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Moving Beyond Model Benchmarks: Engineering Agent Evaluation Workflows

Shift from static model benchmarks to dynamic agent evaluation to ensure reliability in production. Learn how to design multi-turn tests that account for tool usage and state changes.

Reducing Agentic Latency with Programmatic Tool Calling

Programmatic tool calling replaces sequential LLM round-trips with sandboxed code execution. This pattern reduces latency and token costs for complex agentic workflows.

Building an Evaluation Harness for Production AI Agents: A 12-Metric Framework From 100+ Deployments

Move beyond simple unit tests for AI agents. Implement a 12-metric evaluation framework to measure retrieval, generation, and agent behavior in production.

Architecting practical AI Agent Guardrails for Operational Resilience

Move beyond simple prompt filtering to build resilient agentic systems. Runtime orchestration, access control, and automated recovery paths.

Multi-Agent Orchestration: Architectural Patterns for Complex Workflows

Move beyond monolithic AI prompts by implementing multi-agent orchestration. Learn how to choose between supervisor, pipeline, swarm, and hierarchical patterns.

Testing Agentic Systems: Managing Non-Determinism in Tool-Calling Workflows

Moving from static LLM prompts to stateful agentic loops introduces non-determinism. Learn how to build reliable testing frameworks for tool-calling architectures.