Self-Review — Catching What AI Misses

You’ve written the proposal — or more accurately, you and AI have written it together. Now comes the step that separates good proposals from great ones: review. Not proofreading. Review.

Why Self-Review Matters More With AI

When you write every word yourself, you’ve already processed the content deeply. You know what you meant, what data you used, and where you had doubts. When AI generates a draft, you haven’t processed it that way. The text looks polished and reads smoothly, which can mask problems that a manually written first draft would make obvious.

AI-assisted proposals need more review, not less. The polish is the problem — it makes everything look finished when it might not be accurate, specific, or persuasive enough.

AI-assisted proposals can hide:

Statistics that are plausible but wrong
Claims that are technically true but misleading
Language that’s generic rather than specific to your organization
Inconsistencies between sections that were drafted separately
A tone that doesn’t match the funder’s culture

The Three-Pass Review

Don’t try to catch everything in one read. Use three focused passes:

Pass 1: Accuracy

Pass 2: Completeness

Pass 3: Persuasion

What to Look For

The funder's language

Narrative flow

The 'so what' test

Tone consistency

Getting Fresh Eyes

If possible, have someone who hasn’t been involved in the writing read the complete proposal. They’ll catch things you can’t see:

Jargon you’ve internalized but a reviewer might not know
Assumptions that seem obvious to you but aren’t explained
Structural issues that are invisible when you know the content too well

Pro tip

Even 30 minutes from a colleague — or your ED, a board member, a peer at another organization — is valuable. Give them the scoring criteria and ask: “Based on these criteria, would you fund this?”

Purpose-built AI grant tools can run a structured first-pass review before you begin your own. This doesn’t replace the three-pass process — it accelerates it by catching mechanical issues early so your human review can focus on judgment calls.

In Grantable

In Grantable: Grantable can check your proposal against the RFP requirements, flag inconsistencies between your narrative and budget, and verify that scoring criteria are addressed in the text. It runs this review against the funder’s actual guidelines, not generic rules. You still do the three passes — but you start with a cleaner draft.

Check your understanding

You've just finished an AI-assisted draft of a federal proposal. Your first review pass should focus on:

Key Takeaways

AI-assisted proposals need more review, not less — the polish can hide problems
Use three passes: accuracy (are the facts right?), completeness (is everything addressed?), and persuasion (does it convince?)
Check that you're using the funder's language and that the narrative flows logically
Fresh eyes catch what you can't — even a brief review from someone outside the process helps

Next Lesson

Beyond general review, there’s a specific technique for verifying AI-generated content against your source data and funder criteria. It’s called the Spot-Check Technique, and it’s worth learning.