered layout, the integration ticker wraps into rows, and light sweeps become static highlighted segments — with all labels, handoffs, and detail-rail behavior intact.
• Access state: publicly reachable, no account required.
• Failure/recovery: not applicable — this is itself the recovery arrangement.
• Continuation: the architect reads the same information as in the animated state.

4. User Personas

Agentic AI Architect

Product context. The architect is working on the Agentic AI stack across all layers of integration — Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, and Ontology Engineering — and needs a single coherent view of how those layers fit together. They are not a casual reader of an architecture blog post; they are assembling and reviewing the architecture itself, and they bring their own source material (the attached documents describing Semantic layers details) that must appear in the product rather than being paraphrased away.

Primary goal. To understand how prompts, context, inference, and semantic layers are integrated, including the memory — and to be able to point at any named layer and see both its place in the whole and its connections to the others.

Distinct accepted responsibilities.

• Verify that every keyword they named is present in the diagram as a labeled component: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory.
• Read the integration relationships among prompts, context, inference, and semantic layers, rather than only the layer inventory.
• Locate where memory attaches across the layers, since memory is the element that threads the whole stack.
• Follow the end-to-end handoff sequence in order and confirm it loops back to Prompt.
• Inspect a single layer's detail without losing the whole-system context.
• Confirm that the semantic-layer detail in the product matches the attached documents they supplied.

Relevant inputs and decisions. The architect's inputs are the seven named keywords and the attached semantic-layer documents. Their decisions are which layer to inspect next, whether the integration relationships shown match their mental model of the stack, and whether the semantic-layer detail is faithful to the source documents.

Interactions with other accepted participants. There are no other accepted human participants in the current scope. The architect is the sole actor; the product itself is the counterparty that renders, labels, and connects the layers. No handoff to a second human, no approval, and no shared state exists.

Observable success. The architect can see all seven named layers and keywords as labeled components in one diagram, can trace how prompts, context, inference, and semantic layers connect, can see memory crossing every layer, can read the end-to-end path in order, and can read semantic-layer detail that traces back to the attached documents.

What makes this role's work different. The architect's work is comprehension of a whole system, not operation of a feature. They do not create, edit, or persist anything; they read a system map and check it against their own source material. The product's value is entirely in whether the integration is visible and whether the semantic-layer detail is faithful — not in what the architect can produce with it.

5. Core User Flows

Flow 1 — Entering the product and orienting (Agentic AI Architect)

1. The architect opens agentic-ai and lands on Landing.
2. The page renders the product identity, the statement of who it is for, and the monospace subline listing the seven keywords: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory.
3. The hero radial diagram occupies the right 60% of the viewport: a glowing cyan central hub labeled "Inference Engine", five concentric rings for Context, Prompt, Graph, Ontology, and Semantic layers, and a magenta vertical memory spine cutting through all rings. Thin cyan flow lines pulse outward from the hub, and the HUD readout in the top-right shows live layer counts.
4. The architect reads the headline "The Agentic Stack, Integrated" and confirms the product covers the stack they are working on.
5. The architect selects the single cyan-outlined call to action and enters Architecture Diagram.
6. Failure/recovery: if the WebGL hero cannot initialize, the page falls back to a static layered arrangement of the same rings, hub, and memory spine, and the headline, keyword subline, and CTA remain fully readable and functional at 375px, 768px, and 1280px.

Flow 2 — Reading the full architecture diagram (Agentic AI Architect)

1. The architect arrives on Architecture Diagram from the Landing entry.
2. The radial diagram renders with the Inference Engine hub at center and concentric rings for Context Engineering, Prompt Engineering, Graph Engineering, Ontology Engineering, and Semantic Layers.
3. Each layer carries an uppercase 11–12px micro-label at 0.18em tracking above a thin cyan rule, so the architect can read every layer name directly on the diagram.
4. The magenta memory spine is visible running vertically through every ring, showing that memory crosses all layers rather than sitting beside them.
5. The left-rail legend codes the layers in cyan and magenta, matching the connective strokes, active nodes, and memory spine.
6. The architect confirms that all seven named keywords are present as labeled components.
7. Failure/recovery: if a layer's metadata is unavailable, the node and its label still render, and the detail rail shows the layer name and its integration edges without fabricated metadata values.
8. Continuation: the architect selects a layer to inspect it, or moves to the Integration Map.

