ChatGPT · Workflow · 3 min read · Last verified 17 Sept 2026
Writing a proposal a client actually signs
Feed the model your call notes and ask it to identify the client's actual stated priorities before drafting anything, then write the proposal around those priorities rather than your standard template. Proposals get signed when they clearly answer 'why this, why now, why you' in the client's own language.
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What it is good at
- Good at extracting stated priorities from messy call notes.
- Can draft in your voice quickly once you've fed it a couple of past proposals.
- Helps anticipate objections a client might raise before they raise them.
- Fast at producing pricing options in a clear, comparable structure.
Where it falls short
- It can't judge whether your price is right for the market, that's still your call.
- Without your real past proposals, its draft will sound like a generic template.
- It won't catch a client's unstated politics or history that a human relationship would.
How to use it for creative work
- 01
Feed it the call notes, not a brief you wrote for it
Paste your actual notes or a transcript from the discovery call. Ask the model to list the client's stated priorities and concerns in their own words before drafting anything.
- 02
Anticipate the objection
Ask what objection this specific client is most likely to raise about price, timeline or scope, based on what they said, and where in the proposal it should be pre-empted.
- 03
Draft around their priorities, not your services list
Structure the proposal so the first section addresses their top stated priority directly, rather than opening with a generic list of your services.
- 04
Offer two or three pricing options
Ask for a clear comparison table of two or three scope options rather than one take-it-or-leave-it price, this both increases signed rate and clarifies what's included.
- 05
Cut it by a third
Once drafted, ask the model to cut the proposal by a third without losing anything a client would need to say yes. Long proposals get skimmed, not read.
Ready-to-use prompts
Here are my notes from a discovery call: [paste]. List the client's stated priorities and any concerns they raised, in their own words where possible. Do not draft anything yet.
Based on these priorities and concerns: [paste], what objection is this client most likely to raise about price, timeline or scope? Suggest where in a proposal it should be addressed.
Write a proposal for [service] where the opening section directly addresses this client's top priority: [state it]. Use this past proposal as a voice reference: [paste example]. Include: approach, scope, timeline, three pricing options, next step.
Turn this scope description into a comparison table of three pricing options, essential, recommended, comprehensive, each clearly listing what's included and excluded: [paste scope].
Cut this proposal to two-thirds of its current length without removing anything a client needs to say yes. Return the edit, then list what you cut and why: [paste proposal]
Questions people ask
- Will a client notice it's AI-assisted?
- Not if you feed it your real voice and specifics from the actual call, the tell is generic language and templated structure, both of which this method avoids.
- Should I let it set the price?
- No, it can format pricing options clearly, but market rate and your own economics are judgements only you should make.
- How much of my past proposals should I share?
- Two or three strong examples, with any confidential client-specific numbers or names removed, is usually enough to establish your voice.
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