2.5Create tables, lists & reusable templates
The essentials in 30 seconds
- You set the columns, AI fills in: comparing requires explicit criteria — you are the analyst.
- Checklists catch oversights: explicitly request frequent oversights, by phase — exhaustiveness is ordered.
- A good template serves a hundred times: created once, saved in a library — the lasting asset of your skills growth.
Threaded mini-case — Amine and his template library in Algiers
Final act of the level: Amine, project manager in Algiers, capitalizes on his week — his standard follow-up prompt (2.1), his calibrated summary instruction (2.2), his translation glossary (2.3) and his ideation matrix (2.4). He adds three structures: a contractor comparison table (columns set by him), a meeting checklist (before, during, after, with frequent oversights) and a reusable minutes template. Everything joins his personal library: a simple document that will grow at each level.
Epilogue of the 2.1-2.4 thread — Amine turns his week's prompts into a reusable asset.
1. Ready-to-use structures
Have structures produced: comparison tables (vendors, tools, options), checklists (meeting, onboarding, event) and above all reusable templates — minutes framework, standard email, interview grid — created once and reused all year. Like Amine with his contractor table: specify the exact columns and criteria.
2. Tables and checklists that serve
Specify a table (exact columns, criteria, expected verdict) and generate complete checklists, grouped by phase, explicitly requesting frequent oversights — AI excels at exhaustiveness when ordered to. For Excel: request CSV format (semicolon separator) or copy the table directly.
3. Your personal library
Build your personal template library: the file where your templates and standard prompts live. It is the lasting deliverable of this level — the asset that capitalizes your AI learning. A good template created once saves hours every month: invest, and have any regulatory-scope template validated by the relevant department (see 3.4).
Did you know?
Capitalizing means working once to benefit a hundred times.
🔎 Concrete example — 🔎 Worked example — Three useful structures
Amine's three requests (prompts taken from V2):
“Compare [3 options] in a table: cost, deadline, advantages, risks, reco.”
“Meeting checklist: before (D-7, D-1), during, after, + frequent oversights.”
“Reusable minutes framework, sections to complete [in brackets].”Reading: your template library is born.
Lesson: record everything in a simple personal document.
Section vocabulary
- Comparison table
- Specify the columns: “Compare X, Y, Z in a table: price, deadline, advantages, limits, verdict in one sentence”.
Simple example: Amine compares his contractors: cost, deadline, advantages, risks, final recommendation.
What it is not: asking “compare these options” with no columns or criteria.
Reflex: set columns and expected verdict before launching.
- Generated checklist
- “Complete checklist for [task], grouped by phase, with frequent oversights”: AI excels at exhaustiveness.
Simple example: Amine's meeting checklist: before (D-7, D-1), during, after.
What it is not: a scattered list with no phases or flagged oversights.
Reflex: require phases + frequent oversights for each checklist.
- Template
- Fill-in standard document — minutes framework, standard email, evaluation grid — created once, served a hundred times.
Simple example: Amine's minutes framework: sections, bracketed notes, under one page.
What it is not: recreating the same document from scratch at each meeting.
Reflex: create fill-in frameworks for each repeated task.
- Personal library
- The file where your templates and standard prompts live: the asset that capitalizes your AI learning.
Simple example: Amine files follow-up, summary, glossary and matrix in a simple document.
What it is not: prompts lost in conversation history.
Reflex: archive each good prompt as soon as it has proven itself.
- CSV export
- Request a table in CSV format (semicolon separator) to paste it cleanly into Excel.
Simple example: “Give it as CSV, semicolon separator” for the contractors table.
What it is not: recopying a table by hand cell by cell.
Reflex: specify the export format in the instruction.
In practice — In practice — Three structures for your daily work
- The table: “Compare [3 real options from your work] in a table: cost, deadline, advantages, risks, final recommendation”.
- The checklist: “Checklist for preparing an important meeting: before (D-7, D-1), during, after — with classic oversights”.
- The template: “Create a reusable meeting-minutes framework: sections, notes to complete in brackets, under one page”.
- Save all three in your personal library (a simple document) — it will grow at each level.
Ready-to-paste script — create a reusable template
“Create a reusable meeting-minutes framework: sections (decisions, actions with owner and deadline), notes to complete in brackets, under one page. Add at the end the frequent-oversights checklist. I will file it in my personal library and reuse it at each meeting.”
For a regulatory-scope template (HR, legal): starting framework only, validation by the relevant department.
Copy-paste template — reusable minutes framework
MEETING NOTES — [date] / [project] / attendees: [___].
DECISIONS: 1) [___] 2) [___].
ACTIONS: [action] / [owner] / [deadline].
OPEN ITEMS: [___].
NEXT STEP: [___].
MISSED-ITEMS CHECK: [shared? realistic deadlines? owners named?]Options comparison
Three real options, cost, deadline, advantages, risks and recommendation columns: you decide on evidence.
SME Algiers
Amine shares his minutes framework with the team: everyone reports in the same format.
Export to Excel
Table requested as CSV (semicolon): clean paste into the spreadsheet, no retyping.
Standardized template (HR, legal)
AI framework as a starting point, relevant-department validation before any official use.
✓ Best practices
- Specify a table's columns (you are the analyst).
- Explicitly request “frequent oversights” for checklists.
- Capitalize: feed a library of templates and standard prompts.
✗ Common pitfalls
- Letting AI choose a table's columns alone.
- Taking a standardized (HR, legal) template for a validated reference.
- Not capitalizing your templates (redoing everything each time).
Key takeaways
- Specify a table's columns: you are the analyst, AI fills in.
- Generated checklists catch oversights — explicitly request “frequent oversights”.
- A good template created once saves hours every month: invest.
- Your personal library (templates + standard prompts) is the true deliverable of your skills growth.
48h challenge — apply tomorrow
Produce your three structures (real-options table, meeting checklist, minutes framework) and file them in your personal library with the standard prompts of sections 2.1 to 2.4.
- I can specify the columns of a useful comparison table.
- I can generate a complete checklist with frequent oversights.
- I have started my personal library (3 structures + prompts).
Frequently asked questions
How to export a generated table to Excel?
Request CSV format (“give it as CSV, semicolon separator”) and paste into Excel, or copy the markdown table directly — most spreadsheets convert it cleanly. For regular use, keep the prompt that generates the right format: you will reuse it every time.
Are generated templates reliable for standardized (HR, legal) uses?
As a starting point yes, as a reference no: any regulatory-scope template (contract, official HR document) goes through relevant-department validation — the subject of level 3.4. AI produces a clean, complete framework, but compliance always belongs to a professional.
Amine wants a truly useful comparison table. Who sets the columns?