The promise of AI Agents is transformative – that's undeniable. But as enterprises race to adopt the Agent buzzword, we can't afford approaches that won't deliver on that promise.

Perhaps the most dangerous misconception in enterprise AI today is that agents can simply be defined and managed through prompts alone. This prompt-centric approach creates fundamental challenges to implementing agents that enterprises must consider.

Here's the uncomfortable reality: ‘reasoning’ through prompts lacks predictability. The same prompt can yield dramatically different responses depending on factors beyond your control or nuances in the data being passed in. How do you test these prompts when AI models are continuously updated or used in subtly different ways? More critically, how can any enterprise possibly manage this unpredictability across thousands of mission-critical agents?

Workflows provide predictability. They can give an agent a precise series of steps to complete, ensuring these new AI helpers reliably follow the best practices established to keep your business running smoothly and minimize risks. But workflows have traditionally been thought of in the context of people, not autonomous or conversational agents.

And now, all your workflows can be agentic – both in their creation and in their execution.

What does that mean? First, workflows are designed with the help of AI agents. The ability of agents to reason – to suggest new and better ways of getting work done – is powerful and profound. And incorporating this ‘reasoning’ at design time provides this advantage without the exposure brought by spontaneously reasoning at runtime.

This is precisely what we've built with Pega GenAI Blueprint. It leverages a combination of Language Model technologies and our decades of experience to innovatively design workflows that deliver efficiency and predictability.

Once the workflow is designed – and approved by humans – Pega agentic workflows leverage LLMs at runtime as a semantic layer to direct requests to the right workflow. The workflow becomes the knowledge base, prescriptively guiding the agent to capture required data and take the appropriate steps and actions.

The result? You harness the power of conversational agents while maintaining the predictability of workflows.

Experience this enterprise-ready approach to agents by designing a workflow on Pega Blueprint today. And join us at PegaWorld June 1-3 to learn more about Pega's unique approach to agents – architected specifically for enterprise success.

1 This article was originally published by Alan Trefler on LinkedIn on April 10, 2025.

Alan Trefler is an author, and is the Founder and CEO of Pegasystems. He is a Visionary leader, technology change-agent, innovative philanthropist, and trusted advisor to global business executives.

When the power of AI agents embraces the predictability of workflows