Flow 3 — Inspecting a single layer without losing the whole (Agentic AI Architect)

1. On Architecture Diagram, the architect hovers a layer node.
2. The node's integration segments brighten, showing which connections belong to that layer.
3. The architect clicks the node.
4. A glassy HUD detail panel with a 1px cyan border slides in from the right rail — no modal, no page change — showing the layer's monospace metadata: node IDs, parameter counts, and latency readouts.
5. The architect scrolls to scrub the zoom from the whole-system overview down to that single layer, keeping the labels readable throughout.
6. The architect selects another layer, and the right-rail panel updates in place.
7. Failure/recovery: if metadata is unavailable for the selected layer, the panel shows the layer name and its integration edges and states that metadata is unavailable.
8. Continuation: the architect returns to the overview or moves to the Integration Map.

Flow 4 — Tracing the integration relationships (Agentic AI Architect)

1. The architect opens Integration Map.
2. The page renders the integration relationships among prompts, context, inference, and semantic layers as labeled handoff segments.
3. Animated cyan light sweeps travel along the flow lines from Prompt → Context → Graph → Inference → Semantic → Memory and loop back to Prompt.
4. The architect hovers a segment; the active segment brightens, showing exactly which layers that handoff connects.
5. The architect scrolls below the fold to the horizontal end-to-end integration strip, which scrolls left-to-right as a ticker with each layer's handoff shown as a labeled capsule, readable in full as it passes.
6. The architect follows the sequence in order and confirms it loops back to Prompt.
7. Failure/recovery: if a handoff label cannot be resolved, the segment still renders and is marked unresolved rather than being given an invented label. If the ticker cannot animate, the capsules wrap into rows so every handoff remains fully readable.
8. Continuation: the architect inspects the Semantic Layers detail or returns to the diagram.

Flow 5 — Locating memory's place across the layers (Agentic AI Architect)

1. On Architecture Diagram, the architect follows the magenta memory spine as it crosses every ring.
2. On Integration Map, the architect finds memory's attachment points at the cross-layer junctions, rendered in magenta at each junction where memory participates.
3. The architect confirms that memory is not a separate box but a spine that threads the stack, and that the path returns from Memory to Prompt.
4. Failure/recovery: if the spine cannot animate, it renders as a static magenta vertical element crossing all rings, preserving the same information.
5. Continuation: the architect returns to the diagram overview or opens the Semantic Layers detail.

Flow 6 — Reading the semantic-layer detail from the attached documents (Agentic AI Architect)

1. The architect opens Semantic Layers.
2. The page renders the semantic-layer detail in a document-derived column layout with monospace metadata blocks, using schematic diagrams and code-like monospace blocks rather than illustrations.
3. The architect reads each semantic-layer component and its document-sourced metadata block.
4. Each component cross-references its position in the radial diagram and its handoff in the integration path, so the architect can connect the detail back to the whole.
5. The architect confirms the detail matches the attached documents they supplied.
6. Failure/recovery: if the attached documents supply no detail for a component, that component is shown as named with an explicit statement that the documents provide no further detail — no placeholder or invented content. If document content cannot be retrieved, the page states that the semantic-layer detail is unavailable and offers navigation back to Architecture Diagram and Integration Map, which remain fully functional.
7. Continuation: the architect returns to the Architecture Diagram or Integration Map with the semantic layer's position and handoff in mind.

