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Cognition console UI design

User: Oxford Pierpont
Created: 12/7/2025 12:39:13
Updated: 12/10/2025 6:50:26
Exported: 2/11/2026 7:09:19
Link: https://chatgpt.com/g/g-p-69395d9991108191841f1dac1fd8d1a1-oxpi-aiconnected-ui-features/c/6935bbc0-3a00-8327-b73f-fe6e7bd904a2

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Prompt:

I’m preparing to build the Cognigraph artificial cognition architecture, and in order to do that I need to also build a front-end interactive interface that will be used to just, you know, operate and use the AI. So since I have to build one anyway, I’m going to take this opportunity to design a better version of memory, just chat history, chat memory, the way that these chat interfaces the way that a concept like projects works, and the way that memory or interconnected chats work in general. And so that’s what we’re here to plan out today.

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Response:

Good, this is exactly the right time to nail this, before you start wiring in Cognigraph under the hood. Let’s treat today as “define the mental model + UI contract” for how people will actually live inside this thing.

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1. What this interface actually is

Instead of “a chat app with better memory,” I’m going to assume you’re building:

A Cognition Console
where:

• you talk to one or more Personas
• inside clearly defined Projects
• with an explicit, inspectable Memory System (Cognigraph)
• and all of that is visible and controllable from the UI.

So the front-end is basically a control panel over Cognigraph’s memory layers, plus a workbench for doing real projects with the AI.

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2. Core objects (the data model your UI should expose)

These are the “things” the user should see and manipulate. I’ll define them as conceptual types, not final code.

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2.1 Persona

A Persona is not “just a chat.” It’s a semi-stable mind:

• id
• name – “Neuro Architect”, “Legal Analyst”, “Story Engine”, etc.
• role / purpose – What this Persona is supposed to be used for.
• style – Tone, level of detail, assumptions.
• linked_memory_scope – Which slice of Cognigraph it’s mainly allowed to use (global, domain, project-level).
• safety/constraints profile – Guardrails, forbidden topics, etc.

UI impact:

• Persona picker at the top.
• Persona detail panel showing its purpose, strengths, and what memories it “lives inside.”

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2.2 Project

Projects are the backbone. Not loose chats.

• id
• name
• description / goal statement
• status – active / paused / archived
• primary_persona_id (optional)
• related_persona_ids (secondary minds you use for this project)
• pinned_memory_ids – the most relevant long-term memories for this project
• artifact_ids – docs, specs, uploads
• created_at / updated_at

UI impact:

• Left sidebar: list of projects with filters.
• Project dashboard: goals, tasks, last sessions, key memories.

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2.3 Session (what replaces “chats”)

A Session is a conversation episode inside a Project. This is where the messages live.

• id
• project_id
• persona_id
• title – “Memory architecture brainstorm #1”
• context_config – which memories/topics are attached to this session
• created_at / last_active_at

UI impact:

• Within a Project: “Sessions” tab with a timeline.
• Each Session opens into a chat-like view, but with visible context/memory.

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2.4 Message

This is the raw dialogue, but it’s not the primary memory; it’s the evidence from which memory is distilled.

• id
• session_id
• author – user | persona | system
• content
• created_at
• tags – auto-suggested topics
• linked_memory_ids – which Memory nodes this message contributed to
• “promoted” flag – if some part was selected & promoted into long-term memory

UI impact:

• Normal chat stream.
• Hover over a message → see which memories came from it, and promote/demote.

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2.5 MemoryNode (Cognigraph node)

This is the central thing. A structured memory entry, following your Category → Concept → Topic hierarchy and Open/Closed layers.

• id
• scope – global | persona | project | session
• layer – Open Thinking (ephemeral notes) | Closed Thinking (committed knowledge)
• category – big domain (“Business”, “Health”, “Fiction: Rift”, “aiConnected architecture”)
• concept – sub-area (“Cognigraph memory model”, “BrowserEngine PRD”)
• topic – specific thread (“Open vs Closed Thinking Layers UI”, “Project vs Session distinction”)
• type – fact | preference | rule | plan | story | pattern | question | decision
• content – the distilled memory text
• source_message_ids – which messages created this
• origin_persona_id (optional)
• importance_score – how central this is
• stability_score – how “settled” vs “tentative”
• last_accessed_at
• created_at

UI impact:

• A dedicated Memory Explorer.
• “Memory drawer” on the right side of a Session.
• Ability to expand Category → Concept → Topic, click a node, read/edit it.

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2.6 Artifact

Anything that isn’t a message but is part of the work.

