The world’s leading publication for data science, AI, and ML professionals.

Building Successful AI Apps: The Dos and Don’ts

Our weekly selection of must-read Editors' Picks and original features

As businesses and organizations scramble to find good use cases for AI, several crucial questions consistently emerge: do you even need AI-powered tools? How should you go about building or integrating them into your existing workflows? And how will you know if the effort was worth it?

Whether you’re an independent practitioner or part of a larger team trying to make sense of this emerging technology, you’ll find concrete and actionable insights in the lineup of articles we’ve selected this week. They each tackle the nuts and bolts of building AI apps and leveraging their potential for well-defined goals, while avoiding common pain points.

While these posts zoom in on specific topics and business problems, they all offer a pragmatic, accessible approach, making them useful for readers across a wide spectrum of backgrounds and experience levels. Let’s dive in.

Photo by Krišjānis Kazaks on Unsplash
Photo by Krišjānis Kazaks on Unsplash

Branching out into the world beyond AI apps, we’ve selected a few more recommended reads we thought you’d enjoy—from a beginner-friendly intro to LLMs to an in-depth analysis of data strategies.


Thank you for supporting the work of our authors! As we mentioned above, we love publishing articles from new authors, so if you’ve recently written an interesting project walkthrough, tutorial, or theoretical reflection on any of our core topics, don’t hesitate to share it with us.

Until the next Variable,

TDS Team


Related Articles