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Build Fast, Govern Faster: The Real Path To Agentic Success

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Manage episode 525092206 series 3499431
Content provided by Evan Kirstel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Evan Kirstel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Interested in being a guest? Email us at [email protected]

What if the secret to scaling AI agents has nothing to do with better prompts and everything to do with smarter integration? We sit down with Rich Waldron Co-founder & CEO of Tray dot ai to unpack how an integration-first architecture turns agent hype into measurable business outcomes. From cloud-native orchestration to resilient API handling, Rich explains why the hardest part of agents isn’t connectivity—it’s everything behind it: concurrency, retries, governance, logging, and security.
We dig into the real reasons enterprise pilots stall and the pattern he sees among programs that succeed: IT-led, department-partnered builds with clear ROI, tight scopes, and fast iteration cycles. Rich shares a standout customer story migrating hundreds of integrations off a legacy vendor while launching agentic workflows on a single governed platform—delivering 60% lower integration costs and three times faster builds. Along the way, we explore how engineering teams use AI coding tools to prototype faster and offload grunt work, freeing time for architecture and testing without threatening roles.
If you’re choosing where to start, accelerators for ITSM, HR, support, and knowledge make time-to-value tangible and create a structure teams can adapt to proprietary data and processes. We also cover the growing priority of enterprise governance: controlling which tools agents can access, how data moves, and how identities map across systems. Rich outlines Tray’s Agent Gateway for MCP—adding authentication and permissioning and exposing Trey-built tools to other services in a controlled way—so CIOs can move quickly without giving away the keys to the kingdom.
Ready to move from pilot to production with confidence? Follow, share, and leave a review to tell us where your organization is on the journey—and what’s blocking your next agent from going live.

Support the show

More at https://linktr.ee/EvanKirstel

  continue reading

Chapters

1. Build Fast, Govern Faster: The Real Path To Agentic Success (00:00:00)

2. Setting The Stakes For AI At Work (00:00:01)

3. Trey’s Origin And Big Idea (00:00:30)

4. Beyond Legacy Middleware (00:01:50)

5. Why AI Pilots Stall (00:03:23)

6. Case Study: Migrating And Modernizing (00:05:24)

7. Speed And Iteration As Advantage (00:07:08)

8. Impact On Engineering Teams (00:08:19)

9. Agent Accelerators That Work Now (00:10:01)

10. Platform-Agnostic Governance (00:11:36)

11. Coexisting With Legacy Stacks (00:13:32)

12. Roadmap: Orchestration And Agent Gateway (00:14:39)

13. Closing And Listener Resources (00:16:08)

578 episodes

Artwork
iconShare
 
Manage episode 525092206 series 3499431
Content provided by Evan Kirstel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Evan Kirstel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Interested in being a guest? Email us at [email protected]

What if the secret to scaling AI agents has nothing to do with better prompts and everything to do with smarter integration? We sit down with Rich Waldron Co-founder & CEO of Tray dot ai to unpack how an integration-first architecture turns agent hype into measurable business outcomes. From cloud-native orchestration to resilient API handling, Rich explains why the hardest part of agents isn’t connectivity—it’s everything behind it: concurrency, retries, governance, logging, and security.
We dig into the real reasons enterprise pilots stall and the pattern he sees among programs that succeed: IT-led, department-partnered builds with clear ROI, tight scopes, and fast iteration cycles. Rich shares a standout customer story migrating hundreds of integrations off a legacy vendor while launching agentic workflows on a single governed platform—delivering 60% lower integration costs and three times faster builds. Along the way, we explore how engineering teams use AI coding tools to prototype faster and offload grunt work, freeing time for architecture and testing without threatening roles.
If you’re choosing where to start, accelerators for ITSM, HR, support, and knowledge make time-to-value tangible and create a structure teams can adapt to proprietary data and processes. We also cover the growing priority of enterprise governance: controlling which tools agents can access, how data moves, and how identities map across systems. Rich outlines Tray’s Agent Gateway for MCP—adding authentication and permissioning and exposing Trey-built tools to other services in a controlled way—so CIOs can move quickly without giving away the keys to the kingdom.
Ready to move from pilot to production with confidence? Follow, share, and leave a review to tell us where your organization is on the journey—and what’s blocking your next agent from going live.

Support the show

More at https://linktr.ee/EvanKirstel

  continue reading

Chapters

1. Build Fast, Govern Faster: The Real Path To Agentic Success (00:00:00)

2. Setting The Stakes For AI At Work (00:00:01)

3. Trey’s Origin And Big Idea (00:00:30)

4. Beyond Legacy Middleware (00:01:50)

5. Why AI Pilots Stall (00:03:23)

6. Case Study: Migrating And Modernizing (00:05:24)

7. Speed And Iteration As Advantage (00:07:08)

8. Impact On Engineering Teams (00:08:19)

9. Agent Accelerators That Work Now (00:10:01)

10. Platform-Agnostic Governance (00:11:36)

11. Coexisting With Legacy Stacks (00:13:32)

12. Roadmap: Orchestration And Agent Gateway (00:14:39)

13. Closing And Listener Resources (00:16:08)

578 episodes

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