Compares fixed fee, time and materials, retainer, value-based and fixed-term handover for this piece of work, showing what each rewards and risks and where AI speed changes the math, so you choose how to charge and can say why; never a price recommendation. Use for "run disc-fee-structure", "how should I charge for this", "fixed fee or day rate", "why pay for hours if AI is faster", "should I move to value pricing", "retainer or project fee", "compare fee models", part of the Claude for Winni...
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---
name: disc-fee-structure
description: Compares fixed fee, time and materials, retainer, value-based and fixed-term handover for this piece of work, showing what each rewards and risks and where AI speed changes the math, so you choose how to charge and can say why; never a price recommendation. Use for "run disc-fee-structure", "how should I charge for this", "fixed fee or day rate", "why pay for hours if AI is faster", "should I move to value pricing", "retainer or project fee", "compare fee models", part of the Claude for Winning Proposals Pack by Polar Bear.
---
# Fee Structure Choice
## When To Use
The client asks why they should pay for hours when AI makes the work faster, and you have no clean answer. Use this before the proposal to pick the charging model that fits this work, and to explain it in terms of what the client buys rather than the time you spend.
## When Not To Use
If you still need to shape what you are offering, start with Good-Better-Best Options. If a fee is already on the table and the client is pushing it down, Negotiation Plan fits better; this skill never sets or lowers a number.
## Inputs
- The options or scope you are pricing, with deliverables and rough phases
- Your own rates, past fees and how you charge today
- Any value figures the client gave you (what the problem costs them, what success is worth), with who said them
If you have none of this, I start from a one-line description of the work and mark the comparison as a first draft.
## Approach
Comparing fee models is a practitioner convention; the writing principle comes from the US federal acquisition rule FAR 37.602, which asks that work be described by required results and measurable standards, not hours. That is also the honest answer to the AI question: if AI makes your work faster, a fee tied to hours shrinks while the value to the client does not. The failure this prevents is switching to "value pricing" with no figures from the client, which is guesswork with a nicer name. Works in any plain chat.
## Workflow
1. Ask at most three questions: what exactly does the client get at the end; how much of this work does AI already speed up for you; and has the client told you, in their own figures, what the problem costs or what solving it is worth?
2. Write what the client buys as results with a measurable standard, following FAR 37.602: "a pricing model the finance lead signs off" rather than "ten days of analysis". Every model below is judged against this line.
3. Compare the five models on four counts: what the client pays for, what it rewards (speed, outcome, availability), who carries the risk if it overruns, and what AI speed does to it. Time and materials falls as you get faster; a fixed fee lets you keep the gain and carry the overrun; a retainer pays for availability, which AI does not shrink; value-based ties to their result; fixed-term handover pays for building their capacity, including their own AI use.
4. Test value-based honestly. If the client has given you their own value figures, show the link. If not, mark it "not possible yet: ask for [figure]" and add the question to your next conversation. I never estimate what the work is worth to them.
5. Note the risks each model puts on you for this client: scope creep under fixed fee, a capped relationship under T&M, unclear output under retainer. Name the protection each needs (assumptions, change control, a review point).
6. You pick the model, or a mix by phase, and write the reason in two sentences the client could read. I state trade-offs; every rate, fee and price stays yours.
7. Flag tax, contract and payment-term points for later; check with a qualified adviser.
## Output Format
```markdown
# Fee Structure Comparison
What the client buys (results and standards): [one line]
| Model | Client pays for | Rewards | Risk of overrun sits with | What AI speed does to it | Fit for this work |
|---|---|---|---|---|---|
| Fixed fee | [ ] | [ ] | [ ] | [ ] | [fits, partly, does not] |
| Time and materials | [ ] | [ ] | [ ] | [ ] | [ ] |
| Retainer | [ ] | [ ] | [ ] | [ ] | [ ] |
| Value-based | [ ] | [ ] | [ ] | [ ] | [possible, or "not possible yet: ask for [figure]"] |
| Fixed-term handover | [ ] | [ ] | [ ] | [ ] | [ ] |
## Protections needed
| Model chosen | Risk | Protection |
|---|---|---|
| [model] | [risk] | [assumption, change control, review point] |
## The answer to "why pay for hours?"
[Two or three sentences in your voice, from the line on what the client buys]
## Decision
[Your name] chooses the model and sets every figure by [date]; tax, contract and payment terms: check with a qualified adviser.
```
## Done When
- What the client buys is written as results with a measurable standard.
- All five models are compared on the same four counts.
- Value-based shows the client's own figures or is marked "not possible yet".
- The chosen model has its reason and its protections written down.
## Quality Bar
- The comparison talks about what the client gets, never about how busy you are.
- AI speed is named plainly, for and against you; the answer never hides your own use of AI.
- No market rates, benchmarks or "typical" fees appear anywhere.
- A mix by phase is allowed when the work changes shape, as long as each phase has its reason.
- Legal, tax and payment points carry "check with a qualified adviser".
- No price recommendation; you set every number.
## Next
Run disc-moscow-scope (MoSCoW Scope) to fix what the fee covers.
## About the makers
This pack is made by Polar Bear, a consultancy built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).