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The Expert Scaling Revolution: How AI Will Democratize World-Class Expertise

When I started Turalabs, my initial strategy was partnering with subject matter experts/influencers (accountants, marketers, coaches, etc.) who had distribution, trust, and deep industry knowledge. The reasoning was simple: they know what to build and have audiences ready to buy.

While this is a win strategy, we're already seeing the next leap. It might not be "AI applications built WITH experts" but rather "experts productizing themselves AS AI agents."

This manifests in two powerful ways:

1. Highly Personalized Teaching: Instead of generic online courses or expensive 1-to-many in-person training, imagine getting personalized coaching from an "AI Neil Patel" (famous digital marketing expert) trained on your specific business context: B2B vs B2C, junior vs senior, your industry challenges, your current skills, etc.

2. Expert AI Assistants: Now, we take things a step further and the "AI Neil Patel" is not "just" a coach/trainer anymore. It has access to your tools and does the actual work. Your "AI Neil Patel" doesn't just advise on digital marketing strategy; it executes campaigns, analyzes results, and optimizes performance.

The first wave is already starting to hit the market. The second will transform entire service industries within 2-5 years. I used the word assistant because as it stands now, you still need to "manage" and have strategic oversight over these agents.

Breaking Free from the "Horseless Carriage" Trap: We Need a New UX for AI

It's the classic "horseless carriage" problem. In the late 1800s, early car manufacturers took existing horse carriage designs and simply removed the horse, added a motor, and kept everything else the same. The result? Unstable, impractical vehicles that couldn't handle their own power.

Now, the same is happening with AI. Most AI-empowered apps today follow the same flawed pattern:

• Take existing interface

• Add AI generation layer with hidden system prompt

• Hide all customization from users

• Wonder why adoption is low

Here's an example:

Gmail's AI writer produces generic emails that sound like no real person wrote them. The prompt you need to write is as long as the email itself. You're doing more work, not less.

What an AI-first design would be:

You teach the AI how you communicate: your tone with your wife vs. your boss vs. school teachers. You provide context about your current situation.

The result: you get emails like: "Hi Gary, my daughter's sick with the flu so I can't come in today. Thanks."

The challenge I'm still pondering: How do users effectively "teach" AI beyond initial onboarding, with intuitive feedback mechanisms that improve over time?

From Q&A to Action: The Interface Evolution AI Needs

While most people are still using AI for Q&A, the technology has already evolved to the AI assistant phase. If you're reading this and you use AI agents, you're not the norm, you're the early adopter.

Current Problem: Every product just embeds a chat interface

• ChatGPT brought LLMs to mainstream through chat

• Now everyone defaults to chatbot interfaces

• This severely limits what AI can actually do

Better Approach: Design for automation and delegation, not conversation

• Think "AI assistant that does work" not "AI that answers questions"

• Focus on accomplishing tasks, not generating responses

I don't think AI can do all the work, nor does it have the intelligence to do it in the near future. However, I believe it can significantly speed up your personal and professional tasks.

The real opportunity: Teaching the 95% of people how to move from using AI to answer questions to taking initiative actions and automating actual work. We're still in the awareness stage!

AI Startup Survival: Five Defensive Strategies

For AI products to be truly useful, you need three components working together:

1. Model Intelligence: Choose and customize the right LLM

2. Context and Memory: Where intelligence gains unique insights and connects to tools (MCPs make this easier)

3. Applications and UI: How users interact with the system for specific industries and use cases

AI wrappers like Cal AI do a very good job with all 3 components, while good digital marketing AI tools do a very good job with components 2 & 3.

The question now becomes: what can you build so that ChatGPT (or another corporate structure like SAP or Salesforce) doesn't ruin your startup idea with one new AI feature?

I've thought about it a lot and learned from multiple sources, like the CPO of Anthropic. Here are the key differentiators:

1. Deep industry knowledge: Understanding specific market workflows (like Harvey's legal expertise)

2. Differentiated Go-to-Market: Knowing exactly who you're selling to and what they really need

3. Distribution advantage: Now it's about building an audience or working with someone who has one. If 1,000 companies build the same to-do list, why would they choose you? If you partner with a productivity guru like Ali Abdaal (+6 million subscribers), you get the first thousands of customers guaranteed!

4. Novel interaction paradigms: Completely different ways to interface with AI

5. Startup Mentality: Working existentially, "you against the world" urgency

Product fundamentals haven't changed. However, you can now ship MVPs faster to validate customer demand, then iterate rapidly.

Tech Leapfrog Opportunity for GCC/MENA: Why Now Is Different

If you live in an emerging market and have funding plus distribution, what are you waiting for? Why not build the next Salesforce? Or any other enterprise software making tens of billions in the West?

It's a lifetime opportunity. Put aside social media platforms and top 10 S&P 500 companies. Each country can now quickly catch up on the technology gap using AI.

This applies across industries. It starts with software but scales to robotics, electronics, and beyond. Before, China built technological know-how through reverse engineering over 20 years. With AI, this timeline compresses to 5 years.

The combination of AI acceleration, global talent access, and local market understanding creates unprecedented advantages for emerging market builders.

So it's time to learn, research, and build. But we need to act FAST!

Conclusion: What This Means for You

These five insights represent more than trends—they're strategic inflection points that will reshape entire industries. I believe businesses & startups that recognize and act on these patterns early will build sustainable competitive advantages.

The quotes & some insights are distilled from some of the most influential voices in AI and venture capital. Check the sources below.

Until next time!

Amine Rabehi

Founder, Turalabs | AI Implementation Expert

Amine

P.S. Need AI solutions for your business? I help businesses implement practical AI solutions that deliver measurable results. Let's explore how these insights apply to your specific situation.