Techzine TV podcast
In the Techzine TV podcast we analyze B2B IT solutions, strategies, and trends. IT companies are happy to invite us to talk about what they are working on and what they are going to bring to market. We visit them all around the world, and in some cases, they visit us in our office.
We have a good understanding of how technologies work, or how they should work. We also hear a lot from the market about what companies need or where things go wrong. This gives us the ability to have really in-depth conversations on technology, strategies, and products, but we always try to keep it practical and easy to understand.
We explain innovations, interpret new IT concepts, and use practical examples to make complex technology understandable for everyone. Where necessary, we bring in experts to clarify matters further. The goal is to help IT professionals, decision makers, and other listeners better understand IT developments, but also to help them in their search for new solutions for their business and not get stuck on buzzwords and one-liners.
The Techzine TV podcast is an evolution of the previous Techzine Talks on Tour series. We still bring a lot of conversations and interviews from events to this series. We record so many video interviews nowadays, so we can select the best ones for this podcast series.
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Techzine TV podcast
Pega wants to make AI performance and cost predictable
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At PegaWorld in Las Vegas, Techzine TV sat down with Don Schuerman, CTO and head of marketing at Pega, for a wide-ranging conversation about the state of enterprise AI. We discuss with him why simply dropping AI tools into existing workflows is not enough, and why enterprises must fundamentally reimagine their processes, teams, and application architectures to capture real value from AI.
Predictability is a key concept Schuerman returns to regulary. Predictability of the outcome of AI workflows, but definitely also of the cost. Accuracy is also something that needs to be determined properly when it comes to AI. As Schuerman points out during our conversation, an 85% AI accuracy rate is actually a 15% failure rate for a bank. If you compound agent errors, the failure rate will become exponentially worse. We also dig into the cost of tokens. Schuerman gets into how Pega's deterministic orchestration approach should keep AI spending controllable. It makes it possible to offer outcome-based pricing tied to workflows executed rather than tokens consumed.
Schuerman also walks us through the major evolution of Pega Blueprint. That used to be a rather basic ideation tool when it launched in April 2024, but is has been developed into a full design-to-build accelerator. On the new Customer Engagement Studio, he tells us that it brings next best action capabilities to marketing teams who don't have a data science background. The end of the conversation focuses on how to build a clear framework for measuring AI success: better processes, faster delivery, and uncompromised trust.
Key takeaways:
• Enterprises must reimagine workflows, processes, and team interactions, not just add AI tools
• AI accuracy means different things to different people
• Pega's strategy separates non-deterministic AI (design/build) from deterministic execution (run)
• Pega Blueprint now accelerates both the design phase and the build phase of application development
• Applications need to evolve from screen-and-database collections to process, agent, and knowledge collections exposed via MCP
• Outcome-based pricing charges per workflow executed, not per token burned
• Customer Engagement Studio wants to democratize next best action for non-data-science marketing teams
• Infinity 26 supports bring-your-own models, including Mistral for European clients
Chapters:
1:13 - Reimagining enterprise workflows and teams for AI
1:35 - The predictability problem: why 85% accuracy isn't enough
2:25 - Predictability of cost and the tokenomics challenge
3:32 - AI across design, build and run: a smarter architecture
4:41 - Pega Blueprint: from ideation tool to full build accelerator
8:53 - Rethinking application architecture: apps as MCP targets
11:41 - Outcome-based pricing: paying per workflow, not per token
15:49 - Customer Engagement Studio: next best action for all
18:31 - Infinity 26: platform flexibility and bring-your-own AI models
20:05 - Measuring success: better, faster, and trustworthy