ai code completion helps you write the next piece. a coding agent can take a bounded task, inspect the repository, make the change, run checks and hand you a pull request.
they are not competing versions of the same button. they remove different parts of the work.
01what does code completion do well?
completion is close to your hands. you are reading a function, you know what belongs there and the tool offers a useful continuation. you keep the context, the direction and the final edit.
it is especially good for repetitive code, unfamiliar syntax and the small bits of glue between decisions you have already made. you can accept one line, change it or ignore it without creating a new task.
completion is less useful when the answer depends on files you have not opened, an error you have not reproduced or an interaction that needs testing in a browser.
02what does a coding agent add?
an agent has a longer loop. it can search for where a behaviour lives, follow an error to its cause, edit several files and run the project checks. the useful result is not a suggestion in a cursor. it is evidence attached to a change.
for example, a request to fix a forgotten password flow may involve a form component, a server action, an email provider and an end-to-end test. you can still make every product choice. the agent carries the investigation and implementation through the repository.
that longer loop needs boundaries. an agent with a broad request has more ways to be technically reasonable while changing the wrong thing.
03which one should you use?
use completion when you are already at the edit and want help expressing the next move. use an agent when the job has a finish line but requires several moves to reach it.
| Work | Better fit | Why |
|---|---|---|
| Write a reducer branch | Completion | You have the file and the decision. |
| Find and fix a flaky test | Agent | The cause may cross files and needs verification. |
| Rename a local variable | Completion | The change is visible and immediate. |
| Add CSV export with tests | Agent | It has implementation, integration and browser checks. |
the handoff is also useful. you can use completion to shape a new component, then ask an agent to wire it in, exercise the flow and prepare reviewable evidence.
04what stays your job?
the agent should not own the product decision hidden inside an ambiguous request. if the task says "improve onboarding," it has to decide what improvement means. if it says "after creating a workspace, show the invite step and keep skip available," it has a behaviour to verify.
you also decide whether the pull request ships. a passing test suite tells you something important. it does not tell you whether a new behaviour is the behaviour you wanted.
05why use Wayari with either?
Wayari does not ask you to leave the coding app you already use. you can continue working with Claude Code, Codex, Cursor or another MCP app, then tell Wayari to take a bounded job through planning, building, review and its gate.
the goal is not to make coding feel hands-off. it is to make the work that leaves your hands come back with enough context to trust or reject it.
Give the agent a checkable brief, then use browser evidence for user-facing changes. See Wayari documentation for the workflow.
