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Interactive AI avatar guide: design an agent that turns knowledge into action

Downloads | AI workshop guides

An interactive AI avatar works when it has a role, approved knowledge, a goal and a clear next action for the user. Ben English of Kaltura taught that method in a hands-on workshop at aiblLIVE London 2026. Tables designed their own agent on paper before configuring one.

This free guide turns the session into a method you can run with your own team, whichever agent builder you use.

How do you design an AI agent that does more than answer questions?

Make four decisions before you build anything: the agent’s role, what it knows, the goal it works towards and the action it offers at the end. In Ben’s demo, the goal was a meeting booked with a human. Other goals include a passed test, a share of training videos watched or a captured email address.

This AI has a role, it has a purpose, and it has knowledge.

Ben English, Director of Solution Engineering, AI Specialist, EMEA and APAC, Kaltura

How do you stop an AI avatar giving answers you have not approved?

Give it only approved content and let it answer from nothing else. Ben described this as retrieval-augmented generation. The agent finds the relevant passage in your content, then the language model turns it into a reply. It does not go to the open web. Content that changes often needs a named owner.

How do you get users from a conversation to a next step?

Tell the agent what the next step is and let it offer it inside the chat. In the demo, it answered a question, generated next-step buttons, pulled a short video clip and registered the visitor for an event. Once it judged them a serious buyer, it booked a meeting with an expert into their calendar.

How do you set the tone and topics for an AI agent?

Write them into the agent’s playbook, along with its audience and opening phrases. You can ask for a calmer or more energetic tone. Off-limits topics depend on the setting: a customer website should avoid politics and religion, but a university that teaches both needs them left on.

What should the agent do? What does it need to know? And what should happen next?

Ben English, Director of Solution Engineering, AI Specialist, EMEA and APAC, Kaltura

Key takeaways

  • Start on paper. Fill in role, knowledge, goal and action for one real use case.
  • Give it a goal you can count. A booked meeting or a passed test shows whether it works.
  • Feed it only approved content. Keep an owner for anything that changes.
  • Read the analytics weekly. The questions asked show what to fix next.

About the workshop

Kaltura logo

Ben English is Director of Solution Engineering and an AI specialist for EMEA and APAC at Kaltura, the video and streaming company now building conversational AI avatars. He ran this workshop on the Customer track at aiblLIVE London on 20 October 2026.

What’s in the full guide

If you want an agent that does more than answer questions, this is a method you can run next week. The full PDF goes step by step.

  • An eight-step method from use case to live agent, with a one-page design canvas.
  • The worked example from the room: one visitor taken from first question to a booked meeting.
  • Templates and a checklist for the playbook, next-step prompts and an adaptive quiz.
  • Five actions to take back to your own organisation.

For customer experience, marketing, events, learning and support leads. Seven pages, about a nine-minute read.

Design an agent that gets results

Interactive AI avatar guide: design an agent that turns knowledge into action
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