Providing examples in your prompt is a technique known as few-shot prompting . Examples can be a great way to quickly communicate what your desired response should look like - it can often be easier to show with a few examples rather than trying to describe it with words. 'Shots'  is a term taken from the field of machine learning. Each shot is an example given to the model before it performs the task. We often refer to 'few-shot'  and 'zero-shot'  prompting (where you don't

"You're an expert X." "Act as a Y" Role prompting is one of the most widely repeated tips in AI circles. The underlying idea is that if you assign the model a job title or area of expertise, it will respond more like a person who holds that role, making it more relevant, more precise, more expert-sounding. The research on whether that actually holds up is more nuanced than the advice suggests. And the nuance is important if you want to try this out yourself. What is role prom

AI, Machine Learning, Deep Learning, Generative AI, and LLMs are all terms commonly thrown around in tech writing, news and media, but they each refer to slightly different things and shouldn't be used interchangeably... even if they sometimes are. This guide explains what each one actually means, how they relate to each other, and why it matters which is which. What is AI, exactly? Artificial intelligence  is the broadest of the four terms. It describes any computer system

Learn what a context window is, how tokens work, and why they affect your everyday AI use - explained in plain English.

Claude Code is an AI tool that runs in the terminal. For a lot of people, that sentence is enough to put them off. That would be a mistake. While it may have been designed as a coding assistant, it's really just an agent capable of managing your files, using skills, and writing and running code (all by itself) to solve whatever problem you throw at it. Claude Code is one of the more capable AI tools currently available, and you do not need a programming background to get real

Can AI models write Manim code from natural language prompts? I tested Gemini, GPT, Claude, and Kimi to find out what works, what breaks, and why spatial reasoning is the bottleneck.

Modern AI chat tools are powered by Large Language Models (LLMs), which are sophisticated systems trained on vast amounts of text data to understand and generate human-like responses. LLMs like Claude and Gemini don't truly "understand" in the human sense, but they excel at recognizing patterns in language and predicting what text should come next based on your input. This is why the quality of your prompt matters so much. The AI model can only work with what you give it, m

And What Happened to CoT Prompting? Prefer to listen to this article instead? I used ElevenLabs TTS  to create this narration. Check them out using my affiliate link, here . "Think step by step" ...was once great prompt engineering advice, but now seems to have little to no effect. In fact, what if I told you that this technique, at best, has little effect on output quality, and at worst, increases costs, latency, and may even reduce the accuracy of your response? It decreas

Master AI-driven code mapping with this 4-step guide to navigating legacy projects. Turn complex code into clear diagrams and actionable documentation.

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Learn to build AI-powered apps using LLM APIs. This beginner’s guide covers prompt engineering, function calling, and creating custom AI tools.

Master advanced prompt engineering techniques like Chain-of-Thought, ReAct, and role-based prompting strategies to get smarter LLM responses