Beginner

Cover of AI for Your First Week

AI for Your First Week

Seven nights. One box each.

Anyone can use this page. Copy the prompt and try it today.

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Everyday AI

AI for Your First Week

Notes, questions, and the day-one email.

You stay the editor. The model drafts. You decide.

$4.99 · 20 pages

Beginner shelf · new-job week · you stay the hire

Everyday AI · First Week1 / 20

CONTENTS

What's in this book

Read pages 3 through 6. Then copy one cream box.

03The Idea — Stay new. Sort the mess.
04What The Labs Found — Notes first. Claims small.
05Before You Paste — Use this script at your desk
06How To Use This — Four moves, then your review
07Day-One Names — Build a list, not an org chart
08The Glossary — Separate general meaning from local meaning
09The Intro Email — Warm, brief, and still new
10The Task I Don’t Get Yet — Turn fog into questions
11First Meeting Notes — Keep decisions separate from fragments
12The Honest Status — Say what moved—and what did not
13The First 1:1 — Bring three useful things
14What I Learned — Make Friday useful, not shiny
15Monday From My Notes — Plan three hours, not a new life
16The Scary Question — Put the question where people can see it
17One Small Thing A Day — Match the box to the mess
18Stuck — Repair the reply, not your whole system
19Friday Desk Reset — Leave a trail for next-week you
20Sources — Research behind page 4
Everyday AI · First Week2 / 20

THE IDEA

Stay new. Sort the mess.

At 5:42 on Monday, Priya’s notebook says “Sam—badge,” “Jules?”, and the name of a tool she cannot spell. She does not need to sound senior by Tuesday. She needs tomorrow’s questions in one place.

Use it as a clerk. Give it your notes. Ask it to label gaps. Let it shape a short draft.

Do not use it as a witness. It was not at orientation. It does not know who owns the board, what an acronym means here, or whether a deadline changed.

You stay the new person. You send the introduction. You do the task. You tell the truth about status. You ask the question.

Every cream box gives the model a job: Role, Task, Details, Format. The model drafts. You compare the draft with what happened.

Hard nos: No invented teammate, policy, decision, metric, or progress. No borrowed seniority.

Then do this: If a line did not come from your notes or a person who knows, delete it. Sounding new is allowed.

Everyday AI · First Week 3 / 20

WHAT THE LABS FOUND

Notes first. Claims small.

Theo wants proof that AI will make him good at his new job. The research cannot promise that. It can show a few useful habits.

1 · Stanford/MIT: In a study of customer-support agents, an AI assistant raised issues resolved per hour by 14% on average and about 34% for novice and lower-skilled agents. That setting matters.

2 · OpenAI: Writing is about 40% of work-related ChatGPT messages. About two-thirds of writing messages ask the model to modify the user’s text. Bring notes. Edit the result.

3 · Anthropic: Be clear and give a role. For long material, putting the notes first and the question last improved quality by up to 30% in tests, especially with complex documents.

4 · Google: Name the objective, persona, context, constraints, and response format.

Hard nos: Do not turn a customer-support result into a promise for every job or new hire.

Then do this: Start with what you actually heard or did. Ask for a narrow shape. Check every claim.

Everyday AI · First Week 4 / 20

BEFORE YOU PASTE

Use this script at your desk

June is about to paste her whole onboarding folder into a chat. It contains customer names, internal links, and a confidential document. She stops.

SAY THIS BEFORE YOU PASTE

“I am using my own short notes. I am not pasting confidential material. The model was not in the room. It may sort or edit, but it may not fill gaps with guesses. I will review the result before I send, say, or act on it.”

Replace full names with first names or roles when that is enough. Remove customer details, access links, passwords, private employee information, and documents you are not allowed to share. Mark uncertainty as [unknown] instead of guessing.

Hard nos: No confidential documents, secret links, passwords, restricted customer data, or private employee information.

Then do this: Read the material as if it appeared on a public screen. If that would make your stomach drop, remove it and ask a colleague instead.

Everyday AI · First Week 5 / 20

HOW TO USE THIS

Four moves, then your review

Noah has twenty minutes before lunch. He chooses the unclear-task page, not every box in the booklet.

  1. Pick the moment. Names, a message, notes, or one question.
  2. Copy one box. Replace every bracket. Write [unknown] when needed.
  3. Put notes before the final instruction. Keep the requested answer short.
  4. Review against reality. Check every name, date, owner, deadline, decision, and claim of progress.

