Your Ops Team Pays the Price for AI Adoption
October 15, 2026
In this episode of The Agentic Review podcast, Zichuan Xiong, Global Head of AIOps at Thoughtworks, joins Itamar Friedman and Nnenna Ndukwe to look at what AI is really doing to the cost of running software. Over two years, Zichuan’s team grew from a single RAG use case to 25 to 35 operational agents for enterprise clients. He has seen both the job-level gains and the system-level bill: one customer raised AI adoption 1.5x in eight months while operations costs rose 10x. He makes the case for an operations-first SDLC and explains why semantic drift slips past LLM tracing. Zichuan also argues that turning tribal knowledge into agent-ready context needs a dedicated new role.
In this episode of The Agentic Review podcast, Zichuan Xiong, Global Head of AIOps at Thoughtworks, joins Itamar Friedman and Nnenna Ndukwe to look at what AI is really doing to the cost of running software. Over two years, Zichuan’s team grew from a single RAG use case to 25 to 35 operational agents for enterprise clients. He has seen both the job-level gains and the system-level bill: one customer raised AI adoption 1.5x in eight months while operations costs rose 10x. He makes the case for an operations-first SDLC and explains why semantic drift slips past LLM tracing. Zichuan also argues that turning tribal knowledge into agent-ready context needs a dedicated new role.
Key Takeaways:
- Why the SDLC should start from operational context instead of ending with it
- How semantic drift causes errors that LLM tracing never flags
- Why feed-forward controls are harder to build, and more valuable than feedback
- The new roles teams need to codify tribal knowledge for agents
- Why the pull request is no longer the right unit of review
Zichuan Xiong is Global Head of AIOps at Thoughtworks, where he leads AI-powered operations across the company's managed services business. With almost 20 years at Thoughtworks, he has moved from being one of the first designers to bring wireframing into the company's software delivery, to front-end development, to building AI solutions for business problems. Today, Zichuan focuses on agentic AIOps, SRE modernization, and the control systems enterprises need to run AI safely in production.
Episode resources
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