Replies to comments on my "LLMs are eroding my career" post
human-in-the-loop.bearblog.dev
June 8, 2026
7 min read
🔥🔥🔥🔥🔥
57/100
Summary
A viral post about the impact of large language models (LLMs) on careers received numerous comments. The author plans to selectively respond to comments in a consolidated manner to avoid overwhelming thread depths on platforms like HN and Reddit.
Key Takeaways
- LLMs are not fully automating tasks related to local tax codes and specific accounting processes, which still require human expertise.
- The increasing capability of LLMs has reduced the need for collaboration with experienced coworkers, leading to concerns about job security and the commoditization of professional skills.
- The author has adapted to the rise of AI by enhancing their skills and becoming an "AI-native engineer," focusing on improving agentic tooling and conducting adversarial code reviews.
- There is apprehension about the future of the profession as LLMs continue to improve, potentially leading to a significant reduction in demand for specialized roles.
Community Sentiment
Positives
- The rapid improvement of AI tools suggests they will soon be capable of handling complex engineering tasks, potentially transforming the software development landscape.
- The cost of AI output is expected to drop significantly in the coming years, which could democratize access to advanced AI capabilities for more developers.
- The ongoing funding for AI advancements indicates a strong belief in the continued evolution of these technologies, suggesting a bright future for AI applications.
Concerns
- There are concerns that AI maximalism relies on assumptions about the pace of AI improvement that may not hold true, indicating potential instability in the field.
- The perception that LLMs can replace knowledge workers raises ethical and economic concerns about job security and the future of work in the software industry.
- Critics argue that the focus on surface-level functionality of AI tools may lead to neglect of underlying quality, which could result in more software failures.
