Before you go —
take this with you.
1. The Credibility Ladder: a five-rung framework that tells you exactly what your track record can credibly support, and how that should change the way you write your proposal.
2. And a full AI prompt you can paste into ChatGPT or Claude right now: designed to assess your exact position on the ladder for the specific call you're applying to, before you write a single word.
Built for FOR RESEARCHERS, development consultants, project officers, AND NGO professionals
Your work deserves funding.
And AI has already changed the game
(for those Who know how to use it)
A PRACTICAL system to use AI to write faster, better-aligned, and more credible funding proposals
Instant Access
6 pillars with video explanations
Ready to apply in your next proposal
Instant Access
6 modules
Evidence-only drafting
You Control Every sentence
You Control Every sentence
YOUR INSTRUCTOR
FORMER ERC AND UK ESRC PROPOSAL EVALUATOR · RESEARCH FUNDING SPECIALIST
Paulius Yamin
Former Managing Director, UPenn Center for Social Norms. Former Scientific Director, Paris Institute for Advanced Study. Policy Fellow, Harvard Kennedy School of Government. Proposal reviewer for the ERC and the UK ESRC. Consultant for USAID, The World Bank, The OECD, and U.N. Agencies for 15+ years.
Built for researchers applying to:
- Horizon Europe
- ERC grants
- UK ESRC
- Marie Skłodowska-Curie Actions
- National Research Councils
- Major international foundations
- Internal University funding
- International Fellowships
One-time payment · Lifetime instant access
WHY I BUILT THIS SYSTEM
AI has already changed the game for grant writers and consultants. Funding cycles are accelerating, proposals can be written with speed no one thought possible a few years ago, and competition is intensifying drastically. The number of proposals submitted to each call has multiplied.
And yet many researchers and practitioners have hit the same wall: generic outputs, hallucinated statistics, texts that could belong to any organization. Others have refused on principle. Behind both reactions is a legitimate professional concern: can I use AI without creating a compliance, credibility, or quality problem?
This system is built to answer that question directly.
When used correctly, AI can drastically improve both the speed and quality of funding proposals. But it needs a clear structure: one that leverages its strengths, guards against its weaknesses, and keeps human control at the key moments of the writing process.
AI-assisted writing does not just reduce drafting time from days to hours. It enables the writer to draw on a far broader base of evidence, ensures every section is explicitly aligned to what the funder is scoring, and surfaces data and precedents that would otherwise take days to gather.
This system gives you a clear, structured framework: the main elements grant writers need to manage when working with AI, and the right order to apply them.
Course participants work with a real proposal and build a replicable system, not just theory.
The only question is whether you're ready to transform forever the way you write funding proposals.
You don't need a better AI model. You need a better process.
AI can absolutely improve the speed and quality of your funding proposals.
But you need a system that leverages its strengths and minimizes its weaknesses.
This is what the Funding Proposal Secrets system gives you.
And you can get it right now for $37 (introductory price - will increase soon).
What the System Actually Produces
BEFORE
Generic AI output (no system):
Our research addresses significant gaps in current understanding through innovative methodological approaches that contribute to the excellence of European research.
(No call alignment. No evaluator differentiation. No evidence. An experienced reviewer recognises this output in the first sentence. Unfundable.)
AFTER
System-guided draft (your Request for Proposals + your evidence + structured prompts):
In direct response to the MSCA call's priority on cross-disciplinary methods, this project builds on the applicant's published work on [specific method] (see Publications, Attachment B), which demonstrated [specific outcome] across [X] institutions. All capability claims in this proposal correspond to documented outputs listed in the CV."
(Call-aligned. Source-anchored. Defensible to any evaluation panel. Yours — not AI's.)
How AI works in this system
At every pillar, the boundary is the same:
- What AI does: organize, structure, match funder priorities with your project, conduct deep searches, act as sounding board, and draft.
- What AI does NOT do: generate statistics, invent credentials, infer what you haven't supplied, or fill gaps in your evidence.
- Your role: validate and review information, make strategic decisions, reflect on the substance, craft the final versions of texts.
The goal is a proposal you can comfortably defend to reviewers and funders.