• id
• project_id
• type – file | URL | note | spec | dataset
• title
• description
• link / file_metadata
• generated_by_persona_id (if AI wrote it)
• created_at

UI impact:

• Project “Assets” tab showing documents.
• Side panel to quickly insert artifacts into context.

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2.7 Task (optional, but powerful)

Even if you don’t build a full task system, the UI should support:

• id
• project_id
• title
• status – idea | todo | in progress | done
• linked_memory_ids / artifact_ids
• created_at / due_date

UI impact:

• Lightweight checklist inside each Project.
• Tasks feed the memory graph: tasks completed → decisions/lessons get stored as MemoryNodes.

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3. Rethinking “chat history” & “projects”

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3.1 Old world: Chat ≈ Memory

• Each chat is a silo.
• “Memory” is a vague hidden blob.
• Projects are bolted on as a folder of chats.

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3.2 New world: Memory ≈ Knowledge graph; chat is a log

• Projects are first-class.
• Sessions are episodic conversations inside projects.
• Memory is a graph across everything, with clear scopes.
• The UI lets you see:
  • what was remembered
  • where it’s stored (global / persona / project)
  • how it’s used in the current Session.

From the user’s point of view:

“I’m not talking to a blank slate each time.
I’m talking to a Persona that lives in a specific Project,
and I can see the brain it’s using.”

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4. Core screens & layout

Think in terms of 4 primary views:

1. Home / Persona Hub
2. Project Dashboard
3. Session View (chat + memory drawer)
4. Memory Explorer

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4.1 Global layout (for desktop)

• Left sidebar
  • Top: Persona selector (avatar + name + status)
  • Mid: “Projects”, “Global Memory”, “Settings”
  • Bottom: Daily “New Memory Report” link
• Main area
  • Contextual: Projects list, Session, Memory Explorer, etc.
• Right drawer (toggle)
  • “Context & Memory” for current Session:
    • Active memory slice
    • Pinned nodes
    • Recently used nodes
    • Quick edit/add

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5. Project Dashboard UX

When you click a Project:

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Header

• Name
• Main Persona
• Key goal statement (“Build Cognigraph front-end for artificial cognition”)
• Status badge

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Tabs

1. Overview
   • Current goal / summary.
   • Last 3 Sessions.
   • Top 5 “key memories” (pinned MemoryNodes).
   • Active tasks.
2. Sessions
   • Timeline list of Sessions.
   • Each with title, date, Persona, and short summary.
   • Button: “New Session” (with Persona picker).
3. Memory
   • Scoped Memory Explorer:
     • Only project-scoped nodes by default.
     • Filter by type (fact, plan, decision, etc.)
     • List + tree view.
4. Artifacts
   • Uploads, specs, notes, links.
   • “Use in Session” button to attach an Artifact as context.
5. Settings
   • Which Personas are allowed.
   • Default memory slice rules (e.g., “let this project use global ‘Engineering’ memories but not personal life”).

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6. Session View: the “chat” you’ll live in

When you open a Session:

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Left: Breadcrumbs

• Persona avatar + name
• Project name
• Session title

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Center: Conversation Stream

Standard chat, but each message can show:

• Tiny tags under the message:
  • #Cognigraph, #MemoryModel, #UI
• Indicator if memory was created/updated:
  • e.g. small icon “3 memories updated”

On hover / click:

• “View linked memories”
• “Promote this to long-term memory” (if the AI suggested a candidate)
• “Remove from memory”

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Right: Context & Memory Drawer

Sections:

1. Active Context
   • List of memory nodes currently attached to this Session.
   • Chips or cards:
     • Title (topic)
     • Type (rule, plan, preference)
     • Scope icon (global / persona / project)
   • You can:
     • Pin/unpin
     • Temporarily disable a node for this Session.
2. Suggestions
   • Memory nodes the engine thinks would be useful right now.
   • “Add to context” button.
3. Scratchpad (Open Thinking Layer)
   • Ephemeral notes for this Session only.
   • The AI may write transient reasoning here.
   • You can click “Commit to closed memory” to solidify something.

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7. Memory Explorer: “the brain” UI

Separate full-screen view, but also accessible inside a Project.

