Practical AI
The importance of neutral standards is critical for agentic AI development
Organizations are shifting toward fleets of AI agents powered by multiple models
Organizations need AI systems capable of governing other AI systems
Digital labor will become abundant and agents will manage other agents in the post-agentic world
Companies are already deploying thousands and sometimes tens of thousands of AI agents
The agentic transformation has already begun and is not coming in the future
Enterprise software giants are watching their old economic moats erode due to AI agents
Human labor is being repriced in real time as a result of AI agents
AI requires fundamentally different infrastructure approach than traditional cloud computing
ZenML's Kitaru helps developers build resilient, replayable, and observable agent systems
MLOps principles are shaping the future of generative AI workflows and agent infrastructure
Digital labor will become abundant and agents will manage other agents in the post-agentic world
The future of software will be built around AI-first experiences rather than traditional websites and apps