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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 ChatGPT , 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 yo

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.

Do you over-rely on AI? Understand the risks of using AI for self-directed learning. Struggle productively. Reclaim your critical thinking.

Learn how to use regex pattern matching in Excel for advanced data cleaning, text extraction, and analysis.

Convolution kernels explained. Learn edge detection for images using filters and the Sobel operator. Essential computer vision concepts with Python.

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

Unlock the math behind 22/7! Learn how continued fractions generate increasingly accurate rational approximations for irrational numbers like pi

Explore the math behind language. Learn how formal grammars shape speech, code, NLP, and the rules machines use to understand us.

Master set theory: definitions, notation, set operations (union, intersection), and common sets. Essential concepts for higher mathematics.

Learn why accuracy fails in imbalanced data. Master essential model evaluation metrics: Precision, Recall, and the F1 score for robust ML classification.

Perlin noise for procedural generation. Learn to create realistic mountains, cliffs, and caves with parameters like persistence, lacunarity, and Fractal Brownian Motion.

Explore the Gale-Shapley Algorithm and the Stable Matching Problem. Learn how algorithms create stable pairings, not just perfect matches.

Learn how to find an Eulerian Path using Graph Theory and the degree of a vertex. Discover the solution to the Bridges of Königsberg puzzle.

Master data visualization: use pre-attentive features, Gestalt theory, and proper visual data encoding to create clear, effective charts

Discover Turing’s Turochamp, Learn about Alan Turing’s foundational paper-and-pencil chess algorithm and the birth of AI in games.

Explore prime number math: shortcuts, primality tests, Mersenne numbers, and the Lucas-Lehmer Test for finding the largest primes.

Explore the Fibonacci sequence, Golden Ratio (φ), and their appearance in nature, from flowers to the staircase problem in math.