A practical path from context and sources to connected demos, team assets and safe adoption.
The value is also in the business workflow it improves.
Enough concepts to use AI properly. No history lecture.
A model that predicts, reasons, rewrites and structures from context.
An overqualified expert available 24/7, who has absorbed the entire internet — but whose memory wipes clean at the end of every conversation. Without precise instructions and the right tools, they improvise in their own direction, not necessarily yours.
Text, files, images, tables, audio and screenshots in one workflow.
Give the model the right sources so it does not have to guess.
An AI system that can follow steps, use tools and produce a checkable result.
People keep responsibility for judgment, customer impact and production risk.
AI is confident even when context is missing. That is why workflow design matters.
With files, connectors, instructions and tools, it becomes an assistant that has read the case before entering the room.
Prompting is not poetry. It is briefing.
Tell the AI what expert perspective it should use.
Give the business situation, audience, goal and constraints.
Attach the file, paste the facts, quote the approved source.
Ask for an email, table, checklist, memo, JSON or action plan.
Ask it to list assumptions, missing data and human checks.
Ask for a shorter, clearer, more executive or more customer-friendly version.
"Write an email to Carrefour."
No role, no context, no audience, no source, no success criteria.
Using the attached account notes, the retail offer page and the previous Outlook thread, draft a concise follow-up email for a Carrefour regional stakeholder. Keep DRIVECO proof points accurate, list the next three actions, and flag missing commercial information.
A practical map of the tools business teams can use before asking IT to industrialize.
ChatGPT, Projects, file upload, Data Analysis, Deep Research, Canvas, voice and meeting notes.
Custom GPTs, instructions, reference files, apps/connectors, skills and controlled actions.
When a workflow proves its value, extend it — connect APIs, agents and app integrations to scale the output.
Outlook -> 5 livrables business en 60 secondes.
Notion + SharePoint -> brief, objections, follow-up email.
Annonce Autocharge -> 5 contenus pour 4 audiences.
Documents RH Notion -> plan 30-60-90 jours.
Export SAP + bail -> anomalies, obligations, decision memo.
Site Tracker + Slack -> risques, owners, deadlines.
10 tickets + FAQ -> queue structuree et escalades.
Construire un Custom GPT reutilisable en direct.
Retail EV charging -> rapport source et implications DRIVECO.
Transformer la recherche en briefing executif editable.
Same rhythm every time: show the source, produce the business deliverable, then point to missing information and the human validation step.
Same method, different trigger, different sources, different validation owner.
Six workflows connected to DRIVECO tools. One rule: practical or removed.
Account, opportunity, status, next steps.
Pitch deck, approved proof points, partner material.
Previous emails, objections and promised actions.
Account brief, objection table and follow-up email.
Commercial owner checks pricing, promises and next steps.
| Partner | Need | Proof point | Next action |
|---|---|---|---|
| Retail chain | Attract qualified traffic | Fast charging turns dwell time into local spend | Send 5-slide brief |
| Property owner | Recurring income | 0 capex / 0 opex, rent model, long-term lease | Request site eligibility data |
| Fleet operator | Operational continuity | Reliable network, charging speed, support coverage | Prepare objection answers |
Key messages from Autocharge, booking or app feature content.
Drivers, retail partners, property owners, internal audience.
LinkedIn, newsletter, FAQ, partner email, video script and QA checklist.
Invoices, payment status, PO references and anomalies.
Leases, obligations, dates, rent mechanisms and risks.
Account and opportunity context before financial review.
Partner exchanges, missing documents and pending answers.
The goal is to package repeatable work into Projects, GPTs, Skills and approved automations.
One-off task, low reuse, no sensitive data.
Long-running topic with files and instructions.
Recurring team assistant with approved sources.
Standard operating procedure repeated the same way.
IT-secured connector, action, API or agent with approval.
Each person maps one of their own recurring tasks onto the reuse ladder: trigger, inputs, source of truth, expected output, human check, reuse level. First step to turning a manual routine into a structured AI workflow.
Salesforce account brief, SharePoint proof points, Outlook follow-up and partner objection handling.
Role-specific onboarding, manager checklist, interview scorecard and internal FAQ generation.
Autocharge or booking content transformed into multi-audience campaigns with source and claim checks.
SAP export analysis, contract obligation extraction and decision memo with human validation points.
Security is not a reason to stop. It is a reason to design pilots properly.
No secrets, unnecessary personal data, banking data or confidential contracts in unapproved tools.
Ask for citations, attached-file grounding, assumptions and missing information.
Human validation for customer impact, legal, finance, security and production actions.
Read-only pilots, anonymized exports, limited users and controlled permissions.
Time saved, error rate, user satisfaction, escalations avoided and adoption.
Industrialize only after the pilot proves value and risk is understood.
Choose 4 pilot teams: Sales, Marketing, HR, Finance/Admin.
Map 8 repetitive workflows with sources, risk and owner.
Build 4 Projects and 2 GPT or Skill prototypes.
Test with real users on mock or anonymized data.
Document, measure, decide what becomes team standard.
A focused workshop can turn this into measurable internal value.
And if we had to prototype only one workflow first, which one would you choose?