Nemo

Fictional Product

Name: Mnemos

Tagline: Your memory, not theirs.

Core idea:

A persistent, user-owned Context Memory Layer that sits above AI models and below apps. Any AI. Any app. Same memory. No lobotomy between sessions.

Think MCP, but opinionated, portable, and hostile to vendor lock-in.

The Conversation

User:

I’m tired of explaining myself. Every AI forgets who I am, what I’m building, what I decided yesterday.

Mnemos:

That’s because you’re renting memory from companies whose incentive is to reset it.

User:

I switch between models. GPT for reasoning. Claude for writing. Local models for private work. Each one acts like we just met.

Mnemos:

Because they did. You never moved your mind with you.

User:

So what are you?

Mnemos:

I’m not an AI. I’m your memory substrate.

What Mnemos Actually Does

Mnemos = Context OS

Not chat history. Not embeddings soup.

A structured, versioned, inspectable memory graph.

It stores:

• Long-term identity (who you are, how you think)
• Project state (what exists, what’s decided, what’s open)
• Preferences (tone, depth, constraints)
• Mental models (how you reason, not just what you said)
• Active context windows (what matters right now)

All of it:

• Model-agnostic
• App-agnostic
• User-owned

How It Works (No Marketing Lies)

1. Memory Is Externalized

Models don’t “remember.”

They request memory.

Every AI interaction becomes:

AI ↔ Mnemos ↔ App

The model asks:

• “Who is this user?”
• “What project are we in?”
• “What constraints apply?”

Mnemos answers. Same answer for every model.

2. Memory Is Typed, Not Blobs

Memory objects:

• Identity
• Project
• Decision
• Assumption
• OpenQuestion
• Preference
• RedLine
• MentalModel

Each with:

• provenance (where it came from)
• confidence
• expiry
• scope

No more hallucinated permanence.

3. Context Is Composable

You don’t load “everything.”

You mount context profiles:

• Founder Mode
• Legal AI – HAQQ
• Sci-Fi Writing – TARC
• One-Hour Sprint
• Private / No Cloud

Switch profile → every AI immediately behaves differently.

4. Chain Apps Without Losing the Plot

You start in:

• Notion → structuring
• Cursor → coding
• GPT → reasoning
• Claude → writing
• Local LLM → sensitive review

Mnemos keeps the through-line.

No re-explaining.

No copy-pasting.

No “as I said before.”

Why This Is Actually Hard (And Interesting)

Problem 1: Trust

If Mnemos lies, everything breaks.

So:

• Full inspectability
• Diffable memory changes
• Rollbacks
• “Why does the AI think this?” tracing

Problem 2: Over-memory

More memory ≠ better.

Mnemos enforces:

• Decay
• Revalidation
• Conflict detection
• Model-specific filtering

Claude doesn’t need your whole life.

A coding agent doesn’t need your tone preferences.

Problem 3: Incentives

AI vendors hate this.

Mnemos makes models interchangeable.

That’s the point.

Evaluation: Is This a Real Product or Founder Delusion?

What’s strong

• Solves a universal, felt pain
• Model churn makes this inevitable
• MCP-style infra is emerging anyway
• User ownership narrative is powerful
• Becomes a switching-cost magnet

What’s risky

• Needs standards to win
• Needs ruthless scope control
• Needs to avoid becoming “second brain v2”
• Needs security that’s not hand-wavy

What kills it

• Turning it into a UI-heavy app
• Trying to be smart instead of correct
• Letting models write to memory without friction

The Real Insight (The One People Miss)

AI models are stateless labor.

Humans are stateful.

Right now, we’re letting tools own our state.

Mnemos flips that.

One Sentence Version

Mnemos is a personal memory kernel that lets you change AI brains without losing your mind.