-
How to Answer AI System Design Interview Questions
The interview moved from Design YouTube to Design ChatGPT. Here's the framework.
By Nate Rosidi, KDnuggets Market Trends & SQL Content Specialist on August 19, 2026 in Career
-
5 Tools for Building and Deploying AI Agents in Production
This article walks through five tools, one for each layer of the stack from building the agent's logic to running all of it at scale.
-
Run Qwen3.8-27B as a Local AI Coding Agent in Just 3 Commands
Download Ollama, pull and serve Qwen3.8-27B, and launch it with OpenCode using just three command lines.
-
5 Things Vibe Coding Gets Right and 5 Things It Gets Wrong
Is vibe coding the future of programming or a shortcut to bad code? Let’s look at what it gets right and wrong.
-
What Can I Actually Do with a Small Language Model?
But by keeping these limits in mind, and planning for them, we can effectively use these small, local models for the following broad operations scenarios.
-
5 Python Libraries That Make Data Cleaning More Enjoyable
This article covers five Python libraries that turn tedious data cleaning into something expressive and genuinely enjoyable.
By Bala Priya C, KDnuggets Contributing Editor & Technical Content Specialist on August 17, 2026 in Python
-
How to Build a Simple AI Web Scraper with Python
Turn any webpage into a lightweight LLM-powered QA engine by cleaning HTML, converting content to Markdown, and returning focused answers while reducing token usage.
-
5 Fun Agentic AI Papers to Read
If you read only five papers on AI agents, make them these.
-
Building a Streaming Local AI Agent
Streaming gets used in two different ways when people talk about AI agents. Straighten out your understanding here.
-
Constraining Output Space for SLM Narrow Automation Optimization
This article will kick off a series on narrow automation optimization for SLMs, and as the first entry will cover one of the more most useful techniques for doing so: constraining the output space instead of parsing generated text.
-
Building an End-to-End Data Science Portfolio Project
Most portfolios stop at a notebook. Take yours all the way.
-
5 Easy Ways to Install Python on Windows
Learn how to install Python on Windows using the Python Install Manager, WinGet, uv, Miniconda, or the official Python installer, and choose the best setup for beginners and Python development.
-
The Ultimate Guide to Contributing to Open Source Projects
This guide walks through what contributing to open source projects actually covers, how to pick a project that will actually respond to you, the exact git mechanics, and more.
-
3 Visual Proofs of the Central Limit Theorem to Build Your Intuition
To build your intuition, this article shows three visual proofs that the classic bell curve appears in myriad situations.
-
New Free eBook: Understanding Agentic AI, an Executive Briefing
Written for CEOs, CTOs, CIOs, and technology executives, our new free ebook "Understanding Agentic AI: An Executive Briefing" walks through the components every real agentic system is built from.
-
Specification Engineering: The New Skill After Prompt Engineering
Prompt engineering taught us how to ask better questions. Specification engineering teaches us how to define better work.
-
Top 10 AI Influencers of 2026
Ten AI influencers who are actually shaping 2026, from safe superintelligence to AI-native search. Here is who to follow and why.
-
Small Language Models with Hugging Face transformers Library + smolLM3
Running a 70B model in production is expensive, and for many tasks, unnecessary. If you're building a focused pipeline, a well-trained 3B model will match or beat the 70B on your specific task at a fraction of the cost.
-
5 Free Courses to Learn Modern AI and LLMs
Learn how to use generative AI at work, build RAG and agentic apps, fine-tune models, work with the Hugging Face ecosystem, and prototype AI products with hands-on resources.
-
Beyond Bots: Rethinking AI Support with a Hybrid AI Architecture
Learn how blending RAG and fine-tuning creates more effective AI support experiences.
-
The Minimal AI Engineer Toolkit for 2026
Discover the six essential tools AI engineers need in 2026 to build and deploy production-grade autonomous systems.
-
7 Best Web Crawling Tools and APIs in 2026
Learn about the best web crawling tools for collecting website content, crawling subpages, generating clean web data, and powering AI agents.
-
Getting Started with GitHub Agentic Workflows
GitHub Agentic Workflows are in public preview. Find out all about them here.
-
Turn Any CSV into an Executive Report with Python and AI
Learn to implement a repeatable pipeline that cleans a CSV, finds the story, and writes it up.
-
Honest Abacus AI Review: ChatLLM, DeepAgent, AI Studio & More
The All-In-One AI Powerhouse: A Comprehensive Review of Abacus AI’s Full Ecosystem
An in-depth look at how the platform integrates 100+ AI models, autonomous agents, and a complete developer suite into a single, cost-effective workflow for teams and power users.
-
I Replaced Pip, Virtualenv, and Poetry With uv: Here’s Why
uv is making my life easier by giving me one fast tool for package installation, virtual environments, lock files, Python versions, and running project commands.
