Browser Automation

• Key points are in the visual diagram above.

Many business workflows live behind web UIs with no API. Browser automation lets agents interact with legacy systems, internal tools, and third-party SaaS products that weren't built for programmatic access.

Browser automation is hiring a temp worker to use websites for you — they log in, click through menus, and copy data into a spreadsheet.

Scenario

Procurement agent logs into vendor portal, searches for SKU, adds to cart, fills PO form, screenshots confirmation — triggered by a Slack message.

Solution

In Browser & Computer Use Agents, apply Browser Automation to this scenario: Procurement agent logs into vendor portal, searches for SKU, adds to cart, fills PO form, screenshots confirmation — triggered by a Slack message. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Do this before moving to the next module — reading alone is not enough.

Open the Code Walkthrough below and run it locally. Change one parameter related to Browser Automation (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Highlighted lines show where Browser Automation happens in the code.

1# Browser Automation — minimal example2from openai import OpenAI3
4client = OpenAI()  # create API client5
6# Ask the model to explain this topic7response = client.chat.completions.create(  # core API call for Browser Automation8    model="gpt-4o-mini",9    messages=[10        {"role": "system", "content": "You explain browser automation clearly."},11        {"role": "user", "content": f"What is browser automation?"},12    ],13    temperature=0,14)15print(response.choices[0].message.content)  # show output for debugging

• Treating Browser Automation as a black box without evaluation
• Ignoring cost and latency in production
• Skipping error handling for browser automation

Quick recap — the most important points from this module.