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ML.ai

Coding agent for VS Code, Cursor, desktop, and pull requests that routes tasks and previews diffs before changes.

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Introduction

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Information

  • Websiteml.ai
  • Published date2026/10/08

Categories

  • Developer Tools

Tags

  • AI Assistant
  • Code Generation
  • Code Review
  • AI Powered
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How to Use ML.ai

ML.ai's Core Features

Repository-aware agent

Reads the project context before proposing a code change.

Model routing

Routes individual task steps to a model suited to that step.

Diff-first review

Shows the proposed diff before writing changes to disk.

Editor integrations

Supports VS Code, Cursor, and desktop workflows.

Pull-request assistance

Can work with tasks connected to pull requests.

Explicit write approval

Keeps file changes behind an Allow step.

ML.ai's Use Cases

1

Feature implementation

Delegate scoped coding tasks while reviewing every diff.

2

Code review support

Use an agent to inspect or improve a pull request before merge.

3

Multi-model development

Use different models for planning, coding, and review without changing tools manually.

FAQ from ML.ai

ML.ai Support & Company Information

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ML.ai is a coding agent for repository and pull-request work. Its official site says it reads the codebase, routes each step to the model that fits the task, and shows the proposed diff before anything is written to disk. This review-first workflow is aimed at keeping developers in control while using multiple models efficiently.

  1. Install or open ML.ai in the supported editor or desktop workflow.
  2. Describe the coding task and point it at the relevant repository or pull request.
  3. Let the agent inspect the code and plan the next step.
  4. Review the generated diff before allowing a change.
  5. Accept, revise, or reject each proposed change and run your normal tests.
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