---
id: ADR-001
title: "Mneme HQ Positioning and Messaging Rules"
status: accepted
priority: normal
date: 2026-05-03
scope: positioning
---

# ADR-001: Mneme HQ Positioning and Messaging Rules

## Status

Accepted — 2026-05-01 · Updated — 2026-05-03

## Context

Mneme must be positioned distinctly within the emerging AI development governance market. Adjacent vendors are beginning to market governance, policy, and control features, but many operate downstream in software delivery or generic observability. Mneme's differentiation must remain tightly focused on architectural governance during AI-assisted development.

## Decision

Mneme will be positioned as the **architectural governance layer for AI-assisted development**.

---

## Core Positioning

- Mneme is the Architectural Governance Layer for AI-Assisted Development.
- Mneme enforces prior engineering and architectural decisions before model generation.
- Mneme prevents architectural drift and context loss in AI-assisted development workflows.

## Approved Supporting Phrasing

- Decision Memory and Architectural Drift Prevention for Coding Agents
- Architectural decision continuity and constraint enforcement during generation
- The governance layer between your architecture and the model
- Context continuity and decision enforcement for AI coding workflows

## Strategic Narrative

- AI coding is evolving from autocomplete into governed engineering systems.
- The core bottleneck is no longer raw model quality alone, but context continuity and adherence to prior decisions.
- Trust in AI development requires enforceable architectural memory.

---

## Competitive Framing Rules

### Against DevOps / Delivery Governance Platforms

Use this distinction:

- They govern **what gets shipped**.
- Mneme governs **what the model is allowed to propose/build**.

### Against Generic Memory Tools

Avoid reducing Mneme to:

- Persistent memory
- AI memory store
- Context database
- Prompt enhancement layer

If memory is discussed, frame it as:

- Structured architectural decision memory with enforcement semantics
- Retrieval and enforcement of prior engineering decisions

---

## Messaging Guardrails

### Emphasize

- Architectural governance
- Drift prevention
- Decision enforcement
- Context continuity
- Engineering standards adherence
- Pre-generation constraint enforcement

### Avoid / De-emphasize

- Generic AI governance
- Generic memory/persistence framing
- Chatbot assistant framing
- Productivity/autocomplete framing
- Downstream DevOps/platform governance conflation

---

## Market Category Claim

Mneme seeks to own the niche of:

- Architectural Governance for AI Development
- AI Development Standards Enforcement
- Context Continuity Infrastructure for Coding Agents

---

## Implications

- Website, docs, and outreach should reinforce architectural governance language.
- Competitor comparisons should clearly separate Mneme HQ from CI/CD, deployment, and observability tools.
- Product roadmap should continue supporting enforceable decision memory / drift prevention as core moat.

---

## Strategic Update — 2026-05-03: Org-Layer Positioning Thesis

### Reframe

Mneme HQ is not a productivity enhancer for solo engineers. It is infrastructure and governance for engineering orgs adopting AI coding at scale.

- **Not:** developer convenience tool
- **Potentially:** organisational control platform — same category motion as Snyk, Datadog, LaunchDarkly, early GitHub Enterprise

### GTM Model: Bottom-Up Adoption

```
Engineer installs OSS / local version
↓
Team adopts informally
↓
Tech lead / platform team notices value
↓
Org wants shared policies, centralised governance, auditability
↓
Paid team product
```

### OSS vs. Paid Distinction

**OSS version** is the wedge. Validates retrieval quality, enforcement usefulness, and developer workflow fit.

**Paid version** solves org-level problems — not "more memory":
- Shared policy registry
- Org-wide ADR sync
- Central governance dashboard
- Audit logs / compliance trail
- Team policy inheritance
- Approval workflows
- Managed cloud sync
- Analytics / drift reporting

### Validation Pivot

The question is no longer "do devs like this?" It is:

> **Do engineering leaders feel enough pain to buy governance tooling?**

Target discovery calls: CTOs, VPs Eng, Eng Managers, Staff/Principal Engineers, Platform/DevEx leads.

Strong signal: "We've hacked together internal controls", "Review load is rising", "We need governance before scaling AI use", "We'd pilot this."

Weak signal: "Interesting idea", "Maybe eventually."

### Updated Hero Direction

> **Architectural Governance for AI-Assisted Engineering Teams**

Supporting lines:
- Prevent architectural drift before code review
- Enforce engineering decisions across AI-generated code
- Scale governance as AI coding adoption grows

### Strategic Upside

If the org-layer thesis validates: Mneme HQ moves from small dev utility → budgeted engineering infrastructure / governance spend. That is venture-backable territory. Risk profile also changes — enterprise pain cycles are slower, buying process harder, ROI proof required.