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Controls

• Filters:
  • Persona
  • Project
  • Scope (global / persona / project)
  • Type (fact, rule, preference, etc.)
  • Time window (created/last accessed)
• Views:
  • Tree view – Category → Concept → Topic → nodes
  • List view – sortable table
  • Later: Graph view – visual knowledge graph

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Memory Node card

When you click a node:

• Content
• Type, scope, layer, scores
• Source Sessions/Messages
• Links:
  • “Jump to source message”
  • “Edit & version history”
  • “Attach to current Session”
  • “Change scope” (e.g., promote from project → global)
  • “Mark outdated” (lowers stability & hides from default context)

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Daily “New Memory Report”

This is a key surface for Cognigraph:

• Grouped by Project & Persona.
• “New long-term memories created today”
• “Updated memories”
• “Potential conflicts or contradictions”

From the report, you can:

• Approve / adjust / delete nodes.
• Re-scope them (“this belongs only in aiConnected, not global”).

This is how the user actually governs the Closed Thinking Layer.

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8. How messages become memories (UI side)

You’ll want a consistent flow:

1. User and Persona talk in a Session.
2. Behind the scenes, Cognigraph:
   • extracts candidate memories
   • links them to existing nodes or creates new ones.
3. UI surfaces this in two ways:
   • Inline: a subtle indicator on messages (“2 new memories extracted”).
   • End-of-session summary: “Here’s what I learned / updated.”
4. User has explicit control:
   • Accept / reject / edit these new nodes.
   • Or defer and handle via the Daily New Memory Report.

This makes memory feel deliberate, not spooky.

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9. “Projects” as true context bundles

In the current “Project” implementations you’ve seen elsewhere, it’s often just:

Project = folder of chats + some files.

You can do better: For each Project, the system should maintain:

• Context Profile:
  • Default memory scopes
  • Relevant categories (e.g., “Engineering: Cognition”, “Business: aiConnected”)
  • Style preferences (short vs long, more code vs more explanation)
• Personas:
  • Which Persona is the “lead” mind for this domain.
  • Which secondary Personas assist.
• Knowledge baseline:
  • Pinned MemoryNodes representing key assumptions/decisions.
  • The Project reads like a living spec.

Then when you start a new Session, the UI can show:

“Starting Session with:

• Persona: Neuro Architect
• Project: Cognigraph Front-End
• Context: 17 memory nodes (rules, decisions, architecture)
• Artifacts: PRD v1, wireframe sketches, previous conversation summaries”

And you have a “Configure context” button to fine-tune before you send the first message.

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10. How this ties into Cognigraph’s internal layers

You already defined:

• Open Thinking Layer (OTL) – transient reasoning.
• Closed Thinking Layer (CTL) – committed, structured memory.

So in the front-end:

• The Scratchpad and per-Session notes map to OTL.
• The Memory Explorer nodes (with category/concept/topic) map to CTL.

Key UI rules:

1. The user can always see which layer they are editing.
2. Promotion → “Convert this scratchpad element to a permanent memory.”
3. Demotion → “Move this memory back to scratch / mark as tentative.”

You can visually distinguish:

• OTL: lighter, “pencil” icon, ephemeral.
• CTL: solid, “book” icon, durable.

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11. Minimal MVP vs “fancy later”

To avoid trying to ship a 40-year system in v1, your MVP of the interface could be:

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MVP must-haves

1. Personas
   • Persona picker + simple Persona settings.
2. Projects
   • Create/edit Project
   • Attach Personas to Projects
3. Sessions
   • Conversation view
   • Basic Session list under a Project
4. Memory (CTL)
   • Auto-extracted memories displayed as a list under each Project
   • Simple filters (by type, by time)
   • Ability to edit / delete / pin a memory
5. Context Drawer
   • Shows memory nodes currently used in the Session
   • Let user toggle them on/off
6. Daily Memory Report
   • Simple list of new/updated nodes, grouped by Project

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Later enhancements

• Full Memory Explorer tree view + graph view
• Tasks integrated with memory
• Cross-project similarity suggestions (“this looks similar to X from aiConnected”)
• Timeline visualizations (“dashboard of what the AI learned over the last week”)
• Story mode / narrative of a Project’s history

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12. What we can do next

For the next step, I’d suggest:

1. Lock the object model
   • I can turn the conceptual objects above into actual TypeScript interfaces or Supabase table schemas.
2. Define core screens more concretely
   • Screen-by-screen layout: header, sidebars, components, and what each panel shows.
3. Specify the API contract with Cognigraph
   • For example: what the front-end sends when it starts a Session:
     • persona_id, project_id, session_id, active_memory_ids, scratchpad, etc.
   • What it receives when messages are processed:
     • reply, created_memory_nodes[], updated_memory_nodes[], context_suggestions[].

If you want, I’ll start by drafting the data schema + component tree for the MVP version of this Cognition Console so you can immediately map it into Next.js / Supabase.

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