Here's what's actually happening and why it matters

AI is not for the nerds.

The biggest shift in human history doesn't belong on your IT department's desk. It belongs on yours – where strategy meets execution.

Three years ago, I started building AI systems the way I thought everyone would build them: fast, minimal dependencies, straight to users. Then I looked around. Enterprise teams were still writing governance frameworks. Consultancies were still delivering PowerPoints. Offshore teams were still treating AI like another software project.

They're not slow because they lack expertise. They're slow because their structures make speed impossible.

So I keep building. Each project teaches me what theory cannot: what actually works, what doesn't, and why small teams have leverage right now, before that window closes.

AI is the fastest-adopted economically significant technology in human history. When a billion people hold this kind of power, everything changes at once. Education, work, communication, entire industries – already shifting. Much more coming.

This site is for founders who'd rather build than wait for certainty.

The window is 2025–2028.

2025

Year of the Agent

Automation cliff. AI agents handle knowledge work at scale. Companies that move now capture the advantage.

2026

Year of the Robot

Physical automation follows. What started in software extends into the physical world.

2027

ASI Emergence

Artificial superintelligence. The questions shift from "can AI do this?" to "what should AI do?"

2028

Societal Response

Policy catches up. By then, the early movers have already reshaped their industries.

The companies that understand this timeline are moving now—not waiting for certainty.

Where small companies win

Knowledge work niches

  • • Customer needs are standardized
  • • Distribution is digital
  • • Trust barriers are low
  • • No regulatory moats protecting incumbents

Here, speed and AI fluency matter more than size.

Where scale still wins

  • • Heavily regulated industries
  • • Physical goods and logistics
  • • Anything requiring institutional trust
  • • Complex multi-stakeholder environments

Large organizations maintain advantages here—for now.

BUILT

145+

Repositories. I learn by shipping—across healthcare, property, brand education, social monitoring. Real products, real users, real patterns.

CLAUDE PROJECTS

250+

Deep collaboration with AI. I see multi-agent orchestration where others see chatbots—and I think about what this means for work, economics, and society.

MVP VELOCITY

<30 days

From concept to working product. Speed compounds—every week of building is learning that accumulates.

The Doctrine

What I Believe

These aren't abstract opinions—they're patterns I've observed building across industries. This is the foundation for how I think about AI and business.

01

AI is not IT

This isn't a technology upgrade to delegate. It's a fundamental shift in leverage that belongs on the founder's desk. Understanding it yourself changes how you see every decision.

02

Speed is the advantage that compounds

Every week you're learning and building is a week your knowledge compounds. Waiting for certainty means falling behind those who are figuring it out in motion.

03

Small teams have a window

Right now, a small team that moves fast can do what used to require departments. This window exists because the technology is new and the playbooks haven't been written.

04

Outcomes over process

What did you ship this week? Who's using it? These questions matter more than roadmaps and governance frameworks. Results teach faster than planning.

05

The bigger questions matter too

Post-labor economics, AGI control, the nature of intelligence itself—these aren't distractions from building. They're context for why this moment matters so much.

"I'm looking for founders and leaders who sense this shift and want to understand it—both the opportunity and the deeper implications."

The Evidence

What I've Built

This isn't a portfolio—it's proof. I've validated patterns across healthcare, property, brand education, and social monitoring. Each project taught me something that theory couldn't.

I'm not a consultant who advises from the sidelines. I'm a builder who's shipped and seen what works—repeatedly, at speed.

Healthcare

MedHubAI

Production

Empathic, controlled, and compliant AI conversational platform now running at 10 clinics. Built to understand that healthcare isn't just about answers—it's about how you deliver them.

Lesson learned: Compliance and empathy aren't at odds. The best healthcare AI feels human while remaining auditable.

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Real Estate

Property Analysis System

Validated

8 API integrations pulling satellite imagery, planning data, flood risk, transport links, and market intelligence. Turns any address into a comprehensive investment thesis.

Lesson learned: The power isn't in one data source—it's in orchestrating many. Real insight comes from synthesis.

Marketing

BrandGuide.me/AI

Early Bird

RAG-based brand education platform that teaches marketing strategy through conversation. Your brand, your data, your personalised AI mentor.

Lesson learned: Education scales better through AI than through human hours. But the human expertise has to exist first.

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Intelligence

Social Monitoring System

Private

Multi-platform surveillance and analysis for brand reputation and competitive intelligence. Understands context, sentiment, and emerging narratives.

Lesson learned: AI doesn't just collect data—it understands patterns humans would miss at scale.

The Pattern I Keep Seeing

01

Speed compounds

Every week of shipping is learning that compounds. Every week of planning is learning that doesn't.

02

Orchestration wins

Single AI models aren't the breakthrough. Multi-agent systems that orchestrate context, tools, and memory—that's where magic happens.

03

Domain depth matters

The AI isn't the hard part. Understanding the domain deeply enough to know what to build—that's the unfair advantage.