Your Tech Stack Isn’t the Problem — How You Use It Is.

Most Companies Already Have a Tech Stack—But Are They Using It Well?

Most organizations have already chosen their foundational tools. Whether it’s Microsoft 365 or Google Workspace, they have email, documents, spreadsheets, slides, and chat. Yet, despite having these essentials, they struggle to:

• Document and share knowledge effectively
• Leverage AI for efficiency and decision-making
• Connect their tools so they work together seamlessly

The issue isn’t usually the tools themselves—it’s how well they’re used. Without intentionality, even the best software becomes just another layer of digital clutter.

The Real Gaps: AI, Documentation, and Analytics

Rather than pushing new tools, I focus on helping teams use what they already have more effectively. The biggest gaps I see are in:

✅ AI-Driven Workflows – AI is often misunderstood, leading to underuse or abandonment. Worse, when organizations, teams, or individuals use AI, it is often without the personalization and context that would make it useful to them. With trained AI assistants, I can convert transcribed meeting notes into a detailed project plan in 30 minutes—a game-changer for execution speed.

✅ Documentation Culture – Teams store knowledge in emails, scattered files, or people’s heads. A structured Notion workspace (or a Microsoft/Google equivalent) ensures knowledge is accessible and actionable.

✅ Embedded Analytics – Organizations measure their work, but often measure the wrong thing or are inefficient in capturing performance (looking at you, Excel). The "how" of analytics is flexible, but the ability to turn insights into action is critical.

Real-Time AI in Action: From Confusion to Clarity in Seconds

I recently had a virtual meeting where we were discussing hierarchies and permissions in software. It was a complicated topic, and I could see that some participants—especially the executives—were struggling to visualize what I was describing. In an in-person meeting, I would normally grab a marker and head to the whiteboard. Since it was on Google Meet, I didn't have my whiteboard. Instead of continuing to explain verbally and risk losing more time, I turned to my custom-trained ChatGPT assistant and asked it to generate Mermaid.js code for a chart that mapped out the structure.

AI doesn’t render the chart itself, but I had a Notion page already open for meeting notes, which does support Mermaid natively. I pasted the generated code directly into Notion, and within seconds, I had a fully rendered, structured visualization.

I took a quick screenshot, dropped it in the meeting chat, and immediately, the executive got it. He now had a concrete artifact to take back to his team, making the decision-making process easier.

Had I wanted to, I could have shared the entire Notion page, but I chose not to dilute the impact of the visualization. The goal wasn’t to overwhelm them with more data—it was to deliver exactly what was needed, at the right moment, to drive understanding.

This is the power of AI-driven workflows. It’s not just about automation—it’s about removing friction from decision-making and turning complexity into clarity.

A Decision Framework: When to Use New Tech vs. Optimize What You Have

Not every problem requires a new tool. Before adding a new tool, consider whether a process or workflow adjustment could be the real solution. Here’s a structured way to decide whether to adopt new technology or optimize your existing stack.

Mermaid Decision Tree

View the chart here

graph TD  
    A["Do you have an existing tool?"] -->|No| B["Evaluate new solutions"]  
    A -->|Yes| C{"Is it meeting your needs?"}  
    
    C -->|Yes| D["Optimize usage"]  
    C -->|No| E{"Can it be improved with better workflows?"}  

    E -->|Yes| F["Train team / Improve integration"]  
    E -->|No| G["Consider new technology"]  
    
    B --> H["Assess cost, complexity, and ROI"]  
    G --> H  
    H --> I{"Does the new tool provide significant value?"}  
    
    I -->|No| J["Stick with existing tool and refine process"]  
    I -->|Yes| K["Implement new tool with clear use case"]          

This decision tree helps guide intentional technology choices rather than defaulting to new tools. It’s not flashy, but it took just 30 seconds—proving how fast AI can turn ideas into action.

• If a current tool exists, first evaluate if it meets needs before replacing it.
• If gaps exist, check if they can be solved through better workflows or training rather than new software.
• Only move to new technology when it clearly provides significant value over the existing option.

An Intentional Tech Stack That Works for You

I don’t impose new tools unless necessary. Instead, I help organizations:

• Make the most of Microsoft 365 or Google Workspace, leveraging tools they already pay for.
• Introduce lightweight AI-driven workflows with minimal disruption
• Improve documentation and knowledge sharing so teams move faster
• Measure what matters with simple, embedded analytics

My Flexible Stack for AI-Augmented Work

While I’m open to working with what organizations already use, my personal stack includes:

🗂 Documentation & Knowledge Management

• Notion – Centralized knowledge, shared workspaces, instant websites, and rapid project planning (I like it enough to be an affiliate)
• Mermaid.js – For quickly visualizing processes and structures

📢 Communication & Research

• Slack – Vendor and team communication
• Loom – Async video walkthroughs to speed up explanations
• Perplexity & NotebookLM – For deep research, documentation, and reference gathering

🤖 AI & Automation

• ChatGPT (with Custom GPTs) – Personalized AI that enhances workflow efficiency
• Make.com / Zapier – Connecting tools and automating manual processes

📊Data & Reporting

• Power BI, SQL, & Embedded Analytics – Helping organizations measure their progress without forcing them into a rigid reporting system

The Focus Is on Value, Not Tools

I don’t get stuck in change events that focus on tool-switching rather than execution. The real question is:

👉 What needs to be done?

👉 What’s the gap between the current and future state?

👉 How can we get there faster with AI and structured documentation?

The era of AI-powered work isn’t about adding more tools—it’s about using them better.

What’s in Your Tech Stack?

Are your tools truly helping you work smarter and faster—or just adding to the noise?

💡 How are you using AI, documentation, and analytics to accelerate your work? Let’s discuss.