{
  "id": 8604162,
  "title": "A decision you didn't write down isn't a decision",
  "url": "https://urgent.news/2026/09/20/a-decision-you-didnt-write-down-isnt-a-decision",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-20T04:09:00.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/derekwang85/a-decision-you-didnt-write-down-isnt-a-decision-16bc"
  },
  "original_language": "en",
  "account": "In the realm of artificial intelligence, a decision made during a conversation is not enough to ensure its persistence. For a decision to truly stick, it must be documented in a file accessible by both humans and AI models. This concept is at the core of architecture decision records (ADRs), which are written records of decisions made during the development process.\n\nThe author, Derek Wang, has witnessed this failure mode multiple times in his experience with AI coding. He explains that a decision made during a conversation may seem securely locked in, but the moment a new session begins, the AI model starts anew without any memory of the previous decision. Consequently, the deviation goes unnoticed until it has spread across numerous files, causing significant issues.\n\nWang identifies three main failures that arise from decisions made only in conversations: memory drift, architecture drift, and repeated-argument drift. Memory drift occurs when the humans remember a decision, but the AI fails to recall it, leading to repeated arguments about the same issue. Architecture drift manifests as small, innocent-looking deviations from the design that accumulate over time, resulting in a codebase that is significantly different from the original intention. Repeated-argument drift occurs when the same debate happens again with each new session, often leading to conflicting decisions within the same team.\n\nTo address these issues, Wang introduces the concept of a single source of truth, a written decision that acts as the ultimate authority for subsequent decisions. This is where ADRs come into play. An ADR is a short document containing essential information about a decision, such as its status, decision-maker, context, decision itself, rationale, consequences, and mitigation strategies. By providing this self-contained slice of history, ADRs ensure that future engineers or models can understand why a particular decision was made, preventing the need for re-litigating the question.\n\nADRs have proven effective in real-world projects, as demonstrated by Wang's methodology project. In this project, 20 ADRs were recorded for trade-domain rules, and another 11 were created for the architecture as SmartQuant started up. These ADRs effectively capture the decision-making process and provide a clear record of the choices made.\n\nIn the AI era, ADRs have evolved from a top-down constraint to a living record of resolved problems. The Swarm-Fed ADR takes this concept further by incorporating decisions made by multiple agents and models during the development process. These resolutions are then formalized as ADRs and integrated into the single source of truth, ensuring that the accumulated knowledge is preserved and accessible to future generations.\n\nIn conclusion, for a decision made during a conversation to truly stick, it must be documented in an ADR. By providing a clear and concise record of the decision-making process, ADRs help prevent memory drift, architecture drift, and repeated-argument drift, ultimately ensuring that the AI system evolves in a coherent and predictable manner.",
  "summary": "AI Harness Engineering · Essay Three · derek wang (derekwang85) The most expensive failure in AI coding isn't a wrong decision. It's a decision that was made, then forgotten, then quietly unmade by the next generation. Here's the raw version of that law: a decision that lives only in conversation does not persist. It evaporates the moment the context window closes. If making it stick matters at…",
  "key_points": [
    "Decisions made in conversations are not enough to ensure persistence.",
    "Architecture decision records (ADRs) document decisions for humans and AI.",
    "ADRs prevent memory, architecture, and repeated-argument drift in AI systems."
  ],
  "editors_take": "Documenting AI decisions in written records, known as architecture decision records, is crucial to prevent drift and ensure that decisions persist beyond conversations, providing a single source of truth for future reference.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}