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
What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .
By Chinmay Kakatkar
The article "How to Solve the Right Problem in the Age of Agentic AI" presents a practical framework aimed at reducing uncertainty before agents accelerate implementation. It offers guidance on identifying and addressing the most relevant problems in the context of increasingly autonomous AI systems.
By Mike Huls
The article "Beyond RAGs: Building Actually Truthful AI Harnesses" discusses the limitations of Retrieval-Augmented Generation (RAG) systems, emphasizing that retrieval alone does not guarantee evidence for AI claims. It explores methods for constructing AI systems that can substantiate their statements, moving beyond simple retrieval to more robust proof mechanisms. The piece highlights the importance of developing AI that can verify its own outputs rather than merely retrieve information.
By Ari Joury, PhD
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.
By Conor O'Sullivan
The article titled "An Introduction to Jev" discusses an AI system that focuses on making decisions rather than generating text. It highlights Jev’s unique approach to decision-making within the broader context of AI development. The piece was originally published on Towards Data Science.
By Thomas Reid
Towards Data Science has released a video showcase titled "Introducing ShipAI," which highlights real‑world AI work. The post announces this new visual resource and its focus on practical AI applications. It is positioned as a first look into the platform’s capabilities.
By TDS Editors
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
The article titled "Is Agentic AI Just Automation?" argues that many so‑called agents are merely flowcharts in disguise. It explains why this misconception exists and suggests what kinds of systems should be built instead to achieve true agentic AI.
By Prashant Mudgal
Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on Towards Data Science .
By Eivind Kjosbakken
Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.
By Adam Zewe | MIT News