AutonomyAI
AutonomyAI’s Fei Studio is an OS for building in production. It ingests your repo in minutes, lets PMs and designers generate production-quality changes, and opens clean PRs for engineer approval—bridging planning, prototyping, and delivery inside the real codebase.
Overview
Connect your git provider and run a task from a prompt, screenshot, ticket, or Figma. Fei plans the change, renders a prototype, generates code aligned to your patterns, and raises a clean PR with specs—shortening the path from idea to review.
How Fei Studio Works
Fei suits product managers, designers, and full-stack engineers who need to ship interface and workflow updates without re-implementing throwaway prototypes. Teams modernizing legacy UIs, aligning design systems, validating product ideas, or transforming support feedback into fixes benefit from a fast lane to production that preserves engineering oversight. Enterprise stakeholders gain auditability—clean PRs, explicit specs, and change history—without introducing a parallel, disconnected app builder.
- Map repository conventions and architecture automatically in under two minutes onboarding.
- Translate prompts, screenshots, and Figma into structured plans and variants.
- Generate production-quality code aligned to components, CSS, APIs, and hooks.
- Open clean pull requests with specs and complete change history included.
- Run inside Claude Code, Cursor, or any MCP-capable agent workflow.
Key Capabilities
Who Benefits
Begin in the Playground or within supported IDE agents. Connect your git provider, authorize repository access, and Fei will ingest components, styles, APIs, and architecture in under two minutes. Start a task from a prompt, screenshot, ticket, or Figma. Review the proposed plan and prototype, then let Fei generate code and open a clean PR with a linked spec. Engineers review diffs in their normal tools—Claude Code, Cursor, or any MCP-capable agent—and approve when ready. Compliance and documentation resources support enterprise rollout and governance.
Product and design build in the real codebase; engineering reviews once and ships.
Getting Started
Fei’s edge is environment, not just model choice: it learns your stack, keeps context fresh, and outputs audit-friendly PRs product and design can drive. Triple output per task, self-updating knowledge, and per-task pricing create a dependable second lane to production without seat sprawl or duplicate app builders.
Open the tool and review its core product experience.
Create your account or access your existing workspace.
Use your own task to judge speed, quality, and fit.
Check similar AI tools before making a final decision.
AutonomyAI
AutonomyAI builds an operating system for shipping software in production. The team focuses on delivery-grade agent workflows, developer tool integration over MCP, and enterprise guardrails. Their approach centers on modeling each customer’s codebase so non-engineers can propose changes that engineers confidently review and merge.
AutonomyAI’s Fei Studio moves software work from specs to shipped changes by letting product and design build directly in the production codebase. After a rapid ingestion that maps components, CSS conventions, APIs, hooks, and rendering, Fei turns prompts, screenshots, tickets, or Figma into structured plans, testable variants, and production-quality code. Each task yields triple output: a visual prototype, a clean pull request aligned to your standards, and a full spec with change history for context. Fei runs inside developer tools—such as Claude Code or Cursor—or any agent that speaks MCP, so engineers review in-place and approve with one click. The system self-updates as your repository evolves, keeping agent context fresh without manual re-indexing. Pricing is per task, not per seat, creating a second lane to production without reshuffling teams. Explorer Mode, with planned connectors to Amplitude, Mixpanel, and call recordings, aims to add business context so agents understand why a change matters, not just how to build it.
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