Autonomous Browser Recording

A real browser. A real demo. No human in the loop.

Most screen recording tools require a human to perform the demo. AI Screen Recorder replaces that human with an AI agent that drives a real headless Chromium browser — navigating, clicking, typing, and scrolling just like a skilled solutions engineer would.

How the recording loop works

For each feature chunk, the system spins up a fresh, isolated browser context. There are no leftover cookies, no cached state, no data from a previous recording polluting this one.

If your app requires login, the system handles it deterministically — it navigates to your login URL, fills credentials, and waits for the success indicator you’ve defined. The AI agent never sees the password. It’s injected into the browser directly and wiped from memory immediately after use.

Then the agent begins the demonstration loop:

1. The model receives the feature intent and success criteria
2. It chooses the next action (navigate, click, type, hover, scroll, screenshot)
3. That action is executed in the real browser
4. The page snapshot and any relevant DOM changes are logged
5. The loop continues until success criteria are visibly met — or guard rails fire

What gets recorded

Every recording session captures:

• Full video via CDP screencast piped directly to FFmpeg
• Action log (JSONL) — every tool call with timestamp and DOM context
• Keyframes — frames marked by the agent as “highlight this moment” plus auto-extracted stills every 3 seconds

Guard rails that protect your budget

The recording agent runs inside a deterministic wrapper that enforces hard limits:

• Max wall-clock time per chunk (configurable per job)
• Max tool calls per chunk (default: 60 actions)
• Max tokens per chunk (~50k input hard cap)
• Origin enforcement — the browser cannot navigate outside your app’s domain
• Auto-retry — one retry on tool errors; chunk fails cleanly if it persists

If a chunk is blocked (element missing, error state, session expired), the agent calls finish_chunk with a failure reason. Other chunks continue unaffected.

Parallel processing

Chunks fan out to parallel workers. A default job runs 3 chunks simultaneously. The system’s state machine tracks each chunk independently — a failure in chunk 4 never blocks chunks 5 through 10.