Agent Orchestration Landscape

A comprehensive survey of AI agent frameworks, tools, and platforms.

Last Updated: January 2026

Frameworks & Platforms

Tools and frameworks for agentic workflows, orchestration and agent communication.

Benchmarking

Tools, datasets, and standards for evaluating agent performance and reliability.

Benchmark Methodologies

Common techniques for evaluating agent performance, reliability, and safety.

Evals & Unit Tests

Deterministic assertions on agent outputs. Useful for checking JSON structure, tool call arguments, and strict logic constraints.

Model-Based Grading (LLM-as-a-Judge)

Using a stronger model (e.g., GPT-4o) to score the traces of a smaller model. Evaluates reasoning quality, tone, and adherence to complex instructions.

Trajectory Analysis

Analyzing the step-by-step "thought process" or tool use sequence. Checks if the agent took the optimal path or got stuck in loops.

Human-in-the-Loop Feedback

Collecting implicit (clicks, accept rates) or explicit (thumbs up/down) feedback from end-users to fine-tune agent behavior.