Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

Many enterprise workflows remain locked inside supplier portals, government websites or legacy ERP/CRM screens that lack APIs, while traditional RPA scripts break on the smallest UI tweak. This course covers UI-using agents that combine the DOM, accessibility tree and screenshots to navigate web and application interfaces reliably.

Participants use Playwright, Stagehand and Set-of-Marks (SoM) visual grounding to build an agent that fills forms, navigates tables and handles file uploads/downloads, producing a human-confirmed prototype and a resilience and latency measurement plan.

Who Should Attend?

  • Software and RPA engineers building web and enterprise screen automation
  • AI developers implementing agentic process automation
  • Operational excellence and digital transformation specialists
  • Prerequisite: basic Python or TypeScript and familiarity with HTML/DOM

Key Takeaways

  • Build hybrid UI agents that fuse DOM/accessibility trees with visual screen perception
  • Implement natural-language selectors and self-healing steps that survive UI changes
  • Manage authentication, persistent sessions and multi-step form workflows safely
  • Present live previews and human confirmation gates before final submission or payment
  • Optimise step completion rate, page-wait latency and token cost

Curriculum

From Brittle Selectors to Cognitive UI Agents
  • Limits of XPath/CSS selectors and LLM-driven interface interaction
  • Combining DOM, Accessibility Trees and Set-of-Marks (SoM) visual overlays
Browser Orchestration: Playwright, Stagehand and Browserbase
  • Blending deterministic Playwright code with agentic actions
  • Cloud browser sessions, proxies and parallel execution
Session Handling, Dynamic Pages and Data Extraction
  • SSO/MFA handoff, state persistence and SPA wait strategies
  • Extracting structured records across paginated tables and dynamic dropdowns
Self-Healing Workflows and Action Caching
  • Caching discovered action paths for deterministic replay
  • Invoking the VLM/LLM only when the UI changes to save cost and latency
Human Oversight and Safe Execution
  • Pausing before commit buttons, visual proof logging and live takeover
  • Enterprise case prototype and quality/latency measurement plan

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