Build Faster with Pega Infinity '26 AI Assistant | Replay Available

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Hi everyone,

A big thank you to everyone who joined our recent AI Expert Circle webinar on Build Faster with Pega Infinity '26 AI Assistant.

For this session, I was joined by Matt Healy, Ryan Easley, and Dileep Thotakura. Matt walked us through the vision behind Infinity Studio and AI-assisted development, Ryan showed the AI Assistant working live, and Dileep spent a substantial amount of time answering questions from the community about architecture, prompting, guardrails, costs, roadmap direction, and where the technology is heading next.

If you missed the session, the replay is now available:

:movie_camera: Build Faster with Pega Infinity '26 AI Assistant | Pega ?

What I enjoyed most about the discussion was that we quickly got beyond the headlines and into the questions practitioners are actually asking.

Questions like:

  • Should I use the embedded AI Assistant or an external coding agent?
  • What makes a good implementation task for AI-assisted development?
  • How much prompting detail is enough?
  • How does the Assistant find and reuse existing assets?
  • What guardrails are built in?
  • How do token costs work?
  • What can I start doing today versus waiting for a future release?

Ryan’s demo also gave a practical look at how the Assistant can work from implementation plans, build supporting artifacts, create tests, and operate safely within isolated branches. We even looked at how the same capabilities can be accessed from tools many developers are already using today.

One theme that kept coming up throughout the webinar was that AI-assisted development is becoming less about generating code and more about helping teams move from requirements to working business solutions faster while still keeping governance, consistency, and best practices at the center.

I’d encourage you to watch the replay, especially if you’re trying to understand where AI Assistant fits into your development approach, or if you’re simply curious about how other Pega practitioners are beginning to use these capabilities in real projects.

After you’ve watched it, I’d love to hear:

  • What part of the discussion resonated most with you?
  • Have you started experimenting with AI Assistant yet?
  • What questions would you like us to cover in future sessions?
  • What examples or prompting techniques have worked well for you?

As always, some of the best ideas in this community come from practitioners sharing experiences with other practitioners. Looking forward to the discussion.

Jay

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@STEWJ
What part of the discussion resonated most with you?
I really adore coding assistants (internal/external) for building the components and application. extending to all ruletypes is awesome and updating skills will benefit lot for improving the code in terms of planning and build time.
Have you started experimenting with AI Assistant yet?
Just started exploring on lab instance.
What questions would you like us to cover in future sessions?
Improving the code base of heritage applications , best prompts for upgrading codebase to latest advanced shapes (workflow improvement ), older applications with less coding comments and historical description data how to deal with it ? Working on Pega frame works using AI assistants for entry level professionals who will be having less domain knowledge, Data Engineering related AI assistants tasks to work like a data scientist
What examples or prompting techniques have worked well for you?
i usually use AI agents like brain storming , planning & research agents on new topics , context and loop engineering to bring more context on chat while exploring new domains, I explore AI agent repositories online and use structures, frameworks and formats to get better outputs.

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