Brendan Gregg is an Australian systems performance engineer at OpenAI, where he works on datacenter optimizations for ChatGPT. He invented flame graphs and the USE Method, pioneered eBPF observability, and is the author of landmark books including 'Systems Performance: Enterprise and the Cloud'. His work is credited with saving the industry over $1 billion in compute costs. Previously an Intel Fellow and performance engineering leader at Netflix, Gregg is one of the most influential engineers in Linux and cloud infrastructure.
Cindy Sridharan is a distributed systems engineer, O'Reilly author, and influential technical writer based in San Francisco. Known online as @copyconstruct, she wrote the seminal O'Reilly book 'Distributed Systems Observability' and runs the Systems Distributed newsletter on Substack. She is widely respected for her long-form thinking on observability, testing in production, microservices architecture, and engineering culture. She spent years as an engineer at imgix, led the Prometheus user group in San Francisco, and has spoken at major industry conferences including QCon and GOTO. Her Medium essays on monitoring, testing, and systems thinking have shaped how a generation of engineers thinks about building resilient software.
Liz Fong-Jones is a Technical Fellow at Honeycomb.io, renowned SRE practitioner, co-author of 'Observability Engineering' (O'Reilly), and one of the most influential voices in the observability and platform engineering space. With 18+ years in software engineering spanning Google (11 years) and Honeycomb, she bridges deep technical expertise with fierce advocacy for labor rights, trans inclusion, and workplace equity. She led the Google Walkout Strike Fund in 2018, founded the Solidarity Fund by Coworker, and sits on the OpenTelemetry governance committee - all while speaking at every major SRE and DevOps conference on Earth.
Mat Ryer is a London-based Go programmer, open-source creator, author, and long-time host of the Go Time podcast. Known for building beloved Go tools like xbar (18k+ GitHub stars), moq, and the `is` testing framework, he has been writing Go since before its v1 release. He authored 'Go Programming Blueprints' and spent years as a principal engineer at Grafana Labs building AI agents and observability tools. His characteristic blend of deep technical craft, game-show energy, and dry British wit has made him one of the Go community's most recognizable voices.
Theo Schlossnagle is a serial entrepreneur, software engineer, and investor who has spent three decades pushing the edges of distributed systems and scalable infrastructure. Founder of OmniTI (1997), Circonus (2010), and General Partner at L42 Ventures, he is a Distinguished Member of the ACM, an IEEE member, co-chair of ACM's Queue Magazine, and the author of 'Scalable Internet Architectures'. Beyond software, he runs a butcher shop in Maryland, maintains a farm retreat in West Virginia, and has left Twitter for greener (and more federated) social pastures.
ZeroEval is a New York-based AI startup from Y Combinator's Summer 2025 batch building an auto-optimizer for AI agents. Founded by Jonathan Chavez and Sebastian Crossa - two friends who met in college in Mexico - the platform captures every interaction your AI agent makes, scores quality with custom LLM judges, and automatically turns real production data into better prompts. The result: agents that get smarter after launch without manual intervention. Trusted by DoorDash, Datadog, Hugging Face, and Harvard Medical School, ZeroEval closes what the founders call 'the last mile reliability gap' in agentic AI.
Humanloop was an enterprise LLM development platform founded in 2020 as a UCL spinout, offering prompt management, evaluations, and observability tools for teams building AI applications. With customers like Duolingo and Gusto, it raised ~$8M and reached ~$3.8M ARR before being acqui-hired by Anthropic in August 2025, after which the platform was sunsetted on September 8, 2025. Its technology and team live on inside Anthropic's enterprise console.