Flow 7 — Reading the architecture under reduced motion (Agentic AI Architect)

1. The architect's system reports prefers-reduced-motion.
2. On Landing, the hero renders as a static layered arrangement of the rings, hub, and memory spine, with headline, keyword subline, and CTA fully readable.
3. On Architecture Diagram, the outer-ring orbit is frozen and the diagram shows a static layered layout with all labels, the memory spine, and the detail rail intact.
4. On Integration Map, the ticker wraps into rows so each handoff capsule can be brought fully into view, and the light sweeps become static highlighted segments.
5. The architect reads the same information as in the animated state, with no loss of layer names, handoffs, or detail.
6. Continuation: the architect proceeds through the same pages and the same inspection actions.

6. Visuals, Colors and Theme

The creative direction is authoritative for this section. Muse: Gleb Kuznetsov. Headline concept: the architecture as a living instrument — a deep-tech visualization that reads like a spacecraft cockpit, not a SaaS dashboard.

Color tokens (dark mode)

Electric cyan #00E5FF is the primary connective and integration color: flow lines, active nodes, and key labels. Magenta #FF4FD8 is the hot accent reserved for the memory layer and critical cross-layer junctions, capped at roughly 10% of surface. Muted steel-blue #5A6B8C carries secondary text and inactive grid lines. Text is cool off-white #E8ECF8 at high contrast on the deep near-black navy ground.

Typography

• Headings: Space Grotesk — wide geometric sans. Display headlines at weight 500 with tight -0.02em tracking. Uppercase micro-labels at 11–12px with 0.18em tracking for layer names and axis markers.
• Body: IBM Plex Sans.
• Monospace data: IBM Plex Mono for node IDs, parameter counts, and flow annotations.
• Scale: 1.333 modular — display 72/48/32, heading 28/22/18, micro-label 12/11, body 16/15, mono 13. Mobile display caps at 40px; desktop scales to 72px via clamp().

Shape language

Thin luminous strokes — 1px cyan at 40–80% opacity. Rounded glass panels with 12–16px radii and 1px light borders. Circular nodes and bezel-like rings. Radial layout for the core integration hub. Hex and capsule chips for keywords. No heavy fills and no drop shadows; depth comes from glow and layering, not blur.

Layout

Full-bleed dark canvas as the primary surface. The architecture diagram is the page: a central radial hub ("Inference Engine") with concentric rings for Context Engineering, Prompt Engineering, Graph Engineering, Ontology Engineering, and the Semantic Layers, and a vertical memory spine running through all rings. Left rail: layer legend with cyan/magenta coding. Right rail: detail panel that updates on node hover/click. Below the fold: a horizontal flow strip showing the end-to-end integration path (Prompt → Context → Graph → Inference → Semantic → Memory → back to Prompt). The Semantic Layers page uses a document-derived column layout with monospace metadata blocks.

Imagery

The diagram itself is the imagery: glowing 3D nodes, particle fields along integration edges, thin luminous connective strokes, glassy data panels. No stock photos and no flat clip art. Optional subtle volumetric fog behind the hub for depth. Semantic-layer detail uses schematic diagrams and code-like monospace blocks rather than illustrations.

Forbidden

Blue–indigo (#2563EB, #4F46E5, #6366F1) on white is forbidden; all grounds are deep navy/black. Inter, Roboto, Arial, Helvetica, Open Sans, Lato, Poppins, and system-ui are forbidden for headings and body. Gradient-blob heroes and centered headline-plus-subtext-plus-blue-button layouts are forbidden. A grid of identical hover-lift cards for the layer list is forbidden — the radial diagram and rails are used instead. Flat 2D clip-art icons are forbidden; every visual element must read as luminous, layered, or instrumented. Blur-heavy glassmorphism that hurts performance on low-end devices is forbidden. Motion that bounces or plays for its own sake is forbidden — motion must communicate integration flow. The generic indigo/blue-on-white SaaS template is forbidden for this project.

