Simon Willison reflects on his experience with coding agents, noting that while they enable impressive feats, they also complicate software engineering. He emphasizes that fully harnessing their capabilities demands exceptional discipline and deep knowledge. The article highlights the dual nature of coding agents as both powerful tools and challenging additions to development workflows.
The article "How to Work with AI Coding Agents" offers a practical guide aimed at improving code quality rather than merely increasing quantity. It focuses on strategies and best practices for effectively collaborating with AI coding tools to produce better code. The post was originally published on Towards Data Science.
Simon Willison reflects on the emotional impact of AI tools that can produce code quickly, noting that many developers experience an initial sense of disheartenment. He argues that recognizing the shift from coding to higher‑level problem solving allows experienced engineers to leverage new tools and add greater value. Willison emphasizes that software engineering has always faced rapid change, so adapting to AI is part of the profession’s ongoing evolution.
The article discusses the essential skill of effectively instructing coding agents and verifying their changes. It highlights that while line‑by‑line code review is one method, it is not the most efficient way to validate software changes. The focus is on confidently guiding agents and confirming correct implementation without exhaustive inspection.
Apply long-running coding agents to become a more productive engineer The post How to Run Claude Code Agents for 24+ Hours appeared first on Towards Data Science .
arXiv:2606. 21894v2 Announce Type: replace-cross Abstract: As coding agents are rapidly changing software engineering, a natural question is: what are the core skills needed by future software engineers?
Optimise how you interact with your coding agents The post How to Organize All of Your Coding Agent Tasks appeared first on Towards Data Science .
Simon Willison reflects on the evolving role of software developers in the age of AI, noting that while AI can produce high‑quality code, it also enables poor execution that leads to project failures. He argues that the industry is beginning to recognize the continued need for human collaboration and expertise to truly innovate. The piece highlights the tension between automation and the essential human element in software creation.
Perform non-programming tasks with coding agents The post How to Apply Coding Agents to Non-Programming Tasks appeared first on Towards Data Science .
By Ryan Lopopolo, Member of the Technical Staff
Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on Towards Data Science .
How coding agents use tools, memory, and repo context to make LLMs work better in practice
