Explains how your engagement models differ, and which one a described project actually suits — including when the model the buyer wants is the wrong one.
An AI agent for engagement models handles the contracting question that shapes every consulting relationship: fixed price, time and materials, capped, or outcome-based. It explains how each works in practice, what each requires from the client, where the risk sits in each, and which one a described project actually suits. Buyers arrive with a strong preference, usually for fixed price, formed by procurement rather than by the shape of the work. Where scope is genuinely undefined, that preference produces either a padded price, a change-request relationship both sides resent, or a delivery failure — and the moment to say so is before a proposal, not during month three.
Explains the trade-off buyers are making without knowing it.
Explains how each of your engagement models works in practice
Sets out what each model requires from the client side
Explains where delivery risk sits under each arrangement
Identifies which model a described project actually suits
Flags where the requested model fits the work badly
Captures the scope clarity that determines the answer
A fixed price on undefined scope is not a commercial preference, it is a structural problem: the consultancy prices the risk, the buyer pays for uncertainty they could have removed, and every subsequent conversation is about whether something was in scope. Time and materials on well-defined work has the opposite failure, leaving a buyer feeling exposed to a meter they cannot read. Both are avoidable, and neither is usually discussed until a proposal exists — by which point the model has been assumed rather than chosen. Raising it early is also a competence signal. A firm that explains where risk sits under each arrangement sounds like one that has delivered enough projects to know.
A three-step flow from a model preference to a suitable arrangement.
The agent sets out how each model works in practice, including what it asks of the client, rather than as a list of contract types.
It establishes how well defined the work is, because that — not preference — is what determines which model can succeed.
Where the requested model fits the described work badly, it says so plainly and routes the conversation to somebody who can discuss alternatives.
A buyer insisting on a fixed price for undefined scope.
Scenario: a consultancy was quoting whatever model buyers asked for and carrying two projects that had become change-request negotiations. A prospect describes a platform migration in general terms and asks for a fixed price. The agent explains the three models the firm offers, what each requires, and where risk sits in each. It then asks the questions that establish scope clarity: whether the current estate is documented, whether the target state is decided, whether integrations are enumerated. Two of the three answers are no. Rather than accepting the fixed-price framing, it says plainly that fixed pricing on undefined scope usually means either a padded figure or a change-request relationship, and that a common route is a short paid discovery producing a fixed price for the delivery. That is a proposal a person then has. The alternative — quoting a fixed price for work nobody has scoped — was the path to the firm's two current problem projects.
Anybody whose margin depends on how an engagement is structured.
The model decides whether a project is profitable or a dispute.
Procurement asks for fixed price by default, regardless of scope.
You inherit whatever commercial shape sales agreed.
Model choice is assumed before you start writing.
Advisory and implementation work suit different arrangements.
Discovery only sells if somebody explains why it exists.
Explains the models, tests scope clarity, flags the mismatch.
Holds your engagement models and the scope criteria for each.
Records the indicated model and the scope assessment.
Sends the written explanation buyers circulate to procurement.
Flags mismatches to the practice lead before a proposal is drafted.
Books the commercial conversation about structure.
Stores the internal guidance on when each model applies.
The commercial questions decided before anybody discusses them.
Questions about structuring an engagement before quoting it.
An AI agent for engagement models explains how fixed price, time and materials, capped and outcome-based arrangements work, what each requires from the client, where risk sits, and which one a described project actually suits.
Constructively, and early. A firm that quietly accepts fixed pricing on undefined scope is choosing a difficult project over an awkward conversation, and the awkward conversation is far cheaper in every case.
The commercial negotiation is. Explaining how the models differ and what scope clarity each requires is education, and doing it before a call means the negotiation starts from a shared understanding rather than from a procurement template.
By asking whether the current state is documented, the target state decided and the integrations enumerated. Those three questions predict model suitability better than any general discussion of requirements.
It can explain that the route exists and why it is used, which is the part buyers find hard to accept when it appears in a proposal without context. Whether to propose it in a given case is a commercial judgment.
That is a decision for a person, and sometimes the right answer is to decline. Knowing before a proposal is written that the model is fixed and the scope is not is exactly the information that makes declining a considered choice rather than a late retreat.
Retainers have the same problem in reverse — buyers want them for defined project work, where they are usually poor value. The same test applies: how well defined is the work, and where should the risk sit.
Explains how your engagement models differ, and which one a described project actually suits — including when the model the buyer wants is the wrong one.