Agentic Coding vs Vibe Coding: What's the Difference?

Agentic coding vs vibe coding: what actually differs

The real difference is how much of the work you steer versus how much you hand off. Vibe coding is a conversation: you describe what you want, the tool proposes code, and you check each step before moving on. Agentic coding is a handoff: you give an agent a scoped task and a definition of done, and it plans, writes, runs, and fixes the code on its own before you review the finished result. Both use the same generation of AI coding tools. The difference is where the human sits in the loop.

We work with both styles inside client projects at Mound Studio, often in the same week and sometimes on the same feature. Neither one replaces judgment. They just ask for it at different points.

What vibe coding actually looks like

Vibe coding is the style most people picture when they think of building with AI: a chat window, a plain-language request, and a stream of small code changes you approve as they arrive. You might ask for a new component, see the first pass, ask for a tweak, then ask for another. The session is conversational and iterative. Nothing moves forward without you reading it first.

This is a good fit when you cannot fully describe the end state yet. You are exploring a layout, testing an interaction, or trying three versions of a script to see which one reads better. The tool is a fast pair, not an independent worker. You stay hands-on the entire time, which is exactly the point: the value is in tight feedback, not in speed alone.

The tradeoff is attention. A long vibe coding session with dozens of small prompts can drift from the original goal if nobody restates it. It also does not scale well to a large, well-defined task, because reviewing forty small diffs one at a time takes about as long as writing the feature yourself.

What agentic coding actually looks like

Agentic coding removes the step-by-step steering. You still write the brief, but instead of approving each change, you describe the outcome: the ticket, the acceptance criteria, the files that are in scope, and the tests that need to pass. The agent then plans its own steps, edits the code, runs the test suite, reads the failures, and tries again, often several times, without asking you in between.

What makes this possible is tool access. An agentic setup can open a terminal, run a build, read the error output, and act on it. That loop of plan, execute, observe, and correct is what separates it from a single prompt-and-response exchange. The output you see is not the first draft; it is whatever the agent settled on after checking its own work.

This fits tasks you can already describe clearly: a scoped bug fix, a repetitive refactor across many files, a migration with a known target state, or a feature with an existing pattern to follow. It fits less well when the goal itself is still unclear, because an agent working alone toward a fuzzy target tends to produce a confident, wrong answer rather than a useful question.

Where the practical differences actually show up

On paper the distinction sounds tidy. In practice, three things change once a team moves from one style to the other.

Who writes each line

In vibe coding, you are effectively still the author. You accept, reject, or edit every suggestion, so the final code reflects a long series of your decisions. In agentic coding, the agent is closer to a contributor: it makes implementation choices inside the boundaries you set, and you only see the outcome of those choices, not the process.

Who runs and reads the tests

Vibe coding usually leaves testing to you, prompt by prompt, unless you explicitly ask the tool to write and run tests too. Agentic coding treats tests as part of the loop by default: a scoped agentic task without a test suite to run against is flying without instruments, so the agent has nothing to check its own work against.

Who catches the mistake

In vibe coding, you catch a mistake the moment you see a diff you do not like. In agentic coding, small mistakes get caught earlier by the agent's own test run, but a mistake in the underlying assumption, the wrong scope, the wrong library, a misread requirement, only surfaces at the final review. That review has to be thorough, because it is the one checkpoint left.

What a typical agentic coding run looks like, step by step

A useful way to picture agentic coding is as a five-part loop with people at both ends and the agent doing the middle on its own.

1. Scope the ticket. Write the task, the acceptance criteria, and what the agent should not touch. Vague scope is the most common cause of a bad agentic run.
2. The agent plans. It breaks the ticket into steps and lists the files it expects to change, before writing anything.
3. The agent executes. It writes the code, runs the test suite, and works through failures on its own, often across several attempts.
4. A person reviews the diff. Not the summary the agent wrote about its own work, the actual change set, file by file.
5. Merge or send back. A clean diff merges like any other change. Anything unclear goes back with a specific note, not a vague request to try again.

Notice that step four is doing the same job a code review always did. Agentic coding does not remove review; it moves review to the end of a larger unit of work instead of spreading it across many small ones.

When a design or dev team should reach for each approach

Most teams do not need to pick one style forever. The choice usually comes down to the task in front of you.

Reach for vibe coding when:

• You are exploring an interaction or a layout and cannot describe the end state precisely.
• The task is small enough that reading each step costs less time than writing a detailed brief.
• You are prototyping something disposable, where the goal is a fast answer, not production code.
• You want to learn a new library or pattern by watching it get built one step at a time.

Reach for agentic coding when:

• The task is well-scoped and you can write a clear brief and a pass or fail test for it.
• The work is repetitive across many files, such as a rename, a dependency bump, or a consistent refactor.
• You have an existing pattern in the codebase the agent can follow rather than invent.
• You would rather spend your attention reviewing one finished change than approving twenty small ones.

A lot of real projects use both in the same week: vibe coding to work out what a new feature should even look like, then a scoped agentic task once the shape is clear enough to write a brief for. We took this approach on client work that touched how AI fits into a product design workflow, exploring the interaction in a conversational session before handing the repeatable part to a scoped agentic pass.

Common mistakes we see teams make

• Treating agentic coding like a bigger vibe coding session. Handing an agent a vague goal and walking away produces a confident, wrong answer more often than a useful one. Scope matters more here, not less.
• Skimming the final diff. When the agent did the typing, it is tempting to read its summary instead of the actual change. The summary is the agent's opinion of its own work; the diff is the work.
• Letting a vibe coding session run too long without a checkpoint. After a dozen back-and-forth prompts, restate the original goal out loud, or start fresh. Otherwise small approved changes quietly drift from the brief.
• Forgetting that tests are also generated. A test an agent wrote to make its own code pass is not automatically a good test. Read what it checks, not just whether it is green.
• Assuming either approach removes the need for a spec. Both need a clear definition of done. Vibe coding just lets you supply it one step at a time instead of up front.

Review and oversight practices either approach still needs

Neither style removes the need for a person who understands the codebase to look at the result. What changes is when that person looks, and at what.

The common thread is that oversight has to be specific. A general instinct that "it looks fine" is not a check. Reading the actual files that changed, running the tests yourself at least once, and confirming the scope matches the ticket are the three habits that carry over regardless of which approach you are using. Teams evaluating AI prototyping tools for design work run into a version of the same question: the tool changes, but the review habit does not.

A practical checklist before you ship either kind of AI-assisted change

• Is the goal written down somewhere, not just implied by the conversation?
• Did a person read the actual diff, file by file, not just a summary of it?
• Do the tests check the behavior that matters, not just whether the build passes?
• Are dependency, config, and environment changes reviewed with the same care as the code?
• Is there a clear way to revert if something breaks after it ships?
• If the task was ambiguous, did someone clarify it before handing it to an agent, rather than after?

If a team's answer to most of these is no, the fix is rarely a better tool. It is usually a smaller scope, a clearer brief, or a slower review, whichever the current project is missing. That holds whether the code came from a conversational session or an autonomous one, and it is the same discipline behind any vibe coding workflow built for a design-first team: the process around the tool matters as much as the tool itself.

The takeaway

Vibe coding and agentic coding are not competing technologies, they are two different amounts of autonomy applied to the same kind of tool. Vibe coding keeps you inside every step, which suits exploration and anything you cannot fully define yet. Agentic coding moves you to the start and the end of a larger unit of work, which suits a task you can already scope clearly. Both still need a person who reads the actual result closely, not just the summary of it. If you are weighing which approach fits a specific project, or want a second read on how a current build is set up for either one, get in touch with us.