Works alongside · Devin

# Mneme Works Alongside Devin

Devin executes. Mneme preserves architectural intent across that execution. The governance layer that sits above Devin and every other autonomous coding agent on the codebase — ADR-derived constraints, deterministic retrieval, hook and CI enforcement, the same compiled rules across every surface.

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## What Devin changes operationally

The shift Devin reflects — and the rest of the autonomous coding agent category alongside it — is from suggestion to delegated execution. A developer used to read each line; now they review the outcome of a task that may span dozens of files and several runtime actions. That changes what infrastructure is required around the agent.

The developer is no longer the per-line governance mechanism. The architecture has to live somewhere the agent can see, and somewhere the system can enforce, without depending on a human watching each step.

## Why autonomous execution increases governance pressure

An autonomous agent doing real work compounds three problems at once:

- Throughput — more code, more PRs, more files touched per unit time
- Scope — multi-file, multi-repo, multi-tool changes in a single task
- Continuity — long-running sessions with remediation loops that themselves modify the codebase

None of those are bad in themselves. They are exactly what makes autonomous agents valuable. They also mean that any architectural rule which depends on a human reading each change before it lands quietly stops being enforced.

Autonomous execution is not the failure mode. Autonomous execution without an enforceable architectural boundary is.

## Where architectural drift emerges

The recurring patterns we see when autonomous agents operate without a governance layer:

Multi-repo edits

### Cross-repo drift

The agent makes a locally-rational change in one repo that breaks an invariant in another. No single reviewer sees both sides.

Dependency introduction

### Forbidden dependencies

Libraries the team has explicitly deprecated reappear in agent-generated code because the deprecation lived in an ADR the agent never read.

Framework leakage

### Framework boundary crossings

Internal abstractions leak into surfaces they were never meant to touch — the agent picks the shortest path, not the architectural one.

Undocumented conventions

### Tribal-knowledge violations

The senior engineer remembers why this pattern exists. The agent does not. The fix is to write the rule down once and enforce it everywhere.

Remediation patterns

### Inconsistent fixes

The same problem gets a different fix each time it appears, depending on which agent ran and what context it had. Long-term, the codebase loses coherence.

Provenance loss

### Which decision was applied?

After the fact, nobody can reconstruct which architectural decisions the agent considered, which it overrode, and which it never saw.

## How Mneme fits into agent workflows

Mneme does not run as an agent. It runs as a deterministic governance layer next to the agent — a function the workflow calls before file writes, before commits, and at CI time.

- ADR import — bring existing architecture decision records into the governance corpus so they become enforceable, not just documented
- Deterministic retrieval — same task, same state, same architectural context. No probabilistic ranking, no context-window dilution
- CI enforcement — deterministic verdicts on every PR, regardless of which agent generated the change
- Hook / runtime checkpoints — enforcement at the agent’s execution boundaries, not only after the fact

## Governance before generation vs review after execution

Most existing AI-assisted tooling operates after the agent acts. Mneme operates before.

#### Review after execution

- PR-stage code review
- Post-generation linting
- Runtime evaluation
- Drift detection after merge
- Incident-style remediation

#### Governance before generation

- ADR-derived constraints
- Architectural invariants
- Verification contracts
- Hook + CI gates
- Deterministic verdicts

Both layers matter. The difference is leverage: pre-generation governance prevents the violation; post-generation review catches what slipped through. With autonomous agents, the ratio between those two has to shift — the queue cannot carry the weight on its own.

## Example workflow

A concrete picture of what a governed Devin workflow looks like end-to-end:

01
Devin starts the task Receives the issue, plans the multi-step approach, begins editing files across the relevant surfaces.
02
Mneme retrieves relevant decisions Deterministic lookup against the compiled ADR corpus — the architectural rules that apply to this file set and this kind of change.
03
Pre-write check Before the agent commits a file, Mneme validates the change against the constraints. PASS, WARN, or FAIL with a provenance trace.
04
Devin opens the PR With the structured governance verdict attached as part of the PR description, not buried in the prose.
05
CI enforcement The same compiled rules run in GitHub Actions. Merges are blocked on FAIL; WARNs surface for reviewer judgment.
06
The reviewer reviews judgment, not constraints Architectural compliance is already verified. The reviewer focuses on whether the approach is the right one — the work humans are best at.

## Works alongside the rest of the agent ecosystem

The point of a repo-native governance layer is that the rules do not depend on which agent ran. The same Mneme corpus enforces the same architectural decisions whether the change came from Devin, Claude Code, Cursor, or a CI-triggered autonomous workflow.

Native integration

### Claude Code

Hook-level enforcement via SessionStart, PreToolUse, and PostToolUse.

Native integration

### Cursor

Rules export from the Mneme decision corpus into Cursor’s rules system.

CI gate

### GitHub Actions

Deterministic governance verdicts on every PR — same rules across every agent.

Ecosystem

### Devin alongside the rest

Full list of coding agents, frameworks, and execution surfaces Mneme operates next to.

## Architectural governance for autonomous coding workflows

Open-source. Repo-native. Works alongside Devin and every other AI coding agent on the codebase — the same compiled architectural decisions enforced at hook, commit, PR, and CI.

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