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
The gap between the over-performers and the rest was real, but 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?