Role narrows the job. Task names the action. Details hold facts and limits. Format prevents a wall of text.

Hard nos: Do not paste material your employer forbids you to share. Do not let the model invent policy, approvals, reporting lines, metrics, or completed work. Do not send its wording untouched.

Then do this: Change at least one line into language you naturally use. If you cannot explain a sentence, do not send it.

Everyday AI · First Week 6 / 20

DAY-ONE NAMES

Build a list, not an org chart

Priya’s notes contain three names, two arrows, and “ask Sam about badges.” She cannot remember whether Jules owns the tracker or merely showed it to her.

COPY THIS

Role: You are a careful day-one notes clerk for a new hire.

Task: Turn my scribbles into a names-and-questions list. Use only what I wrote.

Details: New hire: [Priya]. Notes: [paste]. Names exactly as written: [Sam, Jules, name missed]. Clear connections: [Sam—badges]. Uncertain connections: [Jules—tracker?].

Hard no: Do not invent people, titles, reporting lines, contact details, or company facts. Keep uncertain items uncertain.

Format: Name as written | What I know | What is uncertain | My next question. Use “unknown” for blanks.

A neat table can quietly turn arrows into official reporting lines.

Then do this: Compare every row with the notebook. If a question mark became a fact, reply: “Questions stay questions. Do not infer relationships.”

Everyday AI · First Week 7 / 20

THE GLOSSARY

Separate general meaning from local meaning

Luis hears “standup,” “ticket,” “SLA,” and “the board.” A general definition may help. It cannot tell him what those words mean on this team.

COPY THIS

Role: You are a cautious glossary partner for a new hire.

Task: Organize the terms I heard. Separate general meaning from meaning I must confirm here.

Details: Terms: [paste]. My guesses: [paste]. Context I heard: [paste].

Hard no: Do not present a general definition as this company’s official meaning. Do not invent systems, rules, targets, or processes.

Format: Term | My current guess | Careful general meaning | What to ask a colleague. Label local meanings “confirm here.”

The likely failure is confidence: broad workplace knowledge gets presented as local policy.

Then do this: Star every “confirm here” item. Ask a human about the term needed for today’s work. Do not memorize the draft as company policy.

Everyday AI · First Week 8 / 20

THE INTRO EMAIL

Warm, brief, and still new

June’s first generated draft calls her a “results-driven leader” and adds an achievement she never mentioned. Neither belongs in her introduction.

COPY THIS

Role: You are a plain-language email editor for a new hire.

Task: Draft a short introduction from my facts. Keep me new.

Details: Name: [June]. Audience: [team]. True facts: [paste]. Optional personal detail I chose: [paste]. How to reach me: [paste].

Hard no: Do not invent experience, achievements, credentials, metrics, colleagues, or company facts. No fake confidence.

Format: One subject line and an email under 110 words. Short paragraphs. End simply.

The failure is biography inflation. Smooth prose can smuggle in a career story you did not give.

Then do this: Read it aloud. Delete any claim you would feel awkward defending over coffee. Replace one polished phrase with words you actually say. You send it.

Everyday AI · First Week 9 / 20

THE TASK I DON’T GET YET

Turn fog into questions

Noah is told to “clean up the tracker.” He does not know whether that means fix labels, remove old rows, or check owners. The model does not know either.

COPY THIS

Role: You are a patient task-clarity partner. You explain; I do the work.

Task: Identify what is known, what is ambiguous, and what I should ask before acting.

Details: Exact request: [paste]. Who asked: [name/role]. Deadline heard: [date/unknown]. Notes: [paste]. What I tried: [paste].

Hard no: Do not invent columns, owners, standards, deadlines, or procedures. Do not complete the task or claim it is done.

Format: Known facts; possible meanings labeled as possibilities; three clarifying questions; one safe first step that does not alter data.

A plausible checklist may be completely wrong for this workplace.

Then do this: Ask the question that would most change your next action. If it directs edits, reply: “No changes yet. Clarify the assignment first.”

Everyday AI · First Week 10 / 20

FIRST MEETING NOTES

Keep decisions separate from fragments

Imani leaves standup with “Sam blocked,” “Friday?”, and two acronyms. She wants a recap, not decisions nobody made.

