{
  "id": 2828505,
  "title": "It's OK. Do Your Thing",
  "url": "https://urgent.news/2026/08/23/its-ok-do-your-thing",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-23T16:32:59.000Z",
  "source": {
    "name": "Lobsters",
    "slug": "lobsters",
    "url": "https://buttondown.com/carlton/archive/its-ok-do-your-thing/"
  },
  "original_language": "en",
  "account": "I’ve been hesitant to discuss AI in my reporting. The Stack Report deliberately adopts a measured tone, and yet, the topic is fraught with controversy. The community is divided, with supporters and skeptics often attacking each other. One might think it’s easy to write about AI, but doing so invites criticism from either side. If you’re too enthusiastic, some deem you a booster; if you’re too skeptical, you’re seen as outdated and irrelevant. Most of us are just trying to figure it out, but even expressing that thought can be problematic. Posts meant for other subjects often get hijacked by AI discussions, making it hard to discuss anything else.\n\nThe analogy to historical reporting is apt. In early 20th-century Spanish newspapers, events were often reported inaccurately, with battles happening that never occurred or deaths occurring that never did. The media’s narrative often reflected preconceived notions rather than facts. In the world of AI, the media reports are equally unreliable. Depending on the source, labs are either hailed as billion-dollar successes or about to collapse due to rising costs. The underlying technology might persist, but its practicality could wane if the expenses outstrip the benefits. While Large Language Models (LLMs) are unlikely to disappear entirely, they may change in form. A $100 monthly subscription might seem reasonable now, but if the underlying costs skyrocket, the model’s viability could be questioned.\n\nHistorically, concerns about programmers being replaced have been a recurring theme. In the early days of my career, outsourcing to India was touted as a solution to cheap labor. The premise was simple: programmers are cheap elsewhere, so let’s outsource work. This narrative gained traction, with major publications like The Economist and The Economist urging developers to abandon coding. Despite these warnings, the global IT outsourcing industry now exceeds $640 billion annually, with India contributing over $250 billion. Despite the predictions, software professionals persisted. The sector evolved, with Western developers’ salaries rising alongside the growing demand for software solutions. The challenge remains in accurately specifying software requirements before implementation. Just as waterfall methodologies failed due to the impossibility of fully defining requirements upfront, AI faces similar challenges. The true essence of software development lies in the implementation, not in the initial specification. AI doesn’t change this fundamental truth; it merely adds another layer of complexity to an already intricate process.",
  "summary": null,
  "key_points": [],
  "editors_take": null,
  "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."
}