Requirements Definition

Pin down exactly what the agent must do

Vague scope is where AI projects quietly go wrong. We turn a rough idea into a precise definition of what the agent handles, what it must never do, what good output looks like, and how success gets measured. It is the difference between an agent people trust and one they quietly stop using.

Let’s talk See how it works

Define the job

A plain statement of what the agent is responsible for and what stays firmly with a person, so nobody is surprised later.

Talk to us about this

Set the boundaries

The hard limits an agent must respect, the actions that always need a human, and the cases it should refuse rather than guess.

Talk to us about this

Describe good output

Concrete examples of a right answer and a wrong one, so quality is something we can test against rather than argue about.

Talk to us about this

Agree how we measure it

Clear acceptance criteria set before the build, so everyone knows what done and working actually means.

Talk to us about this

What it does

Capabilities

Scope and responsibility definition
Guardrails and hard limits
Input and output specification
Success and quality criteria
Edge case and refusal handling
Data and access requirements
Acceptance criteria up front
Shared, sign off ready spec

Why it holds up

Built on four things we don’t bend on.

Honesty

We tell you what AI can and cannot do, then we ship the part that pays for itself.

Craft

Production systems, not slideware. Built around how you actually work.

Speed

Find the one workflow costing the most, ship it to production, prove the return.

Care

Success is hours given back to people and dollars saved. Never the size of the invoice.

Questions

FAQ

What does requirements definition actually involve?

We define the job the agent is responsible for, set the hard boundaries it must respect, describe what good output looks like with concrete examples, and agree the acceptance criteria up front.

Do I need a precise scope before we start this?

No. A rough idea is enough. The point is turning that rough idea into a precise definition of what the agent handles, what it must never do, and how success gets measured.

How is this different from just briefing the build team?

A brief is usually vague scope, which is where AI projects quietly go wrong. This sets hard limits, refusal cases and concrete right and wrong output examples that can actually be tested against.

What happens after the requirements are agreed?

The build starts from the shared, sign off ready spec, so what ships matches what was pictured and there is a clear line for what counts as done and working.

Get in touch

Talk to us about requirements definition

Tell us what you’re trying to do and we’ll reply with how we’d build it, no obligation.

The build starts from a spec everyone has agreed, so what we ship matches what you pictured and there is a clear line for what counts as working.

Let’s talk