From the SREGym team

Blog

Experiments, findings, and field notes on building reliable SRE agents.

Latest writing

Community

SREGym at Frontier Data Summit: Community, Conversations, and What’s Next

Conversations about AI for SRE, our growing community, and a look ahead to SREGym 2.0.

Jackson Clark · Tianyin Xu

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Frontier Data Summit’s featured-poster card for SREGym, presented by Jackson Clark on October 8, 2026, in San Francisco.
Research

Jev-Driven SRE Diagnosis: What Worked and What Failed

A Jev-driven pipeline chooses where to investigate and which cluster evidence supports a diagnosis.

Yiming Su · Saad Mohammad Rafid Pial · Jackson Clark · Tianyin Xu

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Jev selects a component from a cluster snapshot, then reviews collected evidence. A supported cause produces a diagnosis result; otherwise, investigation continues with another component.
Research

Turning Failure Postmortems into SRE-Benchmark Problems

Students from UIUC++ SRSE created 30+ problems in SREGym from postmortem reports of noteworthy system failures.

Tianyin Xu · Saad Mohammad Rafid Pial · Munim Thahmid · Mohammad Elsharqawy · Mahdiya Rahman Sukanya · Sai Hari Krishnan · Sumaiya Islam · Tanzim Hossain Romel · Abdallah Adel · Varuni HK · Jackson Clark

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From postmortems to SREGym problems: reports of real incidents and their causes become reproducible faults for testing SRE agents.
Research

Can Jev Make SRE Agents More Reliable?

We tested TypeSafe AI's Jev as a decision layer for SRE agents.

Jackson Clark · Saad Mohammad Rafid Pial · Yiming Su · Tianyin Xu

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The agent investigates and repairs; Jev ranks and reviews. Pass rate: 40% without Jev, 48% with Jev.