PILLAR 1
Know Exactly What You're Competing For
Most researchers start drafting before they have fully understood how their project maps out to the funder priorities and the evaluation criteria.
AI is great to map how your project and ideas map out to the priority areas, eligibility requirements, and scoring weight of the call you're targeting. Pillar 1 teaches how to feed the right information to AI so that you can do that work in 5 minutes instead of several hours.
"The number one mistake I see candidates doing is submitting recycled proposals that don't clearly map to funder's priorities and evaluation criteria"
The key concept: Funder's priorities and evaluation criteria should be one of the main structuring factors of your proposal. Do this well, and you will land in the shortlist of most calls.
PILLAR 2
Gather Your Winning Information Fast
Garbage in, garbage out.
The Input Snapshot is a structured evidence-gathering tool. Your call requirements, published outputs, team credentials, partner confirmations, and verified outcomes are assembled in one place — and become the only material AI is allowed to use. AI drafts from your facts. Not from its training data. Not from inference. Only from what you supply.
"AI doesn't produce generic output because it's a bad tool. It produces generic output because it received generic inputs."
What this addresses in evaluation: credibility of the arrangements. Every capability claim, every partnership, every outcome figure traces to a source you provided. Nothing is invented. An evaluator can follow the evidence trail from every sentence back to documented reality.
PILLAR 3
Build Your Response Structure in 20 Minutes
Stop writing. Start organizing. The draft follows.
Pillar 3 maps your inputs to the structural skeleton of the proposal: section by section, aligned to the call's required format. Every structural decision is yours to approve, adjust, or reorder before drafting begins. No sentence is written until the architecture is confirmed.
"You are not a better writer when you know more words. You are a better writer when you know what goes where."
What this addresses in evaluation: maturity. A proposal with a coherent, internally consistent structure reads as the work of a researcher who has thought through the project: not one who drafted section by section and hoped it held together.
PILLAR 4
Draft Fast Without Losing Your Voice And Evidence
You are the author. AI is the pen. Keep it that way.
AI converts your structure and your inputs into flowing prose section by section. You read every sentence. If a sentence cannot be traced back to something you provided, it does not go in. The voice is yours because the content is yours. AI contributes the speed. You contribute the judgment that makes it defensible.
"AI makes you faster. Your judgment makes it good. You need both. Never settle for just one."
What this addresses in evaluation: ethics. A proposal drafted this way is one you can stand behind in full — because every claim is yours, every figure is documented, and the AI was a writing tool, not an author.
PILLAR 5
Verify Before You Submit (5-Minute Check)
Five Minutes That Protect Everything
AI drafts fast, and it can also fabricate quietly. Pillar 5 is a field-tested review that catches the six specific failure patterns that are most likely to disqualify a competitive research proposal: invented statistics, generic capability claims, overstated novelty, confidential data leakage, vague funder alignment, and hallucinated citations. Five minutes per section. Run before you submit.
Your Pre-Submit Checklist:
- Every statistic traces to a named, verifiable source
- No credential appears that wasn't in your input materials
- All RFP eligibility requirements are explicitly addressed
- Partner organizations have confirmed their participation in writing
- No outcome claim exceeds what your evidence actually shows
- Budget figures come from your calculations, not AI estimates
- Every [REVIEW] flag from the draft sprint has been resolved
"The question is not whether you can use AI ethically. It is whether you have a process that makes ethical use systematic, not a matter of memory or good intentions under deadline pressure."
PILLAR 6
Turn Your Process Into a Team Repeatable System
One draft is a win. A system is a transformation.
The method from Pillars 1–5 is documented into a repeatable workflow, one that works faster with each proposal, and that a collaborator or research team member can follow without your supervision. First proposal through the system: several hours. Second: close to 60 minutes. By the third, the structure is internalised.
"A workflow that exists only in your head is fragile. One that is documented, tested, and updated becomes an asset — for you, your team, and every future deadline."
