Vibe Coding - meaning, description, origins, challenges and efficiency and risk aspects

Vibe Coding - meaning, description, origins, challenges and efficiency and risk aspects https://www.glukhov.org/post/2025/04/vibe-coding/ Vibe coding is an AI-driven programming approach where developers describe desired functionality in natural language, allowing AI tools to generate code automatically. vibe coding with microphone Coined by OpenAI co-founder Andrej Karpathy in February 2025, it emphasizes a conversational workflow where programmers focus on guiding AI outputs rather than manually writing code. AI-driven code generation Key aspects: Natural language prompts: Users articulate requirements in plain English (or other languages), and AI coding assistants like GitHub Copilot or Replit translate these into functional code. Iterative refinement: Adopts a “code first, refine later” mindset, prioritizing rapid prototyping over immediate optimization. Limited code oversight: Practitioners often accept AI-generated code without exhaustive review, relying on testing and iterative adjustments to resolve issues. Tools and workflow Developers use platforms like Cursor, Replit, or GitHub Copilot to generate code from prompts (e.g., “Create an interactive music visualization with smooth transitions”). The AI produces a functional but often imperfect base, which users refine through follow-up prompts or minor manual tweaks. Debates and limitations Scope: Some argue true “vibe coding” requires minimal code review, while others use AI assistance more deliberately. Maintenance challenges: AI excels at initial creation but struggles with debugging and maintaining complex systems, necessitating human oversight. Skill shift: Redefines developer roles toward creative problem-solving and cross-domain synthesis rather than syntax expertise. Karpathy describes it as “not really coding” but rather observing, describing, and iterating—a method particularly suited to experimental or small-scale projects. Is vibe coding a jargon or lang? Vibe coding is used to describe any of a number of possible applications of AI-assisted computer work. Given that it is an extremely recent word there is a decent possibility that it will change meaning if it sees extensive use. The word is more jargon than slang. Useful links https://en.wikipedia.org/wiki/Vibe_coding https://www.merriam-webster.com/slang/vibe-coding

Comments

Post a Comment

Popular posts from this blog

Argumentum Ad Baculum - Definition and Examples

In the pursuit of truth and sound reasoning, fallacies present themselves as deceptive snares that can ensnare even the most critical thinker. Among these is the ad baculum fallacy, or appeal to force, a fallacious argumentative tactic that employs coercion or threats to support a conclusion. This article provides an in-depth exploration of the ad baculum fallacy, unveiling its subtleties, historical roots, and the impact it has on discourse and decision-making. Definition and Origins The phrase argumentum ad baculum is derived from Latin, meaning “argument to the stick,” or “appeal to the force” symbolizing the use of force or threat. This fallacy occurs when an argument is supported by a threat of negative consequences rather than by legitimate evidence or reasoning. It is a persuasive strategy that relies on fear to compel acceptance of a claim.
Read more

Move Ollama Models to different location

After installing ollama better to reconfigure ollama to store them in new place right away. So after we pull a new model, it doesn’t get downloaded to the old location. Ollama is a text-based frontend to LLM AI Models and an API that can host those too. Install Ollama Goto https://ollama.com/download To install Ollama on linux: curl -fsSL https://ollama.com/install.sh | sh Ollama on Windows is on page: https://ollama.com/download/windows Ollama for Mac is there too: https://ollama.com/download/macOllamaSetup.exe Download, List and Remove Ollama models To download some Ollama models: Go to Ollama Library (https://ollama.com/library) and find the model you need, there you can also find model tags and sizes. Then run: ollama pull gemma2:latest # Or get slightly smarter one still nicely fitting into 16GB VRAM: ollama pull gemma2:27b-instruct-q3_K_S # Or: ollama pull llama3.1:latest ollama pull llama3.1:8b-instruct-q8_0 ollama pull mistral-nemo:12b-instruct-2407-q6_K ollama ...
Read more