AI agent intake process

An AI agent intake process is the front-end scoping work that turns a recurring workflow into a role. It happens before prompts, tools, and deployment. The goal is to decide what the agent should own, what it needs to read, what decisions it can make, and where it must escalate.

Good intake starts with the work, not the model. A buyer might say they want an “AI customer service agent.” That is too broad. Intake narrows it: draft replies for order-status tickets in Front, using ShipStation, prior tickets, and the knowledge base, with all sends approved by a human reviewer. Now the role can be built.

RidgeHQ uses the R.I.D.G.E. framework for this step:

• Role: the job the agent owns.
• Inputs: the systems and data it can read.
• Decisions: the calls it can make without asking.
• Guardrails: the places it cannot go.
• Escalations: the conditions that force handoff.

Each letter removes ambiguity. If the role is unclear, the agent becomes a general assistant. If the inputs are unclear, it guesses. If the decisions are unclear, humans do not know whether to trust it. If the guardrails are unclear, edge cases become incidents. If escalations are unclear, work gets stuck.

The intake process should also collect examples. For a drafting agent, that means good replies, bad replies, policy edge cases, tone preferences, and tickets that should have been escalated. Examples are not decorative. They become the first review set and the first few-shot material.

The best intake includes a wrong-fit discussion. Some workflows should stay human. Some need a better knowledge base first. Some require compliance work RidgeHQ has not claimed yet. A strong intake call should be willing to say no or to name a smaller first role.

For managed agents, intake is also where ownership is clarified. The customer owns the business judgment and final approval. The managed-agent operator owns setup, tool connection, review cadence, and iteration. Without that split, the customer accidentally buys another system they have to operate.

A useful intake output is a written R.I.D.G.E. card plus a first-week review plan. The card says what will be built. The review plan says how quality will be measured. Read the full framework at R.I.D.G.E. or start with the broader category at managed AI agent.

The intake is successful when both sides can point to the same boundary. The customer knows what they are delegating. The operator knows what to build. The agent has a role narrow enough to review.