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.
The article argues that AI agents have surpassed human capacity in code production, prompting a shift in perspective from merely using AI to actively employing it. It highlights how this development has altered the author's view on AI’s role in software development. The piece suggests that embracing AI as a collaborator is now essential.
Find the optimal way to interact with your coding agents The post How to Find the Optimal Coding Agent Interface appeared first on Towards Data Science .
Perform non-programming tasks with coding agents The post How to Apply Coding Agents to Non-Programming Tasks appeared first on Towards Data Science .
Improve coding agent productiveness with refactored code The post How to Refactor Code with Claude Code appeared first on Towards Data Science .
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 .
The article titled "Build Your First AI Agent with One Tool Call" introduces beginners to AI agents, presenting the first part of a series. It focuses on the foundational steps required to create an AI agent using a single tool call. The post is published on Towards Data Science and serves as an introductory guide for newcomers to the field.
The article "How to Effectively Solve 100+ Tasks with Claude Code" discusses strategies for working more efficiently with coding agents. It focuses on practical approaches to manage and complete a large number of tasks using Claude Code. The post was originally published on Towards Data Science.
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
The article outlines four practical applications of AI for PhD students: locating relevant citations, consolidating code snippets, fact‑checking research claims, and preparing for the thesis defence. It highlights how AI tools can streamline the research process and improve the quality of academic work.
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.
One near miss, four months of running agents, and the question almost nobody is asking: what are you supposed to do while the AI writes the code? The post AI Made Me 5x Faster. It Also Made Me 5x Wors...
If you are a programmer and you don't feel "special" anymore, you are not alone The post The Era of No-Code AI: What You Need to Know appeared first on Towards Data Science .