Here's What Our Students Are Saying
From a postdoctoral researcher applying to Horizon Europe Marie Skłodowska-Curie Actions:
"I had two weeks to submit my MSCA Postdoctoral Fellowship and four AI drafts that all said roughly the same thing in different fonts. None of them mapped to the evaluation criteria, they just sounded like proposals. I ran the Credibility Ladder assessment before touching the fifth draft. It told me I was pitching Rung 1 language on Rung 3 evidence. I rewrote the excellence section around what I had actually done. The panel feedback noted the coherence between my track record and the proposed methodology as a scoring strength."
From an independent development consultant writing to the World Bank:
"I've been writing World Bank concept notes for eleven years. I thought I knew what I was doing. What I didn't realise was that I'd been writing to impress reviewers rather than map to the evaluation rubric, and those are not the same thing. The rubric mapping prompt took me eight minutes. It showed me I was spending 40% of my word count on a criterion worth 10% of the score. I rebalanced. The concept note passed to full proposal stage for the first time in three attempts on that mechanism."
From a research coordinator managing an ERC Starting Grant application:
"Our PI had strong preliminary data but no funded ERC track record. Every draft we produced with AI came out sounding either overconfident or defensive, we couldn't find the right register. The Credibility Ladder placed us clearly at Rung 2 and gave us specific language for framing adjacent work as genuine evidence of readiness. The evaluator comments described our capacity section as 'realistic and well-substantiated.' That's exactly the problem we'd been trying to solve for six weeks."
ABOUT PAULIUS YAMIN
The system was built by someone who has reviewed proposals from the other side of the table
Paulius Yamin
I have spent 15 years writing, reviewing, and advising on competitive funding proposals: including as a reviewer for the European Research Council and the UK Economic and Social Research Council.
I have watched excellent researchers lose funding not because their science was weak, but because their proposal could not demonstrate coherence, credibility, and evaluator alignment under the conditions of a competitive call.
After raising more than $18M in competitive grants and reviewing more than 500 proposals, I built this system to make the process teachable, and to make ethical AI use in proposal drafting a disciplined practice rather than a risk.
Former Managing Director,
UPenn Center for social norms
Former scientific director,
paris institute for advanced study
Policy fellow,
harvard kennedy school of government
Proposal Reviewer, ERC and UK ESRC
Consultant for USAID, the world bank, the OECD, and u.n. agencies for 15+ years
What you get on purchase — immediately, with lifetime access
- The 6-Pillar System (6 modules built around the evaluation dimensions that determine funding decisions at the ERC, Horizon Europe, MSCA, ESRC, USAID, and equivalent competitive calls) — Value: $344
- The Input Snapshot Template (5-minute evidence-gathering tool that becomes the only material AI is permitted to use) — Value: $47
- The Human/AI Boundary Guide for Each Pillar (exactly what AI does and does not do at every step, and why each boundary matters for evaluation integrity) — Value: $47
- The Pre-Submit Hallucination Checklist (the 7-point check that catches the specific failure patterns most likely to affect a competitive research proposal at the moment of review) — Value: $37
- The Repeatable Workflow Standard Operating Procedure (Pillar 6 documentation so the process works at the same standard every time, and can be followed by any member of a research team without your supervision) — Value: $47
Total Value: $522
Your Founding Student Price: $37
Special price while course videos are being produced. Then price will go up.
One-time · Lifetime
My Personal Guarantee
Use the system on your next proposals. If after putting the system in place you do not have a complete, source-grounded, funder-aligned draft ready to review within 60 minutes of focused drafting time, email me directly.
You get every cent back. No forms. No explanation required.
I am putting my name on this because I use it myself and I have watched it work across more than 500 proposals and $18M in secured competitive funding — across ERC, Horizon Europe, MSCA, USAID, World Bank, and national research council calls. The methodology is the same whether you are applying as a postdoctoral researcher, a principal investigator, or an independent development consultant.
If it does not work for you, you do not pay for it. That is the only condition.
Paulius Yamin
You have the research. You have the track record. You have the deadline.
The only thing between you and a defensible first draft is a process that does not yet exist in your workflow.
This is that process. Structured. Evidence-anchored. Ethical by design, not by intention.
6 Modules · Input Snapshot · Ethical Review Checklist · Human/AI Boundary Guides · Lifetime Access · Full Refund Guarantee
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