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Hire amazing engineers by seeing how they use AI
Software engineering is being rewritten in real time, and hiring is getting pulled along for the ride. With tools like Claude Code and Cursor, being able to ship is the new baseline. The signal for finding extraordinary engineers is the process: how candidates break down work, steer the agent, make tradeoffs, and recover when things break. Outship is a recruiting tool that allows you to capture and analyze that process alongside the final code so you can hire with confidence. Candidates work in a cloud workspace that's ready to code. We handle the environment setup and secret management to give you a level testing ground.
Outship is a recruiting platform that records and analyzes how engineering candidates use coding agents during take-home tasks or interviews. It imports tasks from GitHub, creates a cloud workspace for candidates, and surfaces evidence of candidates’ decision-making while they code with AI assistants.
The platform spins up a cloud workspace for candidates to work in, allowing hiring teams to observe every decision made by candidates as they interact with coding agents (e.g., Claude Code, Codex). It supports importing a task repository from GitHub, sending interview or take-home invites, and collecting and analyzing candidate activity to determine engineering capability and vibe.
Who it’s for: Engineering-focused recruiting teams and hiring managers seeking to evaluate candidates' practical coding ability and AI-assisted workflows during take-home or interview tasks
marketing/demo oriented; product highlights and customer value articulation; mentions book a demo
now: outship.ai – hire amazing engineers by seeing how they use AI before: robot learning at Berkeley AI Research
now: outship.ai – hire amazing engineers by seeing how they use AI before: nlp at Berkeley AI Research
Outship is a recruiting platform that records and analyzes how engineering candidates use coding agents.
Outship provides a recruiting platform that records and analyzes how engineering candidates use coding agents. It imports a task repo, invites candidates to a cloud VM with a browser-based VS Code workspace, and analyzes their implementation against customizable rubrics to evaluate their use of coding agents and problem-solving approach.
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