COPY THIS

Role: You are a conservative meeting-note editor for a new hire.

Task: Organize only what I recorded. Preserve uncertainty and expose missing context.

Details: Meeting: [paste]. Raw notes: [paste]. Names caught: [paste]. Words not understood: [paste].

Hard no: Do not invent attendees, decisions, owners, deadlines, motives, or action items. Do not resolve unclear shorthand.

Format: What I heard | Possible actions to confirm | Questions. Quote uncertain fragments. Label interpretations “possible, not confirmed.”

The model may turn “Friday?” into “Due Friday” or attach an action to the nearest name.

Then do this: Highlight every action, owner, and date. If it was not explicit in your notes, move it to Questions.

Everyday AI · First Week 11 / 20

THE HONEST STATUS

Say what moved—and what did not

Theo gets “Can you send status on this?” He opened the file and asked one question. A polished draft calls that “significant initial progress.”

COPY THIS

Role: You are an honest status-message editor for a new hire.

Task: Draft a brief update from facts I can verify.

Details: Request: [paste]. Work completed: [paste]. Not done: [paste]. Blocker/question: [paste]. Next update I can promise: [time].

Hard no: Do not invent progress, percentages, findings, approvals, people, or certainty. Do not hide that I do not know yet.

Format: Under 70 words: what I did, what remains unknown, and when I will update. No performance adjectives.

The failure is padded progress. “Reviewed,” “advanced,” and “on track” may claim more than happened.

Then do this: Underline every verb. Ask, “Did I actually do this?” Replace any verb you cannot prove. Promise only a time you can keep.

Everyday AI · First Week 12 / 20

THE FIRST 1:1

Bring three useful things

Claire completed one small task, still cannot find the badge process, and needs her manager to choose between two priorities. She needs an agenda, not a performance review.

COPY THIS

Role: You are a first-1:1 preparation partner for a new hire.

Task: Pull three factual discussion points from my week.

Details: What I completed: [paste]. What I am learning: [paste]. What is unclear: [paste]. Help I need: [paste].

Hard no: Do not rate my performance, invent wins, assign motives to my manager, or add metrics or goals I was not given.

Format: Update | Question | Ask. Under each, write one or two spoken sentences. Add a blank line for my manager’s answer.

The model may turn a first conversation into a speech about impact and growth.

Then do this: Say all three points aloud in under one minute. If they sound like a promotion case, reply: “This is week one. Use plain facts and one clear ask.”

Everyday AI · First Week 13 / 20

WHAT I LEARNED

Make Friday useful, not shiny

Mateo learned where requests enter the team, mixed up two acronyms, and found the right person for access questions. That is enough for a real recap.

COPY THIS

Role: You are a Friday learning-note editor for a new hire.

Task: Turn my week’s notes into a factual reflection in my voice.

Details: Notes: [paste]. Things I can explain: [paste]. Things still unclear: [paste]. One thing to try Monday: [paste]. Audience: [private/manager].

Hard no: Do not invent lessons, wins, feedback, people, metrics, or Monday commitments. No victory-lap language.

Format: Six short bullets: two things learned, one useful person/resource from my notes, two open questions, and one Monday experiment.

The danger is invented learning: a complete-sounding recap with conclusions you never reached.

Then do this: Point to the note supporting each bullet. If you cannot, delete it. Turn private frustration into a neutral question before sharing.

Everyday AI · First Week 14 / 20

MONDAY FROM MY NOTES

Plan three hours, not a new life

Anya has two leftover questions, one promised update, and a 9:30 standup. She needs Monday morning to fit on one screen.

COPY THIS

Role: You are a narrow Monday-morning planner for a new hire.

Task: Arrange only the tasks and meetings in my notes into the first three hours.

Details: Window: [9–12]. Fixed meetings: [paste]. Promises: [paste]. Open tasks: [paste]. People I may ask: [paste].

Hard no: Do not invent meetings, priorities, people, deadlines, or a 30/60/90-day plan. Do not assume an optional task is urgent.

Format: Timeline with start time, action, and stopping point. Add a parking list and one item to drop if the morning changes.

Generated plans often use every minute and add worthy-looking goals.

Then do this: Check the calendar and promised times yourself. Leave one open block. If there are more than three main actions, reply: “Protect the promise. Park the rest.”

