{
  "id": 4563591,
  "title": "Are We Forgetting Software Engineering in the Race Toward AI/ML?",
  "url": "https://urgent.news/2026/08/31/are-we-forgetting-software-engineering-in-the-race-toward-ai-ml",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-31T03:18:10.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/jonathancodes365/are-we-forgetting-software-engineering-in-the-race-toward-aiml-jpp"
  },
  "original_language": "en",
  "account": "In the realm of technology, there seems to be a growing trend of focusing solely on AI/ML engineering, often at the expense of traditional software engineering principles. This perspective was shared by a community member in a DEV Community discussion, sparking debate about the relationship between AI/ML engineering and software engineering. According to the author, it's understandable why developers might prioritize AI/ML, given its exciting nature, but they pose a crucial question: why is AI/ML engineering being viewed as a separate entity from software engineering?\n\nThe article highlights that many developers seem to follow a narrow path towards AI/ML, skipping over the fundamental aspects of software engineering such as backend development, databases, networking, operating systems, system design, APIs, deployment, testing, distributed systems, among others. The author argues that these fundamental aspects are vital for any AI model to thrive, necessitating data storage, pipelines, applications, APIs, and robust backend infrastructure. Without this foundation, the author suggests that AI/ML engineering may be akin to building a house on sand, destined to collapse under real-world pressures like unexpected failures, scaling issues, security vulnerabilities, and inefficient infrastructure.\n\nThe author proposes an alternative path: starting with programming, followed by computer science fundamentals, software engineering, backend/systems, data, ML, and finally AI. This path emphasizes the importance of a strong foundation in software engineering principles, which can support the specialization in AI/ML without compromising the overall system's robustness. The author concludes by reiterating the question: are developers specializing too early in AI/ML and neglecting the essential software engineering principles that underpin all technological systems? The author invites readers to share their thoughts on this matter.",
  "summary": "First of all, I warmly welcome everyone out there in the DEV Community. [Completely open for discussion — drop your thoughts below.] From my perspective, it feels like everyone is racing towards AI/ML. The moment someone says they want to become an AI/ML Engineer, the conversation immediately shifts towards: Python → ML → Deep Learning → LLMs → Latest AI Tools And thinking about it, well, it’s…",
  "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."
}