Introducing Doc Autopilot: Generate Docs from Your Codebase

Every engineering team has the same problem: the code moves fast and the docs don't keep up. You ship a new API endpoint on Monday, and the documentation is still describing last month's version on Friday.

Today we're launching Doc Autopilot — a feature that connects to your code repository, analyzes your codebase using AI, and generates complete, publish-ready documentation automatically.

The Documentation Gap

We surveyed 200 engineering teams and found a consistent pattern:

• 73% said their documentation is always at least one release behind
• 45% have API docs that reference endpoints that no longer exist
• 62% rely on README files as their primary documentation
• 89% said they'd write more docs if it took less time

The problem isn't that engineers don't value documentation. It's that writing docs is a context switch — you go from writing code to writing prose, and it never feels as urgent as the next feature.

Doc Autopilot eliminates the context switch. Your code IS the documentation source.

How It Works

What It Understands

Doc Autopilot doesn't just read function signatures. It understands your codebase at a deeper level:

• API Routes — Express, FastAPI, Rails, Django routes are detected and documented with parameters, request/response schemas, and example calls
• Configuration — Environment variables, config files, and feature flags are extracted into a setup guide
• Data Models — Database schemas (Prisma, SQLAlchemy, ActiveRecord) become data model reference docs
• Authentication — Auth patterns (JWT, session, OAuth) are detected and documented with integration guides
• Error Handling — Error codes and error responses are cataloged into a troubleshooting reference
• Dependencies — package.json, requirements.txt, Gemfile are analyzed for setup instructions

Multi-Platform Support

Doc Autopilot works with the three major Git platforms:

• GitHub — Public and private repos via personal access token or GitHub App
• GitLab — Cloud and self-hosted instances. Uses GitLab API v4 with automatic pagination for large repos
• Bitbucket — Cloud repos via app password. Handles Bitbucket's paginated Source API for file tree fetching

Each platform has its own quirks — different API formats, authentication methods, and file tree structures. Doc Autopilot handles all of this behind a single "Paste your repo URL" interface.

Example Output

Here's what Doc Autopilot generates from a typical Express.js API:

# User Authentication API

## POST /api/auth/login

Authenticates a user and returns a session token.

**Request Body:**
| Field    | Type   | Required | Description           |
|----------|--------|----------|-----------------------|
| email    | string | Yes      | User's email address  |
| password | string | Yes      | User's password       |

**Response (200):**
| Field | Type   | Description                    |
|-------|--------|--------------------------------|
| token | string | Session token (24h expiry)     |
| user  | object | User profile (id, name, email) |

**Example:**
curl -X POST https://api.example.com/auth/login \
  -H "Content-Type: application/json" \
  -d '{"email": "user@example.com", "password": "..."}'

This isn't a template — it's generated by reading your actual route handler, middleware, validation schemas, and response shapes. If your code changes, regenerating updates the docs.

What It Doesn't Do

We want to be transparent about limitations. Doc Autopilot is not a replacement for a technical writer. It won't:

• Write tutorials — It documents what your code does, not how to achieve a user's goal. Tutorials still need human authoring.
• Explain architecture decisions — Why you chose PostgreSQL over MongoDB is context the AI doesn't have.
• Write getting-started guides — The onboarding journey requires understanding your user, not just your code.
• Handle undocumented conventions — If your team uses implicit patterns that aren't in the code, the AI can't infer them.

Think of Doc Autopilot as your first draft machine. It handles the mechanical work — extracting parameters, documenting endpoints, mapping data models — so your writers can focus on the high-value content: tutorials, best practices, and architectural guides.

Pricing

Doc Autopilot is available on Business and Enterprise plans. Each full run costs 50 AI credits. A Business plan includes 10,000 credits/month — enough for 200 Doc Autopilot runs.

For most teams, one run per release cycle (weekly or bi-weekly) is enough. That's 4-8 runs per month, well within the credit limit.

Getting Started

Doc Autopilot is live today. If you're on a Business or Enterprise plan:

1. Go to AI Studio → Doc Autopilot in your sidebar
2. Click Connect Repository
3. Paste your repo URL (GitHub, GitLab, or Bitbucket)
4. Add your access token
5. Click Analyze & Generate

Your first documentation draft will be ready in under 2 minutes.

Not on a Business plan yet? See our pricing or start a free 15-day trial with full access to all features.