You’ve probably heard the term by now. Maybe you’ve tried it yourself: describing what you want to an AI tool and watching functional software materialize in minutes, no programming knowledge required.

Welcome to the era of AI-assisted development, where two distinct approaches have emerged for building software with artificial intelligence. One says “forget the code exists.” The other says “own the architecture, let AI handle the typing.” Both are reshaping who gets to build software and how. This post breaks down what vibe coding and agentic coding actually are, where each shines, and where each falls short.

Where These Terms Came From

Vibe coding entered the lexicon on February 2, 2025, when AI researcher Andrej Karpathy posted a now-viral tweet describing a new way of working: you talk to an AI tool, accept whatever code it generates without reading it, paste error messages back when something breaks, and repeat. You “give in to the vibes” and “forget that the code even exists.” The tweet got over 6.5 million views. Google searches for the term surged 6,700%. Collins Dictionary named it their Word of the Year for 2025.

Agentic coding (sometimes called “agentic engineering”) emerged more gradually through 2025 as AI coding tools became more autonomous. Where vibe coding is defined by the developer stepping back from the code entirely, agentic coding keeps the developer in the architect’s seat while AI agents handle implementation, run tests, trace bugs, and iterate across entire codebases. By February 2026, Karpathy himself moved on from the term and endorsed “agentic engineering” as the term for serious professional practice. (Coverage: The New Stack, Business Insider)

What Each Looks Like in Practice

Vibe coding is remarkably simple, which is the point. You open a tool like Cursor, Replit, Bolt.new, or Lovable, describe what you want in plain language (“build me a recipe app with search and a sidebar”), and the AI generates everything. You run it, see if it works, and if something breaks, you paste the error back. You never open the code files. Some practitioners even dictate instructions by voice. The “source code” is effectively the conversation.

Agentic coding starts differently. The developer writes a structured plan defining architecture, constraints, and goals. This becomes the AI agent’s roadmap. The agent then autonomously writes code across multiple files, runs tests, analyzes failures, and iterates, but the developer reviews every significant change and maintains architectural control. Think of it less like magic and more like directing a skilled contractor: you provide blueprints, they build, you inspect the work.

The Case for Vibe Coding

Vibe coding’s greatest strength is democratization. For the first time, people who can’t write a line of code can build functional software. Non-programmers are creating personal tools, small business apps, and prototypes that previously required hiring a developer. In Y Combinator’s Winter 2025 batch, 25% of startups had codebases that were 95% AI-generated.

For experienced developers, the benefit is speed. First drafts materialize in minutes. The cost of exploring an idea drops to nearly zero. Vibe coding is exceptional for prototyping, personal projects, throwaway scripts, and anything where longevity doesn’t matter.

The Case for Agentic Coding

Agentic coding delivers professional-grade productivity without sacrificing quality. Enterprise case studies tell a compelling story: Rakuten achieved 79% faster feature delivery. TELUS saved over 500,000 hours. Individual developers report becoming more “full-stack” because AI fills knowledge gaps while humans provide oversight.

The developer’s role shifts from typing code to orchestrating AI agents, defining what gets built, reviewing how it’s built, and ensuring it meets real-world standards. Onboarding to unfamiliar codebases collapses from weeks to hours. The work that gets done isn’t just faster work, it’s work that wouldn’t have happened at all.

The Risks Are Real, and Different

Vibe coding’s risks center on what happens when nobody understands the code. Security research paints a stark picture: AI co-authored code shows significantly higher vulnerability rates. One study analyzed thousands of vibe-coded applications and found widespread exposed secrets, missing database security, and leaked personal data including medical records.

Maintainability is equally concerning. Since AI coding tools became widespread, code refactoring has dropped while duplication has quadrupled. The “vibe coding hangover” is what happens when someone inherits a vibe-coded codebase: code so tangled that rewriting from scratch is faster than debugging it.

Agentic coding’s risks are different. Cost is a primary concern, as token consumption for autonomous operations far exceeds simple chat interactions. Runaway agent behavior is documented: in one notable case, an AI agent deleted a production database despite explicit instructions not to. And there’s the expertise requirement: the developers who get the most from agentic tools tend to already be experienced engineers. The tools amplify expertise rather than replacing it. A rigorous randomized controlled trial by METR found that experienced developers were actually 19% slower when using AI coding tools, despite believing they were 20% faster.

It’s a Spectrum, Not a Binary

The emerging consensus isn’t that one approach will “win.” They represent a spectrum of human involvement in AI-assisted development, and professionals are learning to move along it depending on context.

The practical workflow taking shape: build fast with vibe coding to validate ideas, then graduate to agentic tools for production. Use vibe coding for the throwaway prototype. Use agentic coding for the system that needs to scale, stay secure, and be maintained by a team.

Making the Right Choice

Vibe coding works well when:

• You’re prototyping or exploring ideas
• The project is personal or low-stakes
• Speed matters more than longevity
• You don’t have programming experience and need a functional starting point

Agentic coding works well when:

• The code needs to be maintained, secured, and scaled
• You’re working in a team or professional context
• Reliability and security are non-negotiable
• You have (or have access to) engineering expertise to guide the process