Readability at every viewport

Headlines, wordmarks, labels, numbers, and cards' text and controls stay entirely inside the viewport and their container at 375px, 768px, and 1280px, wrapping or scaling (for example font-size: clamp(...) with its mobile size) to fit, and no other element covers any part of them. Imagery, decoration, and motion may be cropped, bled off an edge, rotated, overlapped, or cut as the direction asks, as long as they cover no readable text or control. Moving and scrollable content — the integration ticker and any horizontally scrollable rows — may cross the viewport or container edge by design; every item becomes fully readable as it passes. Under prefers-reduced-motion, items wrap into rows or allow horizontal scrolling so each item can be brought fully into view.

7. Signature Design Concept

The Agentic Stack, Integrated — a radial instrument, not a diagram.

The public entry is a full-viewport dark navy canvas (#06070E). A 3D radial architecture diagram occupies the right 60% of the screen: a glowing cyan central hub labeled Inference Engine, with five concentric rings for Context, Prompt, Graph, Ontology, and Semantic layers, and a magenta vertical memory spine cutting through all rings. Thin cyan flow lines pulse outward from the hub, and a small HUD readout in the top-right corner shows live layer counts.

On the left 40%, an oversized Space Grotesk headline at 72px desktop / 40px mobile reads "The Agentic Stack, Integrated", stacked over a monospace subline listing the seven keywords, with a single cyan-outlined CTA button pinned beneath.

The signature move is that integration is literally visible as light crossing layers: the memory spine threads vertically through every ring, and the flow lines travel the accepted path from Prompt → Context → Graph → Inference → Semantic → Memory and loop back. Selecting a layer slides a glassy HUD detail panel in from the right rail with 1px cyan borders and monospace metadata — no modal, no page change. Uppercase 11px micro-labels with 0.18em tracking and a thin cyan rule above each layer name give the whole surface a spacecraft-cockpit instrumentation feel.

This concept recomposes only accepted content, states, and controls: the seven named layers, the memory spine, the integration path, the layer legend, and the layer detail rail. It introduces no new behavior, page, or destination.

8. Interaction Model & Motion Direction

Interaction Model: Animated Motion Tempo: cinematic Hero Dimensionality: webgl

Landing Hero Motion Brief

• Focal subject. The 3D radial architecture diagram: the cyan Inference Engine hub, five concentric layer rings, and the magenta memory spine threading vertically through all of them.
• Input → transformation → outcome thesis. As the architect moves the cursor across the hero, gentle parallax shifts the diagram's depth layers; thin cyan flow lines pulse outward from the hub along the accepted integration path and loop back from Memory to Prompt; the HUD readout counts up the live layer counts. The outcome is that the architect sees the stack as one integrated instrument before entering the diagram — the integration is communicated by the motion itself, not by a caption.
• Motion vocabulary. Continuous slow orbit of the outer ring on a 30s loop; gentle cursor parallax on the diagram; light sweeps traveling along integration flow lines; counting numbers on parameter and latency readouts; scroll-scrubbed zoom from overview to a single layer. All motion is purposeful and low-frequency.
• Composed first frame. The hub is centered in the right 60% with all five rings and the memory spine already drawn and labeled; the headline, keyword subline, and CTA are fully rendered on the left 40%; the HUD readout is present in the top-right. Nothing is mid-animation or partially drawn at first paint.
• Reduced-motion state. The orbit freezes, the diagram switches to a static layered layout, the ticker wraps into rows, and light sweeps become static highlighted segments — with every label, handoff, and detail-rail behavior intact and readable.

