Maintaining architectural intent in agent-first workflows
Preserving system-level decisions, constraints, and engineering standards as AI coding agents plan and generate code. Start with the practical guide, then go deeper on why intent decays and what keeps it enforced. Browse all insights.
Microsoft's AI Decision Brief: Where Does Architectural Intent Live?
Microsoft's CTO says programming is moving from instructions to intent. Agent governance covers who may act. Architectural intent decides what a change may be.
Conway's Law in the Age of AI Coding Agents
Systems still mirror how organizations communicate. AI coding agents are a new participant who never attended the architecture meeting.
Why Agent-First IDEs Need Architectural Invariants
Delegated tasks need shared constraints. Invariants have to be encoded, retrieved, and enforced, not left in a developer’s head.
Mneme vs Cursor Rules
Cursor Rules are per-repo text files. Mneme HQ is a structured decision memory with a precedence engine and hook-level enforcement. The difference matters when rules conflict or the team grows.
Why Context Alone Doesn’t Prevent Architectural Drift
Better retrieval and larger windows help agents remember more. Architectural drift is caused by local optimization, not forgetting, so context alone does not stop it.
Constraint Decay Is Why Coding Agents Need Architectural Governance
An arXiv paper quantifies it: agents satisfy loose specs but lose ORM rules, framework conventions, and architectural fidelity as structural requirements accumulate.
AI Coding Agent Guardrails: Which Layers Actually Hold
A reference taxonomy of guardrails: runtime, prompt, policy, architectural, and engineering-standards. What each layer catches, what it misses, and why architecture needs enforcement at edit time.
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, and enforcing that intent is the next hard problem.
Shared Memory Is Not Shared Intent: Why AI Coding Teams Need Governance
A shared memory layer lets every agent read the same context. That solves distribution, not governance, and better shared memory can amplify architectural drift.
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.