A structured, self-paced platform. Not a newsletter, not a YouTube channel, not a weekend bootcamp. Real clarity on the fundamentals of AI, built for working professionals and the leaders making decisions around it.
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Structured Path

Not random articles or YouTube rabbit holes. A carefully sequenced path where each module builds on the last, from how AI actually learns to evaluating what's coming next.

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Depth Over Speed

Each topic built on real intuition and visual explanations. You'll understand the "why" behind the technology, not just memorize the buzzwords.

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Real-World Context

Every concept anchored to what's happening now. Understand why DeepSeek rattled the industry, what makes one model cheaper than another, and why most AI agent deployments fail.

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Applied Understanding

Evaluate AI vendor pitches, challenge your team's assumptions, and make decisions grounded in how the technology actually works, not how the marketing describes it.

Early access pricing and format details will be shared with the waitlist first. Whether you're leading a team, evaluating vendors, or building with AI yourself, the foundations are the same. The goal: become someone who actually understands this technology, not just someone who uses it.

You've read the headlines. You've sat through the all-hands. You've nodded along when someone said "agentic AI" or "MCP" like it was obvious. But if someone asked you to actually explain how any of this works, you'd struggle. That's not your fault. The entire AI content ecosystem is optimised for clicks, not comprehension. One article says AI will take your job. The next says it's overhyped. Neither helps you actually understand what's happening. This platform exists to fix that.

How AI Actually Learns

What really happens when an AI "learns" something? We'll build the intuition visually, no maths degree required. By the end, you'll understand why some AI models are smart and others are just expensive.

How ChatGPT, Claude & DeepSeek Work Under the Hood

Everyone uses these tools. Almost nobody knows how they actually work. You'll understand what makes one model better (or cheaper) than another, and why that matters for the tools you pick.

Finally understand the product you use every day

The AI Behind Images, Video & Voice

Kling generates photorealistic video from a text prompt. ElevenLabs can clone your voice from 30 seconds of audio. How does any of this actually work, who owns what it creates, and what are the copyright implications for your business? Understand the technology reshaping trust, content, and IP.

If your company uses AI-generated content, this is a legal question too

How AI Gets Trained (And Why That Matters To You)

Every vendor claims their model is "custom-trained" or "purpose-built." What does that actually mean? Understand the real pipeline so you can evaluate AI products and claims with confidence.

Read beyond the hype when DeepSeek says it built a frontier model for $6M

AI Agents: What's Real and What's Hype

Everyone's talking about AI agents that can book flights, manage your inbox, and run your business. Some of it is real. A lot of it isn't. Learn to tell the difference before you bet on the wrong tool.

The truth about autonomous AI

Why AI-Generated Code Breaks (And Why You Should Care)

Your team is using Cursor, Copilot, and Claude Code. 45% of AI-generated code ships with vulnerabilities. Whether you write code or manage people who do, you need to understand what these tools actually get right and where they fall apart.

Cursor, Claude Code, Copilot

How To Know When AI Is Wrong

AI sounds confident even when it's making things up. Learn how to spot hallucinations, evaluate AI output, and build the instinct for knowing when to trust it and when to question it.

Cut Through the Noise Yourself

New models drop every week. Everyone has a hot take. Instead of depending on someone else's opinion, build the foundation to evaluate what's real, what's marketing, and what actually matters to you.

