ModelRefs / Agentic Systems — Canonical Workflow
Agentic Systems — Canonical Workflow
Canonical Agentic Systems workflow: tool-using models, planners, memory stores, benchmarks and deployment patterns.
Overview
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.
Implementation profile
| Category | agentic-models |
|---|---|
| Implementation maturity | production |
| Primary use cases | agents, enterprise-automation |
| Deployment options | managed-api, self-hosted |
| Architectures | managed-container, self-hosted-cluster |
What this evidence does not establish
- No domain-specific action policy, tool-permission model, or measured task-success threshold is registered.
- The sources provide risk-management and design guidance, not proof of safe autonomy.
Candidate models with published references
- BGE-M3
- GPT-5
- GPT-5 Mini
- Claude Sonnet 4.5
- Claude Opus 4
- Gemini 3 Pro
- Llama 4 Scout
- DeepSeek R1
- Mistral Large 2
- Command R+
- o3
- o4 Mini
Coverage means the model is a candidate worth evaluating for this workflow, not a ranking or a recommendation. Models whose reference pages are still in review are omitted.
Benchmarks relevant to this workflow
- HumanEval+ — Function-level code synthesis with extended hidden tests.
- MMLU — Massive Multitask Language Understanding — 57 academic and professional subjects.
These are the benchmarks whose task shape bears on this workflow. Each one only describes its own protocol and date, so confirm the harness matches your workload before treating a score as evidence.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Agentic Systems — Canonical Workflow.