Architectural governance
Architecture is the set of decisions that must hold while code is written. These essays cover what architectural governance is, why intent decays as agents generate, and what deterministic enforcement looks like before a change lands. Browse all insights.
Review Is Not Governance
CodeRabbit helps review AI-generated code. Mneme helps govern what the AI generates in the first place. Two different layers of the same problem.
Memory Is Not Governance
The category conflates memory, context, retrieval, and governance into one word. Memory systems optimize recall. Governance systems optimize constraint enforcement. Different jobs, different math, different failure modes.
Why Observability Is Not Governance
Observability tells you the agent violated architecture. Governance helps prevent the violation from being proposed in the first place. Visibility is not control — and dashboards without enforcement are operational archaeology.
Why RAG Fails for Architectural Governance
Retrieval-augmented generation works well for documentation lookup. It breaks down entirely when you need authoritative, precedence-aware constraint enforcement. Here’s why.
Why Context Alone Doesn’t Prevent Architectural Drift
Context engineering improves recall. It does not enforce architectural constraints. Better retrieval, larger windows, and richer memory layers help agents remember more — but architectural drift is caused by local optimization, not forgetting.
Constraint Decay Is Why Coding Agents Need Architectural Governance
A new arXiv paper quantifies it: agents satisfy loose specs but lose ORM rules, framework conventions, and architectural fidelity as structural requirements accumulate.
Why AI Architectural Governance Needs Precedence Semantics
When two ADRs overlap, prompt rules resolve by attention, RAG resolves by retrieval score, and PR review resolves by whoever was looking. Precedence semantics — status, supersedes, scope, priority, time — is the missing layer that makes governance deterministic.
Runtime Verification Is Not Architectural Verification
The AI infrastructure market is converging on sandboxes, traces, approvals, and policy enforcement. Those protect a single agent run. They do not prevent systems from drifting architecturally over time. Architectural verification is a different infrastructure category.
Autonomous Code Remediation Requires Architectural Governance
Autonomous remediation loops cannot stabilise without deterministic architectural constraints. Faster generation accelerates drift. Governance must become infrastructure.
The Governance Perimeter Is Moving to the Endpoint
On-device agents are usually framed as a latency or privacy story. The deeper shift is architectural — as autonomous execution moves onto the endpoint, the centralized control plane that hosted-AI governance assumed quietly disappears. Enforcement has to collapse toward the repository.
Beyond Security by Design: The Rise of Governance by Design
Software designs security, privacy, and safety in rather than bolting them on. Autonomous agents make governance the next ‘by design’ discipline — enforced in the architecture, not reviewed after deployment.
Artifacts Are Not Governance
A screenshot can prove the agent opened the browser. It cannot prove the agent respected your architecture.
Prompt Engineering Is Not Governance
Prompt templates can nudge an LLM toward better output. They cannot enforce architectural invariants, resolve decision conflicts, or prevent drift across a multi-engineer codebase.
Spec-Driven Development Still Needs Architectural Governance
Spec-driven development replaces vibe coding with a structured intent-to-spec-to-code workflow. But a feature spec does not define which architectural decisions must hold while the agent implements it. That missing layer is governance.
AI-Native Engineering Has an Intent Debt Problem
As agents write more code, the real risk is not just technical debt. It is stale, implicit, unenforced intent. The next bottleneck in AI-native engineering is intent enforcement.
Models Are Temporary. Architectural Intent Is Not.
Models change. Agents change. IDEs change. Architectural intent should not. The case for keeping AI governance outside the model — and the second kind of lock-in (governance lock-in) that most teams discover too late.