Landing Hero 3D Scene Brief — DIRECTION-DERIVED

• Subject. One crafted real-time object: a radial architecture instrument — a luminous cyan central hub labeled "Inference Engine" with five concentric rings (Context, Prompt, Graph, Ontology, Semantic) and a magenta vertical memory spine passing through every ring.
• Defining state shown. The product's defining state is integration: the memory spine visibly crossing every ring while cyan flow lines travel the accepted path Prompt → Context → Graph → Inference → Semantic → Memory and loop back to Prompt.
• Scene composition. Dark navy ground #06070E with optional subtle volumetric fog behind the hub for depth; glowing nodes on each ring; particle fields along the integration edges; thin luminous connective strokes at 1px cyan, 40–80% opacity; glassy data panels with 1px cyan borders.
• Interaction. Cursor parallax on the diagram; hover brightens the active integration segment; selecting a layer slides the glassy HUD detail panel in from the right rail with monospace metadata (node IDs, parameter counts, latency readouts).
• Performance and fallback. No blur-heavy glassmorphism that would hurt low-end devices. If WebGL cannot initialize, the hero falls back to a static layered arrangement of the same rings, hub, and memory spine, with headline, keyword subline, and CTA fully intact. Under prefers-reduced-motion, the orbit freezes and the scene renders as a static layered layout.

9. Non-Functional Requirements

NFR-1 — Semantic-layer fidelity to the attached documents (explicit) Semantic-layer detail must come from the attached documents supplied by the user. No semantic-layer fact may be invented, substituted with dummy data, or replaced by a generic description. Where the documents supply no detail for a component, the product states that explicitly rather than filling the gap. Rationale: the user stated this as a hard constraint and supplied the documents as an authoritative content source.

NFR-2 — Complete keyword coverage (explicit) The architecture diagram must include all keywords the user typed: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory. None may be omitted, merged away, or renamed. Rationale: the user named these terms explicitly and required the diagram to include all of them.

NFR-3 — Integration legibility (explicit) The product must make the integration among prompts, context, inference, and semantic layers — including memory — understandable. A layer inventory alone does not satisfy this; the relationships and the memory attachment points must be visible. Rationale: the user stated this as their core requirement.

NFR-4 — Readable text and controls at every viewport (explicit) Headlines, wordmarks, labels, numbers, and cards' text and controls stay entirely inside the viewport and their container at 375px, 768px, and 1280px, wrapping or scaling to fit, with no other element covering any part of them. Moving and scrollable content may cross the viewport edge by design, provided every item becomes fully readable as it passes. Rationale: stated as a project-wide readability constraint in the creative direction.

NFR-5 — Reduced-motion usability (required_inference) Under prefers-reduced-motion, the product must provide a usable static arrangement: orbit frozen, static layered diagram, ticker wrapped into rows or horizontally scrollable, light sweeps as static highlighted segments — with all information preserved. Rationale: the creative direction specifies reduced-motion behavior; preserving the same information is indispensable for the architect's comprehension goal.

NFR-6 — Rendering performance on low-end devices (required_inference) The hero and diagram must avoid blur-heavy glassmorphism and other effects that degrade performance on low-end devices, while retaining the luminous, layered, instrumented look. Rationale: the creative direction explicitly forbids blur-heavy glassmorphism that hurts performance on low-end devices.

NFR-7 — Public reachability without accounts (explicit) All four pages are reachable without an account. No identity establishment, verification, or account-management capability is in current scope. Rationale: the planning scope assigns access_requirement: none to every page, and no accepted journey requires continuity of private actor-specific state, a commitment, or a value transfer bound to a participant.

10. Tech Stack

• Frontend: React with a custom UI, delivered as a browser web application.
• 3D / real-time rendering: WebGL via React Three Fiber for the radial architecture hero and diagram, per the creative direction's webgl hero dimensionality.
• Styling: CSS with custom properties for the color, typography, and shape tokens in Section 6; clamp() for the responsive type scale.
• Fonts: Space Grotesk (headings), IBM Plex Sans (body), IBM Plex Mono (monospace data).
• Backend: Python / FastAPI, serving the semantic-layer document content and any layer metadata the diagram reads. This is a single shared backend; no separate service or container is required for the current scope.
• Storage: document storage for the attached Semantic layers documents, read by the backend to populate the Semantic Layers page.
• Deployment: Docker / docker-compose for the frontend and backend. Kubernetes is not required for the current scope.

