Agentic Systems — Canonical Workflow

What this reference supports

Agentic systems give a model the ability to plan, call tools, and execute multi-step tasks autonomously, pairing reasoning models with structured tool schemas, memory stores, and circuit breakers to convert language into action while keeping cost and reliability in budget, unlike a single-turn chat interaction.

Use this page to check whether your use case needs autonomous multi-step execution rather than a simpler single-turn workflow, which models and managed-container or self-hosted-cluster architectures are compatible, and which benchmark references — such as HumanEval and MMLU — speak to tool-use and planning reliability for candidate models.

Workflow fit here is provisional decision support based on goal, data, constraints, risk, and available evidence — it does not guarantee reliable autonomous execution. Test the candidate stack on representative multi-step tasks, including failure recovery, cost under retries, and tool-call error handling, before relying on it for production automation, and keep a human-approval gate for high-consequence actions.