Optimizely Agent Platform workshop: What tasks would you give an agent today?

Most agentic AI plans stall on execution. Teams brainstorm what an agent could do but never answer what it needs to know, who signs off or what happens when it's wrong. This workshop answers those questions live, so you leave with an agentic AI program scoped in Agent Platform.

What you will get from this workshop

You'll leave with a working use case. Here's how we get there via the four questions we'll answer together:

  1. What task would you hand an agent?

    Not "What could AI theoretically do?" The actual task sitting on your desk that you'd genuinely trust an agent with, today.

  2. What would it need to know?

    Brand voice, past campaigns, compliance rules, your organization's own knowledge. This is the difference between an agent that's fluent and one that's useful.

  3. Who'd need to sign off?

    That depends on whether you're evaluating a business case, defining guardrail approvals or looking to scale. We'll name who's involved.

  4. What happens when the agent is wrong?

    This is the question everyone skips, but it's the one that determines whether the agent scales or gets shut down.

Why now?

Generative AI adoption is close to universal, but organizations aren't scaling that capability yet. The gap between adoption and scale comes down to process, orchestration and governance.

82%

Of enterprise leaders use generative AI weekly (Wharton)

95%

Of AI projects fail to scale beyond the pilot stage (MIT)

68%

Of CMOs say their teams struggle to operationalize generative AI (BCG) 

Optimizely Agent Platform, is built to close exactly that gap. This workshop places your organization on the adoption-to-scale curve and shows you how to close the remaining gaps. 

Who is this workshop for?

Wherever you are with Agent Platform, the four questions apply. The answer depends on your stage of adoption.

Stage What you leave with
Pre-adoption and evaluating A business case for your first agent, backed by readiness signals.
Licensed but not yet live Guardrail approval and a path to building your first agent.
Deployed, live and scaling A scale plan built on a maturity placement.

What you will walk away with

  • Your first agentic AI use case, fully scoped.
  • A governance model matched to your organization.
  • A readiness self-assessment to define which gaps you must close before you build.
  • A start date, not a maybe.

This isn't a demo. It's already running.

Most agent demos are invoked manually, in a chat window, answering a question the agent's already seen. This isn't that.

In our Agent Platform and CMS 13 sandbox, a multi-step compliance workflow agent runs end-to-end with no manual invocation. It drafts, checks and routes on its own, the way it would in production.

Getting there took real upfront work. The workflow went through several rounds of revisions before it held up against adversarial test cases, the kind a legal team would throw at it. That calibration discipline carries into every agent we design, whether it's running end-to-end already or still on the blueprint.

You'll walk through that same discipline live, applied to your problem, not a rehearsed one.

Valtech is an Optimizely Premier Platinum Partner , with a dedicated Agent Platform practice: forward-deployed engineers, Agent Platform SMEs and more than 6,000 people across strategy, data and engineering in 26 countries.

Ritu Madan
Technology Practice Principal, OMVP
Shannon Ryan
Chief Growth Officer

Bring us the question you haven't answered yet

Come to this workshop with the task you'd give an agent if you trusted it. You'll leave with answers to the other three questions.

Schedule a discovery call