-
7 Approaches to Reduce Inference Latency in Your LLM Workflows
From quantization to speculative decoding, here are seven engineering strategies to ship faster, more responsive generative AI applications in production.
-
Does MiniMax Agent Actually Make Work Easier?
Read about MiniMax's own architecture, and see how it runs a real task against the actual API. Learn the pieces of the MiniMax story that weren't covered in the launch post.
-
A Guide to Saving Token Usage with Multi-Agent AI
Scaling up and streamlining a multi-agent architecture doesn't necessarily entail escalated costs if you know how to properly implement these four strategies for saving token usage.
-
KDnuggets Weekly Roundup: Build and Deploy Your First Autonomous Agent • 7 Machine Learning Algorithms That Still Matter
A Beginner's Guide to Working with Claude Design • 5 Best AI Tools for Data Analysis You Should Try in 2026 • 5 Books That Will Deepen Your Understanding of Large Language Models • Is KimiClaw a Useful Tool?
-
Building Voice-Controlled AI Agents
Building a voice-controlled AI agents isn't hard, this article breaks the pipeline into its real components: streaming speech recognition, turn detection, streaming generation, interruption handling, and tool calling under voice constraints and shows what each one is responsible for.
-
5 Books That Will Deepen Your Understanding of Large Language Models
Check out these five books on building, fine-tuning, and deploying large language models.
-
A Beginner’s Guide to Working with Claude Design
Claude Design is a research preview under Anthropic Labs, powered by Claude Opus' vision capability, generating interactive prototypes with working navigation, embedded video, voice input, and 3D elements.
-
7 Machine Learning Algorithms That Still Matter
Discover 7 essential machine learning algorithms that every data scientist should know before reaching for LLMs and generative AI, with simple explanations and practical Python code.
-
What Professionals Should Know About Data Science and AI, According to Harvard Business School Online
Learn why clear business goals, data quality, simple models, careful validation, realistic costs, and human judgment matter more than chasing the latest technology.
-
5 Must-Read Resources for Mastering Small Language Models
Five resources covering SLM architecture, fine-tuning, agentic workflows, and local deployment for data professionals.
-
An Introductory Guide to Practical Constraint Decoding
With this introductory guide to practical constraint decoding, you'll no longer need to beg your model to "output valid JSON without including any markdown."
-
5 Best AI Tools for Data Analysis You Should Try in 2026
Discover five of the best AI tools for data analysis that can clean data, write code, create visualizations, and generate insights faster.
-
Is KimiClaw a Useful Tool?
Compare KimiClaw's cloud-hosted AI agent platform against self-hosted OpenClaw across setup, privacy, and automation capabilities.
-
7 Steps to Building and Deploying Your First Autonomous Agent
This article shows you up all the steps in building and deploying your first autonomous AI agents from start to finish.
-
KDnuggets Weekly Roundup: Week of July 20, 2026
Top 5 MCP Servers for High Performance Agentic Development • 10 Newsletters Keeping You Ahead in AI • Kaggle + Google’s Free 5-Day Agentic AI Course • Language Model Hallucination Evaluation with GraphEval
-
Language Model Hallucination Evaluation with GraphEval
Turning the key principles and methodological stages of GraphEval into a simulated practical scenario to better understand its usefulness and key implications in understanding and combating LLM hallucinations.
-
5 Key Concepts Behind Agentic AI Every Engineer Must Understand
This article walks through and explains the five ideas that actually hold agentic systems together.
-
Getting Started with OmniVoice-Studio
OmniVoice Studio is built on a premise that everything runs on your hardware. Voice cloning, video dubbing, real-time dictation, voice design, all of it local, all of it free for personal use, no API key required, no usage counter.
-
7 Best Claude Code Alternatives for CLI Agentic Coding
Discover seven cheaper, faster Claude Code alternatives for CLI agentic coding, with open-source tools, local models, MCP support, and better context control.
-
Kaggle + Google’s Free 5-Day Agentic AI Course
Google and Kaggle's 5-Day AI agents course is now freely available to everyone.
-
10 Newsletters Keeping You Ahead in AI
Cut through AI noise with 10 curated newsletters covering daily news, technical research, policy, and builder tools.
-
Run the Mythos Enhanced Coding Model Locally with llama.cpp and Pi
Run Qwythos-9B-Claude-Mythos-5-1M locally with llama.cpp, connect it to Pi coding agent, and build fast local coding workflows using MTP speculative decoding and an OpenAI-compatible API.
-
5 Free Courses to Go From AI Beginner to Practitioner
Follow this free five-course roadmap to build real AI skills, from classical algorithms to training LLMs from scratch.
