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Magic

Paid
aicode generationai agentsoftware developmentdeveloper toolsautomationai engineercodebase analysisdevopsagile

Magic introduces an AI software engineer that acts as a true teammate, possessing a deep understanding of your codebase to independently resolve bugs, build features, and dramatically accelerate software development cycles.

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Magic is an advanced AI system designed to operate as a fully-fledged software engineer on a development team. It gains a comprehensive understanding of an entire codebase, allowing it to autonomously work on tasks assigned in a project management tool like Jira or Linear. The platform is built for software engineering teams at startups and large enterprises who want to augment their human developers and significantly increase their development velocity. Unlike simple code completion tools, Magic functions with a high degree of autonomy, pulling tasks, writing code, creating pull requests, and responding to feedback just like a human engineer would. Its core purpose is to handle a significant portion of the coding workload, freeing up human engineers to focus on more complex architectural decisions and product strategy.

Pros

  • Operates with high autonomy, pulling tasks from project management tools and creating pull requests independently.
  • Possesses a deep, contextual understanding of an entire codebase, not just a single file.
  • Automates routine coding tasks, bug fixes, and test writing, reducing engineering toil.
  • Accelerates development velocity by adding a persistent and tireless AI coding resource to the team.
  • Understands and incorporates feedback on its pull requests, iterating on code like a human developer.

Cons

  • Pricing is opaque and requires contacting sales, preventing straightforward cost evaluation.
  • Access is subject to a waitlist and qualification process, as it is not a self-serve product.
  • Onboarding may be complex, requiring significant setup to grant the AI secure access to proprietary codebases.
  • Requires building organizational trust in the AI's ability to produce secure, efficient, and correct code.
  • Early stage technology may have limitations in understanding highly abstract or novel architectural patterns.

Key features

  • Autonomous AI Software Engineer
  • Full Codebase Contextual Understanding
  • Project Management Integration (Jira, Linear)
  • Automated Pull Request Generation
  • Iterative Code Refinement via PR Feedback
  • Bug Fixes and Test Writing
  • New Feature Implementation

Integrations

JiraLinearGitHubGitLabSlack

Target audience

CTOs, VPs of Engineering, and software development teams at tech companies seeking to augment their staff with an autonomous AI developer to increase productivity.

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Key Metrics

Founded

2022

Headquarters

San Francisco, USA

Pricing Tiers

Custom

Custom solutions and enterprise pricing models tailored to team size and usage needs. Includes access to the AI software engineer and integration with codebases and project management tools.

Contact for pricing

Frequently Asked Questions

Top Alternatives to Magic

Devin (Cognition AI)

A direct competitor also marketed as an autonomous AI software engineer capable of handling entire development projects from a single prompt.

GitHub Copilot Workspace

This is a more integrated solution from GitHub that bridges the gap between code completion and full autonomy by creating an AI-native dev environment.

Sweep AI

An open-source alternative that acts like an AI junior developer to automatically handle small feature requests and bug fixes by creating pull requests.

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