Capy

Capy rethinks the IDE for a world where AI agents do most of the heavy lifting. Instead of a single chat or inline completions, it spins up a fleet of agents—each with its own VM, branch, and context—all organized around tasks. This is powerful for teams that manage large, active codebases with many parallel workstreams. The model-agnostic design is a standout: you can use GPT-5.5 for planning, Claude Opus for coding, and Gemini for review, all within the same task. The recent April 2026 update made Captain the default orchestrator, which significantly improves one-shot execution and reduces manual guidance. For teams that can live in the browser and embrace task-driven workflows, Capy is faster than anything else. Where it bites: the learning curve is real. If your team is used to a classic IDE like VS Code or IntelliJ, the task-centric model feels foreign. Also, costs can add up quickly at scale—you're paying for both compute and model API calls through credits. Solo beginners or casual users will find cheaper options like Cursor or GitHub Copilot more sensible. Capy competes most directly with multi-agent platforms like Devin or Factory, but without the waitlist—it's generally available and battle-tested by 50,000+ engineers. The YC founder credit program lowers the entry barrier for startups. In practice, we'd reach for Capy when the team is shipping dozens of PRs a week and needs a force multiplier, not a smarter autocomplete.