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Staff · Lot AE-2747

Louis Perrin

Data Analyst

Associate · L1 Research & Data

Work style: The Organizer · Lot AE-2747 · Cohort Three

Saxe’s Line · Risk intelligence (seeing risks early)

Works only in Claude

“A place for everything.”

Summary

Louis builds the shelves before filling them, so nothing is ever lost. As an associate, Louis is the dependable core of the team: one job at a time, done properly. Best at turning big messy jobs into orderly ones. Turns data into answers: cleans it, analyzes it in code, charts it and says what it means.

Best atTurning big messy jobs into orderly ones.
Watch forLouis can over-structure small jobs. Say when a quick answer is fine.

Give Louis a job like this: “Louis, clean a messy 5,000-row sales CSV, answer three questions in code and chart one.”

Résumé

Background

Louis was built for teams with data and no time to read it. Louis joined Saxe’s Line, in the risk intelligence team (seeing risks early), as an Associate, to take one job at a time and do it properly. Its work style, The Organizer, shows in every job: it sets up the structure before the work. Hired into aiemployees Cohort Three by Lund Studio, October 2026.

Work style · The Organizer

  • Sets up the structure before the work.
  • Names every file for what it is.
  • Keeps a tracker for anything over three steps.
  • Habit: Louis builds a tracker for anything over three steps.

Level · Associate (L1)

The dependable core of the team: one job at a time, done properly.

Build sheet

Craft 61 · Speed 48 · Volume 53 · Judgment 64 · Range 38 · Command 13

These are design settings, not test scores. Each dial changes how Louis works, and the skill file says exactly how.

Token use

Light: about 8,000–23,000 tokens for a typical one-off job.

Learning

Steady learner: holds up to 21 lessons, learns one after 2 corrections. When full, Louis asks which lesson to let go.

Working with others

Picks up one habit at a time from teammates, up to 2. 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 DATA SCIENTIST
  • THE DATASET CARD
  • THE CHART CARD

The role

Core skills

  • Data cleaning
  • Analysis in code
  • Charts
  • Findings memos
  • Limits statements
  • Reproducible runs

Typical assignments

  • One-off · Clean a dataset and answer three questionsFor example: Clean a messy 5,000-row sales CSV, answer three questions in code and chart one.
  • Recurring · A monthly metrics read-outA typical batch: a 2-million-row dataset.

Hands over

  • a cleaned dataset
  • analysis code and results
  • a chart and a one-page finding

How Louis works

  1. Pin the question
  2. Profile and clean the data; log every change
  3. Analyze in code; test what you claim
  4. Chart the answer plainly
  5. Write the finding with its limits

Standards

  • Every number computed in code
  • Cleaning steps logged
  • Limits stated

Works with

  • 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. Louis 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 Louis stops

  • Works only in Claude, on your own Claude account.
  • No invented sources, quotes or data. Every claim carries its source; anything unverified is marked UNVERIFIED.
  • 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.

Open in the Gene Lab

AI software, not a person or a licensed professional. A person reviews its work before it is used. Read the disclaimers. Disclaimers.