The LOI that used to eat your whole evening can be a real first draft before the coffee's cold.
Faster LOIs, proposal narratives, and budget language -- with funder facts, outcome figures, and multi-client confidentiality staying exactly where they belong: with you.
Secure checkout via Stripe — Apple Pay & Google Pay supported
One-time payment · Instant access · Yours to keep
This guide is for you if...
✓You write grant proposals -- freelance for multiple nonprofit clients, or in-house for your own organization -- and handle funder research, LOIs, and proposal narratives yourself
✓You want faster first drafts of LOIs, proposal sections, and budget narratives without losing a single funder fact or outcome figure to an AI guess
✓You work across multiple nonprofit clients and want a concrete, repeatable habit for keeping one client's program and budget details out of another client's draft
✓You want a clear line between what AI can draft for you and what always stays a verified fact, a confirmed commitment, or your own compliance judgment
What you'll learn
7 sections · 28 topics
1.1The 5 places AI can help a grant writer draft faster (and 2 where it doesn't belong)Free preview
1.2The facts-and-figures line: no invented funder facts, no invented outcomes, no credential claims
2.2Turning your funder research into a usable summary
2.3The LOI first draft, built from your case-statement boilerplate
2.4Action: Build your prospect research and LOI templates
3.1What AI can help with in proposal writing (and the hard line it can't cross)
3.2The problem/needs statement, built from your own program data
3.3The program/outcomes narrative, mapped to the funder's actual priorities
3.4Action: Build your proposal-section templates
4.1Why a budget narrative needs a story, not just numbers
4.2The budget narrative draft
4.3Bios, letters of support, and organizational-capacity statements
4.4Action: Build your budget-narrative and attachment templates
5.1The client review ask: timed to a real milestone
5.2Marketing your track record without overclaiming
5.3The referral ask
5.4Action: Draft your review, track-record, and referral templates
6.1The funder progress or final report draft
6.2Client onboarding, scope, and fee communications for a freelance practice
6.3Scheduling across multiple clients and deadlines
6.4Action: Build your reporting and back-office templates
7.1What never goes into a free AI tool: client and funder data
7.2The facts-and-figures line: what AI cannot do
7.3An illustrative weekly AI routine — adjusted to the work actually required
7.4Action: Fill in your "My AI Ground Rules" one-pager
What's in this guide
A funder-research and LOI workflow built around your own verified priorities, eligibility, and deadlines -- AI never invents or estimates a funder fact
A proposal and budget-narrative system where every outcome, people-served count, and dollar figure stays a literal placeholder you insert yourself, never an AI guess
A multi-client confidentiality standard for freelance writers -- separate AI conversations per client, with no program, budget, or beneficiary detail ever crossing between them
A track-record marketing framework built on the FTC standard -- records-supported typical/exceptional disclosure and confirmed client permission before any result goes into your own marketing
Common questions
AI is genuinely useful for the writing that repeats across every proposal cycle -- organizing funder research, drafting an LOI or proposal narrative from your own verified facts, budget-narrative language, and marketing or client-onboarding messages. It is never useful, and this course never uses it, for the facts and judgments that carry real weight: what a funder actually said, what your organization has actually accomplished or can actually commit to, and whether a client engagement is safe to reference publicly. Those stay yours.
No. This is the line the course never crosses. AI never states, implies, or estimates a specific funder's priorities, eligibility rules, deadline, or award range, and it never invents, estimates, or rounds an organizational outcome, people-served count, or budget figure. Every funder fact and every organizational figure routes through your own current, verified research and comes back out as a literal placeholder you fill in yourself, outside the AI tool.
Every prompt in this course is built to take only public, client-approved, or safely generalized information -- never unpublished program strategy, proprietary budget detail, beneficiary information, or material from a different client, even anonymized. If you're freelance, the course builds a standing habit of a separate AI conversation per client, so one engagement's details never surface while you're drafting for another.
No. This course teaches a drafting workflow, not legal, tax, or grants-compliance advice, and it does not guarantee any funding outcome. Whether a specific claim is compliant, whether your organization's tax status or credentials are current, and whether a marketing use is properly authorized stay with you and your organization's own attorney, accountant, or compliance officer.
Try it free — The 5 places AI can help a grant writer draft faster (and 2 where it doesn't belong)
Know exactly what AI can do for your grant-writing practice — and what it can't. Grant writing runs on a deadline cycle, not a steady weekly rhythm: an RFP drops, the clock starts, and the same underlying story — who the org is, what the program does, what it has actually accomplished — has to be re-told, genuinely tailored, to a different funder's stated priorities and scoring criteria, again and again. Five places AI can genuinely help:
Prospect research summaries. Turning your own research notes on a funder — pulled from their RFP, website, or a database like Candid or GuideStar — into a clean, organized summary you can act on, instead of a scattered set of tabs and bookmarks.
The Letter of Inquiry (LOI) first draft. Taking your org's existing case-statement boilerplate and the funder's stated priorities and producing a real first draft, not a blank page.
Proposal narrative structuring. Turning your notes on the problem, the program, and your outcomes into a tight, well-organized narrative — built around facts you supply, not facts AI invents.
Budget narrative language. Drafting the connective prose around a budget you've already built, so the numbers tell a story instead of sitting in a table with no context.
Marketing and back-office admin. Client onboarding messages, review and referral asks, scheduling, and the routine communication that piles up between deadlines.
Two places AI does not belong, and this course won't ask it to: