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Codexa for startups

Ship an MVP in days and keep iterating with real code.

Describe the product, get a working first version, and refine it in an editor you would use anyway. Nothing is locked inside a proprietary format.

A typical workflow

From idea to a URL you can put in front of users.

  1. Step 1: Describe the MVP

    Write the user stories as a prompt. Codexa picks a starter template and plans the files.

  2. Step 2: Generate and review

    The agent creates the project, runs the type-check, and shows a per-file diff before you accept.

  3. Step 3: Connect data

    Add a PostgreSQL or Supabase connection and encrypted environment variables.

  4. Step 4: Run and test

    Preview in an isolated sandbox with streamed logs and viewport controls.

  5. Step 5: Deploy

    Publish to Codexa hosting, roll back if needed, and point a custom domain (CNAME) at it.

Features that matter here

Example project ideas

Starting prompts you can paste into Codexa. Each one maps to a starter template and produces real, editable code.

  • A waitlist landing page with referral codes and an admin view of signups
  • A B2B SaaS dashboard with team invites, plan limits, and Stripe checkout
  • A marketplace MVP with listings, search, and seller onboarding
  • An internal metrics page that reads from an existing PostgreSQL database

Limitations to know about

  • AI generation requires an Anthropic or OpenAI API key configured by the operator of your Codexa instance; without one the agent shows a "not configured" state.
  • Generated code is a starting point. Review it like any other contribution before shipping to customers.
  • Starter templates currently cover single-page React apps, static sites, and Node + Express APIs. Other stacks can be imported from GitHub but have not been tuned for the sandbox.
  • Concurrent editing by several people at once is on the roadmap, not shipped; collaborators see presence and share snapshots instead.

Build your first MVP with Codexa

Start on the Free plan. Upgrade when you need more AI requests, runtime, or collaborators.