Everyday AI · First Week 15 / 20

THE SCARY QUESTION

Put the question where people can see it

Wes has wondered since Tuesday who owns the board. His draft begins with a paragraph apologizing for being new. The question is buried at the bottom.

COPY THIS

Role: You are a question editor for a new hire. I will ask it myself.

Task: Make my question brief, respectful, and visible.

Details: Rough question: [paste]. Person: [name/role]. Channel: [chat/1:1]. Relevant context: [paste]. What I fear: [paste].

Hard no: Do not invent the answer, owner, or company process. Do not add a long apology or hide the question.

Format: First, one direct question. Second, a version with no more than two sentences of context.

The failure is avoidance disguised as polish. A kind paragraph can make the needed response unclear.

Then do this: Read only the first sentence. Can the person answer it? If not, reply: “Put the answerable question first.” Then send it or say it.

Everyday AI · First Week 16 / 20

ONE SMALL THING A DAY

Match the box to the mess

June is tempted to run every prompt. She has one immediate problem: tomorrow’s 1:1. She opens that page and leaves the others alone.

Names sliding around? Build the names list.

Team language foggy? Make the cautious glossary.

Assignment unclear? Separate facts from questions.

Meeting notes fragmented? Organize without inventing decisions.

Status requested? Report only real progress.

Manager conversation coming? Prepare an update, question, and ask.

Friday a blur? Record learning and open questions.

Monday crowded? Plan only three hours.

Question following you? Draft it plainly and ask.

Hard nos: Do not use ten polished outputs to avoid one human conversation. Do not treat the model’s plan as your manager’s priority list.

Then do this: Choose the page connected to the next real action. When that action is done, close the chat.

Everyday AI · First Week 17 / 20

STUCK

Repair the reply, not your whole system

At 4:50, Luis gets a glossary full of confident company definitions. He does not need another app. He needs one sharper instruction.

Invented fact: “Use only facts and names I supplied. Replace inferences with ‘unknown’ or a question.”

Question became decision: “Restore my question marks. Separate confirmed items from possibilities.”

It did the task: “Explain the assignment and give clarifying questions. I do the work.”

Padded progress: “Use only completed actions I listed. No adjectives, percentages, or implied progress.”

Fake senior voice: “Keep me in week one. Remove performance language.”

Too long: “Cut this by half. Keep facts, unknowns, and next action.”

Hard nos: Do not argue a false draft into being true. Do not keep a sentence merely because it sounds good.

Then do this: Check the corrected version against the source notes again. A second draft can introduce a second error.

Everyday AI · First Week 18 / 20

FRIDAY DESK RESET

Leave a trail for next-week you

At 5:08, Imani has five tabs open and questions on three scraps of paper. Before leaving, she makes one small page for Monday.

People I can ask: Names and only the help you have confirmed.

Words to confirm: Local terms that still need a human definition.

Promises I made: Updates or deadlines you actually agreed to.

Questions still open: Including the uncomfortable one.

First action Monday: One action, not a career plan.

Keep useful drafts beside the notes that support them. Follow your employer’s rules for tools, records, and company information.

Hard nos: No invented certainty. No borrowed seniority. No sending a draft you cannot explain.

Then do this: Put Monday’s first action where you will see it. Close the rest. Being new is not a defect to edit out.

Everyday AI · First Week 19 / 20

SOURCES

Research behind page 4

Brynjolfsson, Erik; Danielle Li; Lindsey R. Raymond. “Generative AI at Work.” NBER Working Paper 31161, April 2023; published in The Quarterly Journal of Economics, 2025. Study setting: customer-support agents.
https://www.nber.org/papers/w31161

Chatterji, Aaron et al. “How People Use ChatGPT.” OpenAI, September 15, 2025; NBER Working Paper 34255.
https://openai.com/index/how-people-are-using-chatgpt/

Anthropic. “Be Clear and Direct.” Prompt-engineering documentation.
https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/be-clear-and-direct

Google Cloud. “Prompt Design Strategies.”
https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/prompts/prompt-design-strategies

Research can support a prompting habit. It cannot verify your employer’s people, policy, deadlines, or decisions.

Hard nos: Do not use a research result as proof that a generated workplace claim is true.

Then do this: Verify workplace facts with your notes, manager, or colleague.

Everyday AI · First Week 20 / 20