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Our Summer '25 Product Roadmap Series.

Get a first look at what’s coming from Optimizely, shared by our product leaders in a fresh, on-demand format. The perfect fit for your busy summer schedule!

Start with the ultimate Optimizely One Intro to the Series which even includes some Opticon teasers. Then head over to our sessions which span all the hottest topics of the summer: AI, Analytics, Testing & Personalization, Content, and Commerce.

Jump in!

And now on to our product updates!

Opal Tools Management

Admins will be able to manage, view and add tools in the Tool Directory, which can then be used by agents for executing specific use cases.​

Examples of pre-built tools include:​

• Perform web search​

• Upload files and answer questions about them​

• Get information/support on Optimizely products​

• Action execution (e.g. create a task, generate a brief, suggest flag variables)​

Agent Directory

Leverage pre-built (or create your own!) advanced agents that excel at specific tasks by following a set of instructions and accessing tools.​​

Examples include:​

• Experiment Planning Agent​

• Personalization Ideation Agent​

• Campaign Brief Agent​

Workflow Agents

In Opal platform, admins will be able to coordinate multiple specialized agents and behavioral augmentation agents in a sequence or simultaneously to accomplish tasks on their behalf.​​

Examples include:​

• Content Marketer Agent (conduct keyword research, formulate )​

• Experiment Development Agent (ideate, plan test, build variations, review, summarize results)​

Opal in Slack and Microsoft Teams

Slack user? You'll be able to use Opal exactly how you use it in Optimizely, but from within Slack's interface., including:​​

• Getting test ideas based on a URL
• Creating a campaign in CMP​
• Building comprehensive briefs​

Your chat history in Slack will also be preserved in Opal within Optimizely's interface, so you can easily refer back to previous threads.​

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Opal RAG

Opal will reference assets and activities, including Opti Graph, experiments, content, tasks and campaigns in your instance as source of context for its output.​

This will let you ask questions about your experiments, tasks, campaigns and content, and generate exportable reports with custom prompts (e.g., “What were the results of the experiments run in the last 30 days?).