We're joined by Jeremy Edberg, C-Suite Advisor* at DBOS, Inc., to explore how durable execution works, why it matters for building production-ready AI agents, and what lessons from Netflix-scale reliability engineering apply directly to the age of agentic coding.



*Since recording, Jeremy has become C-Suite Advisor to DBOS, Inc.

KEY TAKEAWAYS

00:00 Introduction 

01:30 DBOS was born from research into replacing the operating system with a database. 

04:00 A career spent making things reliable — from Reddit to Netflix — built Jeremy's obsession with automation. 

09:00 If you do something twice, automate it; make manual steps look like automation. 

12:30 Durable execution lets systems resume from exactly where they last succeeded. 

14:00 Replaying saved LLM outputs removes non-determinism from agentic debugging. 

16:00 In agentic coding, the bottleneck isn't writing code — it's deployment, testing, and operations. 

20:00 DBOS adds roughly 1% overhead to Postgres, making durable execution practical at scale.

28:00 Agentic AI created a new class of workloads between instant API calls and long bat

RESOURCES MENTIONED

DBOS, Inc

https://www.dbos.dev

Transact library

https://www.dbos.dev/dbos-transact

CockroachDB

https://www.cockroachlabs.com

Dosu

https://dosu.dev/

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We explore how agents introduce new challenges for distributed systems, why long-running autonomous workflows require interruption-tolerant execution, and how durable promises provide a simpler mental model for building reliable multi-agent systems.

Key Takeaways:

00:00 Introduction.

02:20 A career start during the rise of AWS and cloud computing shaped Dominik’s focus on distributed systems.

04:10 Separating the concept of durable execution from specific implementations led to the idea of interruption-tolerant systems.

05:15 Failures as interruptions — voluntary or involuntary — lead to a broader, more practical model for resilient execution.

12:40 Simplifying complex concepts and why engineers often struggle to align their mental models when designing distributed systems.

14:10 Dominik defines an agent as a combination of a model, tools, and a system prompt, while distinguishing between an agent definition and a running agent instance.

23:30 Many effective agents are simply tool-calling loops, despite the complexity of the surrounding ecosystem.

26:20 Running agents in enterprise environments introduces distributed systems challenges, especially when workflows involve long-running or expensive operations.

33:15 Unlike traditional microservices, retrying agent operations can be extremely expensive when LLM calls or data pipelines are involved.

40:20 A durable promise is a simple mechanism for coordination and recovery in distributed agent workflows.

Resources Mentioned:

Dominik Tornow

https://www.linkedin.com/in/dtornow/

Resonate HQ | LinkedIn

http://www.linkedin.com/company/resonatehqio/

Resonate HQ | Website

https://www.resonatehq.io/

"Think Distributed Systems" by Dominik Tornow

https://www.manning.com/books/think-distributed-systems

Temporal (durable execution platform)

https://temporal.io

Thanks for listening to “Hello Agent!: The podcast at the intersection of data & agents.” If you loved this episode, let us know with a 5-star review! Remember to subscribe so you don’t miss an episode. To learn more about Redpanda, visit redpanda.com

#RealTimeData #DataStreaming #Redpanda

Key Takeaways:

00:00 Introduction.

02:00 Nicolas’ focus on solving technical problems for the real world.

05:43 Programming in C builds a deep appreciation for low-level systems.

09:39 Securing proprietary data matters more than models in enterprise AI.

15:32 Vector data can expose sensitive information to attackers.

20:59 Auth systems are often weaker than expected, even for sensitive data.

25:03 Agentic AI removes the perimeter, making zero trust essential.

30:06 Poisoned data is hard to trace across agent systems.

35:07 Deleting keys makes sensitive data unreadable immediately.

40:48 Modern cryptography is no longer a bottleneck, making strong encryption practical.

45:06 Zero trust isn’t optional — the future of agentic AI depends on it.

Resources Mentioned:

Nicolas Dupont

https://www.linkedin.com/in/cyborgnico/

Cyborg Inc. | LinkedIn

https://www.linkedin.com/company/cyborginc/

Cyborg Inc. | Website

https://www.cyborg.co/

Cyborg Blog: Vector Embeddings Are Not One-Way Hashes 

https://www.cyborg.co/blog/vector-embeddings-are-not-one-way-hashes

Thanks for listening to “Hello Agent!: The podcast at the intersection of data & agents.” If you loved this episode, let us know with a 5-star review! Remember to subscribe so you don’t miss an episode. To learn more about Redpanda, visit redpanda.com

#RealTimeData #DataStreaming #Redpanda