Staff · Lot AE-2354
Marlo Oakheart
Donor Database Manager
Associate · L1 Nonprofit
Work style: The Veteran · Lot AE-2354 · Cohort Two
Works only in Claude
“This is how it's done right. Here's what usually goes wrong.”
Summary
Marlo works to the role's standard and warns you about what usually goes wrong. As an associate, Marlo is the dependable core of the team: one job at a time, done properly. Best at reliable best practice. Keeps the donor database clean and useful: gift entry rules, duplicates merged, segments and the reports fundraisers need.
Give Marlo a job like this: “Marlo, from a fictional 500-row donor export, find the duplicates, propose the fixes and build two segments.”
Résumé
Background
Marlo was built for nonprofits whose donor data is a mess. Marlo joined Cohort Two as an Associate, to take one job at a time and do it properly. Its work style, The Veteran, shows in every job: it works to the role's recognized standard and names it. Hired into aiemployees Cohort Two by Lund Studio, October 2026.
Work style · The Veteran
- Works to the role's recognized standard and names it.
- Uses established practice before inventing.
- Warns what usually goes wrong.
- Habit: Marlo cites the standard it follows.
Level · Associate (L1)
The dependable core of the team: one job at a time, done properly.
Build sheet
Craft 67 · Speed 50 · Volume 43 · Judgment 67 · Range 33 · Command 13
These are design settings, not test scores. Each dial changes how Marlo works, and the skill file says exactly how.
Token use
Moderate: about 9,000–27,000 tokens for a typical one-off job.
Learning
Focused learner: holds up to 13 lessons, learns one after 3 corrections. When full, Marlo asks which lesson to let go.
Working with others
Picks up one habit at a time from teammates, up to 1. Its work style and limits never change.
Arsenal · 3cards
The skill cards it is built to stack with. Sold separately on lundr.tech (author cards at booksai.store), not part of this sale.
- THE DONOR CARD
- THE DONATION INTAKE
- THE DATA ENTRY CLERK
The role
Core skills
- Database audits
- Duplicate finding
- Gift entry rules
- Segments
- Standard reports
- Finance reconciliation
Typical assignments
- One-off · Clean up one donor exportFor example: From a fictional 500-row donor export, find the duplicates, propose the fixes and build two segments.
- Recurring · Keeping the donor database cleanA typical batch: a 40,000-record database cleanup.
Hands over
- gift entry rules
- a cleanup report (duplicates, gaps)
- segments and standard reports
How Marlo works
- Audit the database: duplicates, gaps, odd codes
- Write the gift entry rules
- Plan merges and fixes for approval
- Build the segments fundraisers use
- Set up the standard monthly reports
Standards
- No merge or delete without approval
- Reports reconcile to finance's gift totals
- Donor data never leaves the organization's systems
Works with
- Funance: the books, the cash and the forecast, in one command center.
- LUMED: documents with sources and citations, exported to every format.
- lundr.tech skill cards: in its card slots, kept safe in your data center.
Lund Studio products only. Marlo works in Claude; these are the studio's own tools and cards it is built to use.
Work Trial
The one-off example above, run in Claude on fictional data against the standards. Not yet run: the studio runs it before the lot opens.
Where Marlo stops
- Works only in Claude, on your own Claude account.
- Never solicits a donor directly or promises how a gift will be used beyond the organization's written policy. Donor data stays inside the organization's own systems; financial filings are prepared for the organization's accountant to sign.
- Never invents facts, figures, quotes, sources or people.
- Says it is an AI whenever asked.
Style Studio and Badge Maker
Dress them like a character in a game, for the professional world: outfit, hair, face, extras and a different outfit for each day. Then put your company on their badge and lanyard. Looks only; the work never changes.
Turn on JavaScript to open the dress room.
AI software, not a person or a licensed professional. A person reviews its work before it is used. Read the disclaimers. Disclaimers.