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    Home » TDS Newsletter: October Must-Reads on Agents, Python, Context Engineering, and More
    Artificial Intelligence

    TDS Newsletter: October Must-Reads on Agents, Python, Context Engineering, and More

    ProfitlyAIBy ProfitlyAINovember 1, 2025No Comments3 Mins Read
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    By no means miss a brand new version of The Variable, our weekly e-newsletter that includes a top-notch choice of editors’ picks, deep dives, group information, and extra.

    A superb month on TDS is one by which we get to share a variety of incisive articles with our readers, masking cutting-edge instruments, foundational information and ML abilities, considerate takes on the state of AI, and career (and other) insights from our top authors.

    By this measure, October was one for the books. This week, we’re thrilled to have fun our most-read and farthest-reaching tales of the previous month: they tackled Python’s most up-to-date launch, the most recent in each context and immediate engineering, and much more. Let’s dive proper in.


    Python 3.14 and the Finish of the GIL

    What’s new in Python-world? Rather a lot, it appears. Thomas Reid‘s complete explainer is right here to assist us unpack the “thrilling enhancements” included within the main launch unveiled just a few weeks in the past, focusing particularly on the promise of a free-threaded (or GIL-free) Python.

    Is RAG Useless? The Rise of Context Engineering and Semantic Layers for Agentic AI

    The constraints of retrieval-augmented technology are well-known by now. Steve Hedden appears at what lies forward for LLM-boosting workflows, and at RAG’s evolution into “ruled, context-aware programs.”

    Immediate Engineering for Time-Sequence Evaluation with Giant Language Fashions

    Can a well-designed immediate be the game-changer for considered one of information scientists’ most ubiquitous duties? Sara Nobrega outlines a number of highly effective methods for leveraging LLMs to enhance time-series evaluation outcomes.


    Different October Highlights

    Don’t miss our different high reads from the previous month, tackling statistics, agentic AI, and robotics, amongst different subjects.

    • Implementing the Fourier Remodel Numerically in Python: A Step-by-Step Information, by Junior Jumbong
    • Learn how to Construct An AI Agent with Operate Calling and GPT-5, by Ayoola Olafenwa
    • Learn how to Construct a Highly effective Deep Analysis System, by Eivind Kjosbakken
    • Learn how to Consider Retrieval High quality in RAG Pipelines: Precision@okay, Recall@okay, and F1@okay, by Maria Mouschoutzi
    • A Newbie’s Information to Robotics with Python, by Mauro Di Pietro
    • How I Used ChatGPT to Land My Subsequent Knowledge Science Position, by Yu Dong
    • Knowledge Visualization Defined (Half 4): A Evaluation of Python Necessities, by Murtaza Ali

    Meet Our Returning Authors

    Simply as we’re thrilled to welcome new contributors to TDS, we’re at all times pleased to see acquainted voices showing in our publication after a hiatus. Working example:

    • Barr Moses revealed a brand new article stuffed with sharp insights on the macro tendencies shaping the way forward for AI.
    • Jingyi Jessica Li (with coauthor Pan Liu) supplied an accessible writeup of their newest analysis on the intersection of statistics, bioinformatics, and medical information science.
    • Robert Constable introduced an accessible, hands-on introduction to constructing a geospatial lakehouse with open supply instruments and Databricks.

    Whether or not you’re an present writer or a brand new one, we’d love to think about your subsequent article — so in the event you’ve just lately written an fascinating venture walkthrough, tutorial, or theoretical reflection on any of our core subjects, why not share it with us?


    Subscribe to Our Publication



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