2026 Optimizely Web Experimentation release notes

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March

• Released a new version of the AI variation development agent which helps you modify and update existing website elements, create new ones, and generate and apply enhancement suggestions, while maintaining brand consistency by automatically retrieving page styles.
• Improved the look and feel of selecting the parent or child element of a selected element. See Edit elements with the new Visual Editor.
• Introduced a hotkey (keyboard shortcut) to edit the items behind a hover. See Edit interactive or dynamic elements.
• Released a more reliable way to dispatch events and rewritten some of the logic to collect events that use redirects. This ensures a more accurate count. 

February

• Enhanced the new Visual Editor with smoother highlighting.
• Released drag and drop re-arrange in the new Visual Editor.
• Released the following Web Experimentation system tools in Opal to help you use the AI variation development agent:
  • exp_ve_apply_change – Applies a pending change to the Visual Editor.
  • exp_ve_element_glob – Finds elements in the Visual Editor DOM that match a glob pattern.
  • exp_ve_element_grep – Searches for elements in the Visual Editor DOM whose content or attributes match a regular expression.
  • exp_ve_element_read – Reads the content or attributes of a specific element in the Visual Editor.
  • exp_ve_element_tree – Retrieves a partial DOM tree for a specified element and its descendants in the Visual Editor.
  • exp_ve_get change_schema – Retrieves the JSON schema for a specific type of Visual Editor change.
  • exp_ve_get_selector – Generates a robust CSS selector for a given element in the Visual Editor.
  • exp_ve_list_pending_changes – Lists all pending Visual Editor changes for the current experiment or personalization.
  • exp_ve_revert_change – Reverts a specific pending Visual Editor change, undoing its effects.
  • exp_ve_validate_change – Validates a Visual Editor change object against its schema to ensure it is well-formed.

January

• Added the Experimentation Program Overview agent to the Opal Agent Directory which creates a report on how your Optimizely Experimentation program is performing using top experiment and win rate data. 
• Released the following system tools in Optimizely Opal to help you with your Web Experimentation projects. See System tools for Web Experimentation for the full list of available Opal tools, including when to use them, variables, and example prompts. 
  • exp_get_schemas –  Retrieves detailed schemas for various Optimizely entities relevant to Web Experimentation. This is a mandatory first step before using the exp_execute_query tool to retrieve actual data about these entities.
  • exp_execute_query – Executes a template-based query to fetch specific data from your Optimizely Web Experimentation instance. It lets you retrieve detailed information about various entities. 
  • exp_program_reporting_top_experiments – Helps you identify and analyze your highest-performing experiments (A/B tests, multivariate tests, and so on) within Optimizely Web Experimentation. It provides a program-level view of success by ranking experiments based on their lift values.
  • exp_program_reporting_underperforming_experiments – Helps you identify A/B tests that are not yielding significant or positive results, letting you quickly decide whether to stop, re-evaluate, or iterate on them.
  • exp_program_reporting_win_rate – Gives you a high-level overview of the success of your experimentation program by calculating the win rate over a specified period. It is a great way to track the overall effectiveness of your A/B tests.