Tag: enterprise ai

A practical evaluation loop for multi-agent workflows that catches demo-friendly failures in task handoff, tool use, permissions, latency, and completion criteria before release.

Capability is no longer the hard question about AI agents. What the agent is permitted to do, and whether it will do it successfully, are. Here is why that distinction matters architecturally.

OpenAI's April 2026 Agents SDK update matters because sandboxed execution, manifests, resumable state, and memory move agents closer to real production automation.

A practical map of NVIDIA NeMo for teams that want to curate data, fine-tune open-source LLMs, evaluate them, and move from research checkpoints to production inference.