Tag: llmops
LLM deployment: Why human review beats automated testing
Automated tests miss the subtle quality issues that make AI deployments dangerous. Knight Capital lost hundreds of millions in 45 minutes from one deployment bug. Here is how to build LLM deployment pipelines that combine automated safety checks with human judgment, using golden datasets and canary deployments to prevent production disasters.
LLMOps is more Ops than LLM
LLMOps success depends more on proven operations discipline than AI-specific tooling. With a large share of agentic AI projects facing cancellation in the next few years, the teams that survive apply Google SRE principles to LLM infrastructure rather than treating it as something that needs special handling.
Prompts are code - treat them like it
Production AI systems fail when prompts lack version control. Teams building reliable AI use Git workflows with tools like Helicone and Braintrust for automated prompt testing, code review, and staged deployment. Undisciplined prompt management is one reason so many agentic AI projects stall before production.