Developers often struggle to get actionable results from AI coding assistants. This guide provides 7 detailed prompts, designed at the Principal Engineer level, that walk AI step by step through code review, debugging, testing, architecture, and productionization. Copy, paste, and adapt these prompts to ship scalable, secure, production-ready software with AI support.
In the final part of our Hugging Face LLM training series, learn how to publish your model to Hugging Face Hub and create a live demo so anyone can use it instantly.
In Part 2 of our Hugging Face series, you’ll fine-tune your own AI model step by step. Learn how to load datasets, train with the Trainer API, and save your very first custom LLM.
Kickstart your AI journey with Hugging Face. In this beginner-friendly guide, you’ll learn how to set up, run your first model, and prepare a custom dataset for fine-tuning.
Discover how the 2017 paper Attention Is All You Need introduced Transformers, sparking the AI revolution that powers ChatGPT, Claude, Gemini, and today’s LLMs.
OpenAI just launched ChatGPT Go, a new low-cost plan priced at ₹399/month—India-only for now. You get big bumps over Free (notably ~10× message and image limits, file uploads, and longer memory) while Plus keeps the heavier tools (Deep Research, Sora, Agent Mode). Here’s how Go compares to Free/Plus/Pro, who it’s for, and whether you should switch.
Running large language models (LLMs) locally is easier than ever, but which tool should you choose? In this guide, we compare Ollama, vLLM, Transformers, and LM Studio—four popular ways to run AI on your own machine. Whether you want the simplicity of a command line, the flexibility of Python, the performance of GPU-optimized serving, or a sleek GUI, this showdown will help you pick the right workflow for your needs.
Experiment tracking tools often slow down research with heavy configuration and infrastructure setup. RexF flips the script by offering zero-configuration reproducibility with just a single decorator. Here’s why it’s quickly becoming a favorite among researchers and data scientists.
Picking an AI coding partner in 2025? GPT-5 often wins fast bug-fixing and tool-heavy workflows, while Claude’s Sonnet-4 earns praise for steady, requirement-faithful edits in big repos. Benchmarks like SWE-bench show both at the top; developer reports vary. The real answer: pilot on your code and choose what ships green tests most reliably.
Boost your Java microservices with high-performance distributed caching. This guide shows you how to use JCacheX to implement a robust caching strategy for your applications running on Kubernetes. Learn to dramatically improve speed and scalability, ensuring your services handle heavy loads with ease and efficiency.