AI browsers like Atlas may initially refuse to scrape sites like LinkedIn due to built-in guardrails. Explicitly prompting the tool to "use your agent mode" can often serve as a workaround to bypass these restrictions and execute the task.
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The agentic nature of browsers like ChatGPT Atlas, where they visually process the screen and act like a user, makes them robust but not fast. For quick operations under five minutes, traditional methods or faster AI browsers like Dia are more efficient.
Atlas can navigate websites like LinkedIn, identify potential contacts based on a query, and click through to extract hidden information like emails, compiling it all into a ready-to-use list without any coding required.
Honeybook built a ChatGPT agent that logs into LinkedIn, searches for candidates based on a job description, and applies nuanced filters (e.g., tenure, location, activity). This automates a time-consuming, multi-step workflow, freeing up the hiring team for higher-value tasks.
Instead of guessing how to make your site more compatible with new AI browsers, directly ask the AI itself. Prompt ChatGPT with your URL and ask what changes are needed on your site to ensure the right answers appear when users search with the Atlas browser.
The rise of AI browser agents acting on a user's behalf creates a conflict with platform terms of service that require a "human" to perform actions. Platforms like LinkedIn will lose this battle and be forced to treat a user's agent as an extension of the user, shifting from outright bans to reasonable usage limits.
You can instruct an AI browser to navigate through your product's user flows page-by-page. The agent will document each step and can even include screenshots, automating what is typically a very manual and time-consuming process for product teams.
AI-powered browsers can instantly open tabs for all your competitors and then analyze their sites based on your prompts. Ask them to compare pricing pages, identify email collection methods, or summarize go-to-market strategies to quickly gather competitive intelligence.
For years, businesses have focused on protecting their sites from malicious bots. This same architecture now blocks beneficial AI agents acting on behalf of consumers. Companies must rethink their technical infrastructure to differentiate and welcome these new 'good bots' for agentic commerce.
When an agent fails, treat it like an intern. Scrutinize its log of actions to find the specific step where it went wrong (e.g., used the wrong link), then provide a targeted correction. This is far more effective than giving a generic, frustrated re-prompt.
Contrary to being overhyped, AI agent browsers are actually underrated for a small but growing set of complex tasks like data scraping, research consolidation, and form automation. For these use cases, their value is immense and time-saving.