The discussion also touches on the evolution of software engineering, noting that it has changed significantly over the past decades even without AI. The importance of continuous learning and adaptability in the face of change is emphasized. Lastly, it is suggested that very low-level work such as OS kernels and firmware, as well as high-level work that involves customer interaction, may be less susceptible to AI disruption.
Key takeaways:
- There is a debate in the tech industry about the impact of AI on programming jobs, with some suggesting that the next generation shouldn't learn coding as it will be done by AI.
- Some believe that no common software engineering roles will be disrupted by AI and that those suggesting otherwise may have financial incentives in promoting AI.
- Others argue that while the nature of software engineering may change due to AI, it doesn't mean people should stop learning to code. They emphasize the importance of continuous learning and adaptability.
- It is suggested that low-level work (like OS kernels, firmware) and high-level work that requires customer interaction are less likely to be disrupted by AI. Also, if AI models remain unstable, infrastructure and testing roles will still be needed.