Introducing Autohand

Autohand is a platform for building AI software engineers with self-evolving capabilities. It helps engineering teams build, deploy, and manage complex systems through autonomous agents that learn and improve over time.

Product suite

Autohand's product suite covers the full software development lifecycle:

  • Autohand Code: A self-evolving coding agent for the terminal and your IDE. Autohand Code includes the CLI for terminal-first workflows, extensions for VS Code and Zed Editor, and JetBrains integration through the Agent Communication Protocol (ACP).
  • Code Agent SDK: A programmatic toolkit for embedding Autohand coding agents in applications, services, and automated engineering workflows.
  • Evolve: Self-improving AI agents that discover and optimize algorithms through evolutionary processes. Evolve runs autonomously, testing mutations against your evaluation criteria and selecting the best performers for each generation.
  • Slack: An integration that brings Autohand into your team conversations. Interact with AI agents directly from your workspace channels.

Core technology

Autohand is built on self-evolving AI agents that operate autonomously across your development workflow. The platform combines four key technologies:

  • Self-improving agents: Autonomous agents that test, mutate, and improve without human intervention. Each generation builds on the successes of the previous one.
  • Ground truth evaluation: You define the success criteria, and the agents measure every solution against your standards. Only improvements that pass your tests survive to the next generation.
  • Cloud-agnostic deployment: Run Autohand on AWS, Google Cloud, Azure, or your own infrastructure with no vendor lock-in.

Installation

Choose your preferred environment to get started with Autohand:

What teams build with Autohand

  • Algorithm optimization through self-improving agents that discover efficiencies across generations.
  • Large-scale code modernization and framework migrations with automated testing and verification.
  • Autonomous SRE workflows for incident detection, root cause analysis, and automated remediation.
  • Technical debt reduction through continuous code analysis and refactoring.
  • Custom AI workflows that integrate with existing tools through Slack, CLI, and API surfaces.

Next steps