[D] How do ML engineers view vibe coding?

Reddit r/MachineLearning / 4/1/2026

💬 OpinionSignals & Early TrendsIdeas & Deep Analysis

Key Points

  • The post discusses mixed opinions on using AI for coding, focusing on how it affects workflow speed and the time spent reviewing AI-generated output.
  • It frames the question as a comparison between traditional deterministic software engineering and ML engineering work, suggesting ML engineers may have different perspectives due to their responsibilities.
  • The author aims to understand how ML practitioners feel about “vibe coding” (AI-assisted coding) in their day-to-day professional practice, including under workplace mandates.
  • The content is presented as an open-ended discussion prompt rather than a report of a specific new release or outcome.

I've seen, read and heard a lot of mixed reactions about software engineers (ie. the ones who aren't building ML models and make purely deterministic software) giving their opinions on AI usage. Some say it speeds up their workflow as it frees up their time so that they can focus on the more creative and design-oriented tasks, some say it slows them down because they don't want to spend their time reviewing AI-generated code, and a lot of other views I can't really capture in one post, and I do acknowledge the discussion on this topic is not so black and white.

That being said, I'm sort of under the impression that ML Engineers are not strictly software engineers, even though there may be some degree of commonality between the both, and since that may be the case, I thought I'd hear it from the horse's mouth as to what the ML techies think about incorporating AI usage in their daily professional work, whether or not it's workplace mandate. What's it like?

submitted by /u/EfficientSpend2543
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