An AI ecosystem for fundraising letters
Some Bibel TV fundraising letters raised noticeably more than others, and nobody had a record of why. I built the analysis that found the pattern, the Claude Project that turns it into a draft, the web prototype that puts someone in control of that draft, and the Claude skill that carries the same voice into in-app notifications, web banners, and video scripts. All of it done solo, at the layer where prompt design meets product design.
The problem
Some Bibel TV fundraising letters raised noticeably more than others, and nobody could say exactly why beyond a guess about the season. Every campaign still needed a letter that read warm, specific and unmistakably Bibel TV — drafted from scratch, several times a year.
The follow-up content built to carry the same message into the app, the web and video scripts had two options: get copy-pasted, and lose the specificity that made the original work, or get written from a blank page again, and lose the time. The blank page kept eating the calendar.
What I built
### 1. A performance analysis of the source material
Read the reasoning behind this decision
I went back through the fundraising letters and their results, identifying what separates the over-performers from the under-performers. Seasonality was one axis. Style, sentence length, warmth, how directly the ask was framed, and how much specific reference to Bibel TV programming was woven in — that was the other. That analysis is the ground truth the whole ecosystem sits on.
2. A Claude Project that guides the generation with follow-up questions
The analysis, together with the style guide, is encoded into a Claude Project. Crucially, the Project doesn't just take a prompt and produce a letter. It asks follow-up questions before generating, clarifying the campaign occasion, the audience segment, the specific programme or milestone the letter should reference. The interaction is a multi-turn clarification loop with a human, not a single-shot completion.
3. A web prototype for the generation flow
The flow isn't chat-only. I built a web prototype that gives the generation a proper surface: inputs for the context Claude needs, a side-by-side view of the working draft, iteration in place. Prompt engineering shows up in the model's behaviour; the prototype shows up in the human's ability to drive it.
4. A Claude skill for multi-surface follow-up content
The fundraising letter is only the first surface. The same message has to land as an in-app notification when a viewer opens the Bibel TV app, as a banner on the web, and as a video script for the on-air fundraising spots. I built a Claude skill that takes the letter's tone and message as its ground state and produces follow-up content across all three surfaces. One voice, three surfaces, one source of truth.
Want to hear more?
- Curious why the fundraising AI won't generate until it knows what campaign and what programme this is for — and how one letter becomes an in-app notification, a web banner, and a video script without anyone rewriting it?