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Here you can see how the service is built: the system design, data handling, quality checks, security measures, and any AI-supported workflow behind it. This helps you judge how the work will be done and what to expect in practice.
Agent-based workflow architecture

Role, tools, permissions, data boundary, review loop.

Agent projects often go wrong before anyone writes the first prompt. We start by defining the job the agent should do, which tools and data it may use, and how a person reviews its work so it stays within that scope.

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Who this is for

For teams planning internal agents, workflow automation, or AI-assisted operations that need to work reliably with real business data.

The real problem

Agent demos often work because the setting is forgiving. Production agents fail when nobody has decided what the agent is responsible for, what it may access, what it must escalate, and how a person reviews its decisions.

What we do

Before prompting the agent, we define its job, how success will be measured, which tools it may use, what it is allowed to access, where its data boundary sits, how it can fail, when it must hand off to a person, and how its work is reviewed. That gives the prompt a clear role inside a designed system.

How it holds together
  • 01

    Job definition

    One clearly defined responsibility, measurable success criteria, and written rules for what the agent should not do.

  • 02

    Tool + permission model

    Tool access is limited to what can be justified and tracked. Agents do not receive credentials or permissions they do not need.

  • 03

    Data boundary

    What the agent may read, write, and send to providers — and what stays outside that boundary.

  • 04

    Review loop

    Human review checkpoints, escalation paths, and a clear way for the agent to say “I don’t know.”

Agent architecture

Job → tools → permissions → data boundary → review loop.

  1. 01

    Job

    responsibility · success criteria

  2. 02

    Tools

    scoped APIs · functions · actions

  3. 03

    Permissions

    least privilege · audit

  4. 04

    Data boundary

    read · write · provider out

  5. 05

    Failure modes

    escalation · safe default

  6. 06

    Review loop

    human checkpoints · feedback

What you get
  • 01Agent job and success-criteria definition
  • 02Tool, permission, and data-boundary model
  • 03Failure mode and escalation design
  • 04Review loop and monitoring recommendations
Parent services

Service areas that use this technical foundation

Related reading

Background on this topic

Next step

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