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.
By Sara A. Metwalli
The article "Bug Detection Blind Spots in AI Coding Harnesses (GStack and Beyond)" reports on 28 debugging experiments that show AI coding tools struggle more with missing information than with code complexity. It highlights that these tools exhibit blind spots when key details are absent, affecting their debugging performance.
By Nhu Hoang
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...
By Gursimar Singh
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.
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 .
By Sara Nobrega
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post I Built a Tool-Calling Agent in Python. Here’s How I Debugged It appeared first on Towards Data Science .
By Abdullahi Dattijo