Insights from Cleric: Building an Autonomous AI SRE // Willem Pienaar // #290

Willem Pienaar is the Co-Founder and CTO of Cleric. He previously worked at Tecton as a Principal Engineer. Willem Pienaar attended the Georgia Institute of Technology.Insights from Cleric: Building an Autonomous AI SRE // MLOps Podcast #289 with Willem Pienaar, CTO & Co-Founder of Cleric.// AbstractIn this MLOps Community Podcast episode, Willem Pienaar, CTO of Cleric, breaks down how they built an autonomous AI SRE that helps engineering teams diagnose production issues. We explore how Cleric builds knowledge graphs for system understanding and uses existing tools/systems during investigations. We also get into some gnarly challenges around memory, tool integration, and evaluation frameworks, and some lessons learned from deploying to engineering teams.// BioWillem Pienaar, CTO of Cleric, is a builder with a focus on LLM agents, MLOps, and open source tooling. He is the creator of Feast, an open source feature store, and contributed to the creation of both the feature store and MLOps categories. Before starting Cleric, Willem led the open-source engineering team at Tecton and established the ML platform team at Gojek, where he built high-scale ML systems for the Southeast Asian Decacorn.// Related LinksWebsite: willem.co --------------- ✌️Connect With Us ✌️ -------------Join our Slack community:https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup:https://go.mlops.community/registerCatch all episodes, blogs, newsletters, and more:https://mlops.community/// MLOps Swag/Merch⁠https://shop.mlops.community/⁠Connect with Demetrios on LinkedIn:https://www.linkedin.com/in/dpbrinkm/Connect with Willem on LinkedIn:https://www.linkedin.com/in/willempienaar/Timestamps:[00:00] Willem's preferred coffee[00:18] Takeaways[02:28] AI SRE Challenges[06:07] Complexity in Knowledge Graphs[16:25] Agent Budget Loops[20:07] AI Knowledge Graph Triage[24:21] Memory in AI Agents[31:32] Alert Fatigue and UX[38:21] Pricing for Agent Solutions[41:34] Tool Integration Challenges[45:52] Agent Root Cause Analysis[50:56] True Resolution Challenges[55:20] Wrap up