Coding agents

A coding agent takes a software task, such as a bug report or a small feature request, and works through it on its own: it reads the codebase, edits files, runs the tests and comes back with a set of changes, usually as a pull request. That is different from an autocomplete or chat assistant in an editor, where a developer stays in control of every keystroke. Here the developer reviews the finished work.

These agents need an environment to work in. Some run in a cloud machine the vendor manages, others in a container on your own hardware, and some directly on a developer's laptop. Each choice changes what the agent can reach. Decide in advance which repositories, branches, secrets and network locations the agent may use, and prefer setups where it cannot push to protected branches or production systems.

The tasks that suit them are well-scoped and checkable: dependency upgrades, test coverage for existing code, small bug fixes with a clear reproduction, and the same change repeated across many files. Vague tasks with unclear goals tend to produce large, confident diffs that take longer to review than the work would have taken.

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4 AI agent tools in coding agents

OpenHands

by All Hands AI

Open-source coding agent that edits code, runs commands and browses in a sandbox, with a hosted cloud version.

  • Open source
  • Can run on your own servers

goose

by Block

Open-source agent from Block that runs on your machine, edits code, runs commands and connects to tools through MCP.

  • Open source
  • Can run on your own servers
  • Works with MCP

Devin

by Cognition

Autonomous coding agent that works in its own cloud environment and opens pull requests for your team to review.

Replit Agent

by Replit

Agent inside Replit that builds and changes apps from a plain-language request, then runs and deploys them on Replit.

Treat every agent change like one from a new team member. It goes through code review, runs in CI, and gets merged only by a person who understands it. Track how many agent pull requests are merged without changes, and use that to decide which kinds of tickets to keep sending.

Cost is worth tracking per merged change rather than per task started, since abandoned runs still use model calls and compute.

Questions about coding agents

How is a coding agent different from an AI code assistant?

An assistant works inside your editor while you type and you accept each suggestion. A coding agent takes a whole task, works on it without step-by-step input, and hands back finished changes for review, usually as a pull request.

Is it safe to give a coding agent access to our repositories?

It can be, with limits. Give it access only to the repositories it needs, keep production secrets out of its environment, block direct pushes to protected branches and require human review before any merge.

Which tasks should we start with?

Start with small, testable tickets that have a clear definition of done, such as fixing a failing test, upgrading a library or adding tests to existing code. Avoid open design work until you have seen how the agent handles your codebase.

Can we run a coding agent on our own infrastructure?

Some can. Open-source agents here can run in containers on your own machines, while hosted products run in the vendor's cloud. Check each tool page and the vendor's security documentation.

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