-
A Beginner’s Guide to Setting Up Claude Code for High Performance Agentic Programming
This article walks through the actual configuration, permissions, hooks, and command habits that separate a fresh install from a setup that holds up under real, sustained agentic work.
-
Top 5 MCP Servers for High-Performance Agentic Development
Here are five that are genuinely worth wiring into a high-performance agent development setup, chosen for what they do to an agent's actual capability rather than their star count.
-
Could Your AI Systems Already Be High-Risk Under the EU AI Act?
Access the on-demand webinar to understand what the latest guidance means for your AI governance program and what your organization should do next.
-
KDnuggets Weekly Roundup: Week of July 13, 2026
Stop Using If-Else Chains: Use the Registry Pattern in Python Instead • 5 Real-World SQL Projects to Build Your Data Portfolio • 10 YouTube Channels Keeping You Ahead in AI • Structured Language Model Generation with Outlines
-
Git Worktrees for AI Development
A Git worktree is a separate directory checked out from the same repository. You can have as many as you need, each on its own branch, all coexisting simultaneously on your filesystem.
-
5 FREE Resources on Agentic AI
Here are 5 curated resources to help you progress your agentic AI learning for FREE.
-
Working with Pi Coding Agents
The most interesting thing about Pi isn't any single feature; it's that the project treats "what we didn't build" as documentation worth writing, which is rare enough on its own to take seriously.
-
10 YouTube Channels Keeping You Ahead in AI
Explore 10 YouTube channels for AI engineers covering paper breakdowns, coding tutorials, and industry analysis.
-
-
7 Python Frameworks for Orchestrating Local AI Agents
This article contains seven Python tools that engineers are actually using in 2026 to build, coordinate, and run agents on local infrastructure.
-
Getting Started with Conductor for Gemini CLI
Conductor is a Gemini CLI extension built to fix your context problems. Learn all about it here.
-
12 Ways to Reduce LLM Latency and Inference Costs in Production
Scaling LLMs isn’t about adding GPUs. It’s about removing wasted work from every request.
-
Structured Language Model Generation with Outlines
Outlines is an open-source library that introduces deterministic certainty into LLMs' output generation process for better, more reliable generation of structured outputs.
-
5 Real-World SQL Projects to Build Your Data Portfolio
Build a stronger data portfolio with these practical SQL projects covering customer churn, data warehousing, sales analysis, banking segmentation, and healthcare analytics.
-
Fine-Tuning Explained for Noobs (How Pretrained Models Learn New Skills)
You don't need a PhD to understand fine-tuning. This article explains how pretrained models learn new skills through fine-tuning.
-
Local Video Summarization Pipeline: Processing Frames with SmolVLM2-2.2B
SmolVLM2-2.2B sits at a genuinely useful point on the capability-size trade-off curve; small enough to run on a single consumer GPU, capable enough to produce video summaries that are actually useful for real workflows.
-
Running OpenClaw with Ollama
This article covers the full path from zero to a running private research assistant on Telegram, including configuring the context length correctly, connecting the channel, enabling web search, and deploying it headlessly in Docker.
-
7 Steps to Automating Descriptive Statistics with Python
Stop writing mean() and std() for every column. Learn how to automate descriptive statistics in Python and generate publication-ready summary tables in just a few steps.
-
How to Clean Messy CSV Files with Python: A Beginner’s Guide
Learn how to clean CSV files with pandas by handling missing values, duplicate rows, messy text, wrong data types, mixed date formats, invalid emails, and currency values.
-
SQL vs Pandas vs AI Agents: Which Solves Analytics Problems Best?
Same three analytics problems, three tools, eight dimensions, measured with real execution times and real agent prompts.
-
Zero-Shot Local Document Parsing with Gemma 4: Treating PDFs as Images
Treating PDFs as images and feeding those images to Gemma 4 dissolves the scanned-versus-digital distinction that makes every text-extraction pipeline fragile. Fix that.
-
10 Probability Concepts for Machine Learning Explained Simply
A model is almost never 100% sure of anything. These 10 probability concepts explain how it makes decisions anyway.
-
Data Scientists Are Becoming AI Managers, Not Model Builders
The role is shifting from building models to managing them.
-
Getting Started with Hugging Face ML Intern: Your First ML Agent
You describe the model. It writes the code, runs the training, and ships the checkpoint. Welcome to ML Intern.
-
5 Ways Small Language Models Are Powering Next-Gen Agents
This article looks at five concrete ways SLMs are showing up inside next-generation agents right now, from the research backing them to the tools and numbers worth knowing if you're deciding whether your next agent needs a frontier model at all
-
Getting Started with the Claude API in Python
In this article, you'll learn how to use the Claude API in Python, make your first request, and handle responses with the official SDK.
By Bala Priya C, KDnuggets Contributing Editor & Technical Content Specialist on July 3, 2026 in Python
|
