The latest updates on all JetBrains products and topics
PyCharm product marketing lead with 9+ years in content strategy and go-to-market for B2B/B2C software.
PyCharm 2026.2.1: AI agents now work in your Jupyter notebooks and target the right Python environment, marimo notebooks arrive, plus changes to bundled plugins.
PyCharm's new Agent Environment Coordinator gives AI agents your project's real Python interpreter – lifting task success from 68% to 98% on average.
PyCharm's new Jupyter skill lets AI agents work in a live kernel, so notebooks don't corrupt, state persists, and long jobs wait until execution is completed instead of constantly checking and wasting precious tokens.
We're unbundling and deprecating several low-usage plugins in PyCharm 2026.2. Here's what's changing, why, and what it means for you.
This article provides a guide for developers with basic Python knowledge looking to explore deep learning using PyTorch.
Compare the top object detection models for 2026. YOLOv12, YOLO26, RF-DETR benchmarks, use cases, and selection guidance.
Compare the top Python AI frameworks for 2026. Learn when to use each, their strengths and limitations, and how to choose the right one for your project.
Let's compare the leading agentic AI frameworks in 2026 and explore what each framework does best – click here to find the right framework for your project.
Learn how to build a real-time object detection app using TensorFlow and PyCharm, then deploy it onto the Reachy Mini robot for live object tracking.
Read our guide to LLM evaluation and AI observability, explaining how to monitor, test, and deploy reliable AI agents in production with confidence and control.
Explore key highlights from Python Unplugged on PyTV, our first fully online Python community conference, including talks on AI, open source, Django, and more.
PyTorch vs. TensorFlow in 2026: Compare learning curves, deployment options, and use cases, and get guidance for choosing the right deep learning framework.
