Agentic Coding vs Vibe Coding: The Real Difference

Both vibe coding and agentic coding use AI to write code. If you only look at the output — files with code in them — they can look identical. The difference is everything else: how you direct the AI, how you verify the output, and what happens when complexity increases.

I use both approaches. They solve different problems. Understanding the distinction helps you pick the right one for the situation you’re in, instead of applying one approach to everything and wondering why it breaks.

What is vibe coding

Andrej Karpathy coined the term in early 2025. His description: “fully giving in to the vibes, embracing exponentials, and forgetting that the code even exists.” It’s a useful framing because it captures the essence of the approach — you describe what you want, the AI writes code, and you evaluate the result by feel.

In practice, vibe coding looks like this: you open a chat with an AI model, describe what you want in natural language, and let it generate code. You paste that code into your project, run it, and see what happens. If something looks wrong, you describe the problem and let the AI try again. The feedback loop is visual or manual — “does this look right?” or “does this button work when I click it?”

There’s no spec. No plan. No automated checks. You and the model are having a conversation, and the quality of the output depends entirely on the quality of that conversation.

This isn’t a criticism. Vibe coding is genuinely powerful for certain use cases. I’ve built entire proof-of-concept apps in an afternoon this way. The problem isn’t the approach — it’s applying it to situations where it doesn’t hold up.

What is agentic coding

In agentic coding, the AI isn’t a tool you prompt. It’s an agent you direct. The distinction matters because it changes your relationship with the AI from “write this for me” to “execute this plan according to these constraints.”

The key differences from vibe coding:

Structured intent. Before the AI writes a single line of code, you define what needs to be built. A spec, a plan, success criteria. The AI knows what “done” looks like because you told it explicitly, not because it inferred it from a vague prompt.

Automated verification. Instead of checking output visually, you verify it systematically. The build passes. Types check. Tests pass. Linting is clean. The AI itself runs these checks and iterates until they pass. You’re not the quality gate — the process is.

Context management. Vibe coding happens in a single conversation. Agentic coding spans sessions. State files, architecture docs, and roadmaps give the AI context it didn’t have to infer. Each session picks up where the last one left off without you pasting context back in.

Systematic debugging. When something breaks in a vibe coding session, the common pattern is to describe the problem and hope the AI fixes it — or start over. In agentic coding, you treat bugs like an engineer: form a hypothesis, write a test that exposes the issue, fix the implementation, verify the test passes. The AI does the work, but the process is structured.

For a deeper dive into the foundations, see the full definition of agentic coding.

Side-by-side comparison

Dimension	Vibe Coding	Agentic Coding
Intent	Implicit (“make this look nice”)	Explicit (spec + plan)
Feedback	“Looks right” / manual test	Automated verification
Quality	Variable, depends on prompt	Consistent, depends on process
Debugging	Often start over	Systematic (hypothesis, test, fix)
Scalability	Breaks at complexity	Handles multi-phase builds
Context	Single conversation	Managed across sessions
Learning curve	Low	Medium
Speed (simple task)	Faster	Slower (overhead)
Speed (complex task)	Slower (rework)	Faster (less rework)

The speed row is the one most people miss. Vibe coding feels faster because there’s no setup overhead. For a simple script or a quick prototype, it genuinely is faster. But for anything with moving parts — multiple files, state management, integrations — the rework cost of vibe coding exceeds the setup cost of agentic coding. Usually by a lot.

When vibe coding is the right choice

I reach for vibe coding regularly. It’s not a lesser approach — it’s a different tool for different situations.

Prototyping and exploration. When I’m testing whether an idea is worth building, I don’t need a spec. I need to see it on screen. Vibe coding gets me there in minutes, not hours.

One-off scripts. A script to rename 200 files, convert data formats, or scrape a page. These don’t need tests or architecture. They need to work once.

Learning a new framework. When I’m exploring unfamiliar territory, I want the AI to show me how things work. Structure would slow me down. I’m not building — I’m learning.

Internal tools. If nobody outside your team will use it, and maintenance isn’t a concern, vibe coding is fast and sufficient.

Time pressure. Sometimes “good enough in 2 hours” beats “perfect in 2 days.” Vibe coding lets you ship something functional when the deadline is tomorrow.

The pattern: vibe coding excels when the cost of failure is low and speed matters more than reliability.

When agentic coding is necessary

Some situations demand structure. Not because it’s theoretically better, but because the alternative — vibe coding — will actively work against you.

Production software. If real users depend on it, you need automated verification. “It looked right when I tested it” doesn’t survive contact with edge cases, different browsers, or unexpected input.

Client work. Clients have specs, even informal ones. Agentic coding maps those specs to implementation plans and verification criteria. This protects both you and the client — the deliverable is defined before work begins.

Multi-session projects. Any project that spans more than one working session needs context management. Without state files and architecture docs, you’ll spend the first 20 minutes of every session re-explaining the project to the AI. That’s wasted tokens and wasted time.

Maintained codebases. If you or anyone else will modify this code in the future, it needs to be understandable and tested. Vibe-coded projects tend to accumulate technical debt rapidly because there’s no process preventing it.

Projects where “it broke and I don’t know why” is unacceptable. Agentic coding’s structured debugging means you can always trace a failure back to its cause. With vibe coding, you’re often reduced to “let me try reprompting” — which is not debugging, it’s gambling.

The pattern: agentic coding is necessary when the cost of failure is high or the project will outlive a single session.

The spectrum

It’s not binary. In practice, most of my work involves both approaches, sometimes in the same day.

I vibe code when I’m exploring a new idea. I’ll spend an hour prompting, seeing what works, getting a feel for the shape of the solution. No spec, no plan — just vibes.

Then, when I’ve validated the concept and I’m ready to build it properly, I switch to agentic coding. I write a spec based on what I learned during exploration. I create a plan. I set up verification. The exploratory code usually gets thrown away entirely — it served its purpose.

Here’s what that looks like in practice. Say I’m building a new component for this site:

Vibe coding phase: I prompt the AI to build a rough version. I iterate on the visual design conversationally. “Make the heading larger.” “Add a border on the left.” “Try a different color.” This takes maybe 15 minutes.
Transition: I look at the rough version and decide it’s worth building properly. I note what worked and what didn’t.
Agentic coding phase: I write the component into my project spec. I define the props, the responsive behavior, the accessibility requirements. I create a plan. The AI builds it with proper types, tests, and documentation. This takes longer, but the result is production-ready.

The vibe coding phase isn’t wasted time. It’s research. It’s prototyping. It informs the spec I write for the agentic phase. The mistake isn’t using vibe coding — it’s stopping there and shipping the prototype as the final product.

The real differentiator

The gap between vibe coding and agentic coding isn’t technical sophistication. It’s intent.

When you vibe code, you’re saying: “AI, figure out what I want and build it.” When you use agentic coding, you’re saying: “Here’s exactly what I want, here’s how I’ll know it’s right, now build it.”

The second approach requires more from you upfront. You have to think about what you actually want before you start building. You have to define success criteria. You have to set up verification. That’s work, and for simple tasks it’s overhead that isn’t worth it.

But for anything that matters — anything that ships, anything that gets maintained, anything a client pays for — that upfront work is what separates professional output from “AI slop.” Not the model. Not the tools. The process.

For my opinionated take on how this distinction is reshaping who gets to build software professionally, I wrote a blog post covering the broader implications.