Overview
Upskilling Circle was an AI-native startup I co-founded; a useful contrast to the NGO and consultancy cases. This was one of the clearest cases where Notion was not just a place to organize work after the fact. It became the operating layer where the startup’s research, courses, meetings, CRM, website, assessment flow, content, and proposals compounded together.
My cofounder Majdi was not familiar with Notion at first. He bought into it after seeing what it could do for him as a coach and entrepreneur. His reaction captured the shift well:
“Pure magic!!”
The magic was not that Notion looked impressive. It was that the workspace let us move from scattered thinking to a connected startup operating system: research informed courses, meetings enriched CRM profiles, CRM context shaped proposals, website content drew from the same knowledge base, and our AI-readiness assessment fed directly into company records.
The challenge
Upskilling Circle needed to move quickly. We were building an AI-native startup around people development, AI readiness, operational improvement, and practical automation. That meant we needed to research deeply, package services clearly, develop courses, manage leads, follow up with clients, maintain website content, and produce proposals; all without becoming buried in scattered documents and disconnected tools.
The risk was obvious: a tiny founding team could easily lose its own thinking. Research could live in one place, meeting notes in another, CRM updates somewhere else, social content in drafts, and proposals as isolated documents. Every new course, article, assessment, roadmap, or client proposal would then start from partial memory.
We needed the opposite: a workspace where every serious piece of thinking stayed reusable.
What I built
I set up Upskilling Circle’s Notion workspace around the startup’s actual operating needs:
- Research knowledge base: multiple research directions organized as reusable foundations for courses, articles, assessments, roadmaps, and proposals.
- Course development: courses developed directly inside Notion with the help of Notion AI.
- Meeting notes: team and client meetings captured, summarized, and turned into tasks.
- CRM: lead and client profiles connected to meetings, notes, opportunities, proposals, and follow-up.
- Social media content: content ideas and drafts grounded in the same research base and positioning.
- Website backend: website content developed and maintained from the same knowledge base.
- AI-readiness assessment: assessment submissions came directly into Notion, creating CRM entries for the companies.
- Proposals and client work: proposals drew from research, lead context, meeting history, and reusable service language.
This setup meant we were not just storing information. We were building compounding context.
Research as the foundation
The first major value of the workspace was research. We organized several research directions in one knowledge base so they could become the accessible foundation for everything else: courses, articles, AI-readiness assessment, AI roadmaps, client proposals, and service positioning.
That mattered because Upskilling Circle was not selling generic AI hype. We needed grounded thinking about what organizations actually struggle with: unclear AI readiness, poor process integration, manual work, team habits, leadership gaps, and the difficulty of moving from experimentation to real operational value.
Instead of treating research as background reading, the workspace made it reusable. A research note could inform a course module, a website section, a client proposal, a LinkedIn post, or an assessment dimension.
Courses and products developed inside Notion
We developed courses directly inside Notion, with Notion AI helping shape drafts, outlines, explanations, exercises, and supporting material.
The important part was that course development stayed close to the research and client context. We were not writing in a blank document. We were building from the same base that held our positioning, our market thinking, our client conversations, and our evolving service design.
This made product development faster and more consistent. New material did not need to be invented from scratch every time; it could be assembled, tested, refined, and connected back to the broader knowledge base.
Meetings, tasks, and CRM
The meeting workflow was one of the strongest parts of the system.
Team and client meetings were captured and turned into structured notes. Those notes generated assigned tasks and preserved decisions, follow-ups, and useful signals. More importantly, client meetings enriched lead profiles in the CRM.
That changed how proposals and products developed. A lead profile was not just contact information. It could carry meeting history, needs, objections, context, proposed ideas, next steps, and clues about the organization’s readiness. That made proposal work faster and more grounded.
The workflow gave us a kind of organization and alignment that was native to none of us. It reduced the amount of coordination we had to hold in our heads.
Website and assessment backend
The knowledge base also became the foundation for developing and maintaining the Upskilling Circle website.
Website content was not separate from the startup’s thinking. It drew from the same research base, offer development, course material, and positioning work. This helped keep the site aligned with what we were actually learning and building.
The free AI-readiness assessment was also integrated with the backend. Assessment submissions came directly into Notion, and CRM entries were created for the companies. That meant inbound interest did not disappear into a form tool. It became part of the same operating system: a company record, a readiness signal, a possible lead, and a starting point for future conversation.
Why Notion AI became more useful
This setup made Notion AI dramatically more useful than using a generic chatbot against disconnected material.
ChatGPT and NotebookLM can be powerful, but they usually depend on what you upload or paste into them in the moment. Inside the Upskilling Circle workspace, Notion AI had access to the working context: research, meetings, CRM profiles, course material, proposals, website content, and assessment data.
That made the AI feel less like an external assistant and more like an operating partner grounded in the startup’s actual work.
A fair way to put it: this setup made Notion AI feel 10x more useful than using ChatGPT and NotebookLM separately, because the intelligence was embedded where the work already lived.
Impact
The most important impact was compounding.
- Research did not die in documents.
- Meetings did not disappear into transcripts.
- CRM notes did not stay separate from proposals.
- Website content did not drift away from the actual service logic.
- Assessment submissions did not become isolated form responses.
- Course material stayed connected to the thinking that produced it.
The workspace helped us do more with less overhead. It gave a small founding team a shared operating memory: one place where ideas, client signals, tasks, leads, content, and products could reinforce each other.
It also helped Majdi see Notion not as “another productivity app,” but as a serious environment for coaching, entrepreneurship, and AI-native knowledge work.
What this case proves
Upskilling Circle shows what happens when Notion is used at the beginning of a venture, not after the mess has already accumulated.
The workspace was not just documentation. It was the startup’s production environment: research engine, course studio, meeting memory, CRM, website backend, assessment backend, content system, and proposal support layer.
For a small AI-native startup, that mattered. It let us move like a more organized team than we naturally were, and it made every serious piece of thinking easier to find, reuse, and build on.