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Agentic workflows

Agentic workflows, explained on one canvas

An agentic workflow is a process where AI agents execute real steps: reading documents, classifying cases, chasing missing information, preparing payments, drafting communication. The hard part is not the technology. It is deciding which steps, with how much autonomy, under whose supervision. That is a design problem, and it deserves a design tool.

The three levels of autonomy

Autonomy is a dial, not a badge. The same claims-triage agent can act on low-value claims and merely recommend on complex ones, with a decision block routing between the two. On the canvas, that rule is visible to everyone.

Humans in the loop, by design

Hybrid steps put a person and an agent on the same task. Human gates stop the flow before consequential actions: a payment, a customer communication, a hire. Controls, preventive, detective and corrective, supervise agents continuously: confidence thresholds before, sampling and drift alerts during, reconciliation and rollback after. A risk matrix (impact × likelihood) tells you where supervision is mandatory rather than optional.

Designing one, step by step

Start with the as-is: who does what today, in which systems, at what volumes. Then reallocate: move steps to the AI Agents lane deliberately, one at a time, setting autonomy and supervision as you go. Validate the design against governance rules, price it against the hours it frees, and break each agent step into a build-ready blueprint. The tools for each of these stages are described in AI process mapping and business process redesign.

🤖 Classify claim type and urgency
Humans 👤 Assess coverage
Hybrid (HITL) 🤝 Review AI recommendation
AI Agents 🤖 Extract claim data
Systems ⚙️ Send SEPA payment

Reallocating a step is moving it to another lane. The decision is the design.

an agentic invoice workflow: intake, screening, matching, exception and supplier status agents supervised by controls
An agentic invoice workflow: five agents, three controls, one hybrid step, one human approval gate, one audit trail.
hands moving a glowing card between colored rows on a dark glass board

Autonomy is granted per step, not per tool.

Frequently asked questions

What is an agentic workflow?

An agentic workflow is a business process in which one or more AI agents execute steps with a degree of autonomy: reading inputs, making or recommending decisions, acting in systems, and handing off to humans or other agents. It differs from simple automation because the agent handles variability and judgement, not just fixed rules.

What is the difference between an AI agent and an AI assistant?

An assistant responds when a person asks. An agent owns a step in a process: it is triggered by the flow, works towards the step's outcome across systems, raises exceptions, and hands off the result. The design question is not what it can do but what it is allowed to do, which is why autonomy levels matter.

When should a human stay in the loop?

As a rule of thumb: whenever the step's impact and likelihood of harm are high, when a decision affects people's rights or money above a threshold, or when regulation requires accountability. In practice you encode this with hybrid steps, human gates before consequential actions, and controls that supervise the agents.

How do I start designing an agentic workflow?

Map the as-is first, as it really runs. Then decide step by step what moves to an agent, at which autonomy level, with which supervision. A design studio that models executors, autonomy, risk and controls turns this from a whiteboard argument into a reviewable artifact.

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