Source URL: https://simonwillison.net/2025/Jul/3/table-saws/
Source: Simon Willison’s Weblog
Title: Table saws
Feedly Summary: Quitting programming as a career right now because of LLMs would be like quitting carpentry as a career thanks to the invention of the table saw.
Tags: careers, ai-assisted-programming, generative-ai, ai, llms
AI Summary and Description: Yes
Summary: The text draws an analogy between the impact of large language models (LLMs) on programming and the impact of table saws on carpentry, suggesting that professionals should not abandon their careers but rather adapt to new tools. This perspective is significant for those in AI and software development as it emphasizes the ongoing need for skilled professionals even in the face of rapid technological advancements.
Detailed Description: The statement suggests that the rise of LLMs, which can automate certain programming tasks, should not deter individuals from pursuing a career in programming. Instead, it should be seen as an opportunity to enhance skills and productivity, similar to how carpenters have adapted their skills to utilize table saws effectively.
– **Adapting to Technology**: Just as carpenters have incorporated table saws into their work, programmers should embrace LLMs to improve their workflow and not abandon their profession.
– **Skill Evolution**: The analogy implies that, rather than becoming obsolete, programming skills will evolve, and professionals will need to learn how to work alongside AI tools effectively.
– **Creativity and Problem-Solving**: The core skills of creativity, critical thinking, and complex problem-solving that human programmers bring to the table remain irreplaceable, even in an AI-enhanced environment.
In summary, the text emphasizes resilience and adaptation in the tech workforce, wherein the evolution of tools should lead to enhanced practices rather than fear of job displacement. Security and compliance professionals should note that while tools evolve, the fundamental need for skilled oversight and governance in AI-enabled systems continues to grow. Emphasizing continuous learning and adaptability can be critical in maintaining relevance in rapidly changing fields like AI and software engineering.