Helping Nonprofits secure funding (without the anxiety attack)

1️⃣ Why I Picked This Project

I’ve spent at least ten years in nonprofit and community spaces so I know firsthand how brutal funding negotiations can be. There are usually idealistic mission-driven folks on one side (been there done that) and ROI-obsessed corporate entities on the other. And when both worlds collide? It’s usually a mix of awkward small talk, vague promises…and we’ll circle back…never.

My thought—what if I could train AI agents to simulate this mess and actually teach future community members to negotiate better? Plus, it sounded fun, and I love building weird AI experiments.

(Also, if you’re into deep dives on LLM alignment and why AI struggles with qualitative reasonsing, check out this paper: here.)

2️⃣ The Problem: Nonprofits Struggle to Secure Funding

Here’s the deal:

❌ Many nonprofits don’t know how to frame their value in corporate language.

❌ Corporations see funding as a business transaction, not just feel-good philanthropy.

❌ Negotiation anxiety is real—people are afraid of saying the wrong thing.

❌ Trust-building is hard when both sides come from wildly different perspectives.

Solution:

🔹 AI-driven negotiation simulations that let nonprofits practice without real-world consequences.

🔹 Agents that self-learn and adapt, simulating corporate vs. nonprofit negotiations realistically.

3️⃣ The Goal: Build AI Agents That Negotiate Like Humans (But Smarter)

Mission: Develop AI agents that can simulate real-world nonprofit-corporate negotiations and improve over time. All names are a work in progress. I AM WIRE-FRAMING HERE. I can’t be everything all at once…

What I Wanted to Achieve:

✅ Nonprofit Baby learns how to reframe mission statements into fundable proposals.

✅ Corporate Baddie adapts based on risk, ROI, and deal structuring.

✅ Agents engage in multi-turn conversations to find realistic compromises.