No source-specified technology was overridden; the stack above reflects the creative direction's rendering requirements and the minimal server-side need for document-sourced semantic-layer content.

11. Assumptions and Constraints

Constraints

• C-1 (explicit). Semantic layer details must come from the attached documents supplied by the user. This is a hard constraint and is not relaxed anywhere in the product.
• C-2 (explicit). The architecture diagram must include all seven named keywords: Context Engineering, Prompt Engineering, Graph Engineering, Inference Engineering, Semantic Layers, Ontology Engineering, and memory.
• C-3 (explicit). The diagram must show how prompts, context, inference, and semantic layers are integrated, including memory.
• C-4 (explicit). The creative direction is authoritative for visuals, color, typography, shape, layout, motion, and imagery. The forbidden list in Section 6 is binding.
• C-5 (explicit). All four pages are publicly reachable with no account requirement.

Assumptions

• A-1 (required_inference). The attached documents describing Semantic layers details are available to the product as a content source at build and runtime. If they are not, the Semantic Layers page states that the detail is unavailable rather than substituting content.
• A-2 (required_inference). The seven named keywords constitute the complete current layer set. No additional layers are added.
• A-3 (required_inference). The Agentic AI Architect is the sole accepted human actor; no collaboration, sharing, or multi-user state is assumed.
• A-4 (required_inference). The end-to-end integration path is Prompt → Context → Graph → Inference → Semantic → Memory → back to Prompt, as stated in the creative direction's layout and signature moves.
• A-5 (required_inference). Layer metadata shown in the detail rail (node IDs, parameter counts, latency readouts) is illustrative instrumentation for the diagram; where real values are unavailable, the panel states that metadata is unavailable rather than fabricating values.

Future and excluded scope

The following are explicitly out of current scope and are not built now:

• Executing prompts, running inference, training models, or operating any live agent runtime.
• Hosting or managing a graph database, an ontology authoring environment, or a memory store.
• Account management, authentication, role-based access, or differentiated permissions.
• Collaboration, sharing, export pipelines, or persistence of architect-specific state.
• Any layer, keyword, or capability beyond the seven named terms and their integration relationships.

12. Glossary

• Agentic AI Architect — the sole accepted human persona; the technical practitioner who assembles and reviews the integrated Agentic AI layer view and supplies the semantic-layer source documents.
• Architecture Diagram — the page that renders all seven named layers and keywords as labeled components in a radial layout.
• Context Engineering — one of the seven named layers; rendered as a concentric ring around the Inference Engine hub.
• Graph Engineering — one of the seven named layers; rendered as a concentric ring around the Inference Engine hub.
• Inference Engine — the central hub of the radial diagram; the layer around which the other rings are arranged.
• Integration Map — the page that renders the integration relationships among prompts, context, inference, and semantic layers, including memory's attachment points.
• Integration relationship — a labeled handoff segment connecting two layers along the end-to-end path.
• Landing — the public entry page that explains the product, its audience, and its purpose before the architecture work begins.
• Memory spine — the magenta vertical element that runs through every ring in the radial diagram, showing that memory crosses all layers.
• Micro-label — an uppercase 11–12px label at 0.18em tracking, set above a thin cyan rule, used for layer names and axis markers.
• Ontology Engineering — one of the seven named layers; rendered as a concentric ring around the Inference Engine hub.
• Prompt Engineering — one of the seven named layers; rendered as a concentric ring around the Inference Engine hub.
• Semantic Layers — one of the seven named layers, and the page that renders its detail sourced from the attached documents.
• Semantic Layers page — the page that presents document-derived semantic-layer detail in a column layout with monospace metadata blocks.