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AI Agent Guides

Short, practical guides for understanding agent architecture, pricing, benchmarks, and workflow fit.

Fundamentals

Focused explainers for faster buying and workflow decisions.

How agents differ from LLMs and why architecture matters.

The practical difference between model capability and tool-using agents.

How the benchmark works and how to interpret scores.

The formula behind stack scores and architecture scores.

Why static ARscore needs real coding tests and source labels.

Focused explainers for faster buying and workflow decisions.

Ranked agents with workflow and pricing context.

Open-source and free-agent options.

Subscription, API, and total cost comparison.

A workflow-first selection framework.

Focused explainers for faster buying and workflow decisions.

Terminal-first agent workflow and tradeoffs.

OpenAI terminal agent workflow and model pairings.

IDE-native coding with composer and autocomplete.

Git-native open-source coding agent.