Never depend on hype cycles again

Two-thirds of CEOs admit they invest in AI before understanding its value. Then they cut headcount to justify the spend. You deserve better than being a bystander in someone else's hype cycle.
75%
of AI projects fail to deliver promised ROI according to IBM's survey of 2,000 CEOs
IBM 2026
45%
of vibe-coded output contains security vulnerabilities, shipped by people who never looked at the code
CodeRabbit Dec 2025
55K
jobs explicitly cut "because of AI" in 2025, but Oxford Economics says most were dressed-up layoffs
Challenger, Gray & Christmas
$250B+
in corporate AI investment this year, while most companies can't explain how the technology they're buying actually works
Industry Estimates 2026
$67.4B
in global losses attributed to AI hallucinations in 2024. 47% of enterprise users made major decisions based on hallucinated content
Deloitte 2025
95%
of enterprise generative AI pilots fail to reach production. Most stall in proof-of-concept mode without anyone understanding why
MIT / IBM Global AI Adoption Index

One company fires half its workforce and the stock jumps 24%. Another posts $68B in revenue selling AI chips. Meanwhile, the companies that already tried this? They're quietly hiring people back.
Block
Feb 2026: Jack Dorsey, co-founder of Twitter (now X), cuts 4,000 employees at Block, nearly half its workforce. Says AI tools like their in-house "Goose" can do the work.
The market: Shares soar 24%. Wall Street rewards the cuts. Dorsey says "most companies will reach the same conclusion within a year."
The reality: 4,000 people out. The bet is untested. And the CEO of the company that couldn't make Square profitable for a decade is now an AI oracle.
Nvidia
Q4 2026: Posts $68.1B in quarterly revenue. Up 73% year-over-year. Full-year revenue: $215.9B. Net income: $120.1B.
The signal: Jensen Huang calls it "the inflection of agentic AI." Guides next quarter to $78B. The company selling shovels in the gold rush has never been richer.
The question: Hundreds of billions spent on AI infrastructure. But are the companies buying these chips actually seeing returns? Only 1 in 4 AI projects delivers ROI.
Klarna
2023โ€“24: Fired 700 agents, replaced them with AI. CEO declared AI "can already do all of the jobs that we, as humans, do."
What happened: Customer satisfaction plummeted. Robotic responses. Inflexible scripts. CEO admitted cost was "too predominant" and quality was "lower."
Now: Rehiring humans in gig-style "Uber model." Same work, less stability, lower pay. 578 days of disrupted lives later.
Duolingo
Apr 2025: Declared "AI-first." Said it would replace contractors and only hire if AI couldn't do the job.
What happened: 40%+ error rates in AI-generated lessons. 18% drop in user retention. Social media backlash went viral.
One week later: CEO walked it back: "I do not see AI as replacing what our employees do. We are continuing to hire."
55%of companies regret AI-driven layoffsOrgvue / Forrester 2026
50%of AI layoffs predicted to be quietly reversedForrester Predictions 2026
24%of basic tasks completed by the "best" AI workerCarnegie Mellon University
The people making these decisions didn't understand the technology. The people losing their jobs didn't either. That's the problem this platform exists to solve.

Anyone who showed up to work one day and "AI" was suddenly in their job description
Founders buying AI tools without knowing what questions to ask
Anyone evaluating vendors who throw around "agentic AI" and "MCP" to sound impressive
Leaders purchasing automation, AI agents, or AI-built products who need to know what they're actually getting
Anyone unsure what happens to their company's data every time an AI tool processes it
Leaders navigating "build vs buy" without the technical grounding to know which one makes sense
Anyone buying an AI MVP who needs to tell a real product from a ChatGPT wrapper with a logo
Anyone who's already wasted budget on an AI tool that didn't deliver
Leaders who can't tell if their own team actually knows what they're doing with AI
Career changers who don't trust 15-minute tutorials

Founder & CEO, OriCastle | AI Innovation Studio

I've been the engineer writing the code. The leader managing the team building it. The technical sales lead convincing the boardroom to buy it. And now, the founder building AI systems from the ground up. 14+ years across every layer of the org chart, from embedded automotive platforms at Mercedes and BMW to production multi-agent systems in legal tech and recruitment.

That trajectory is why this platform exists. I know what the developer needs to hear, what the manager is actually worried about, and what the executive won't admit they don't understand. I've spent my career translating complex technology across all of these audiences. This platform is built on that same skill: making AI foundations accessible without dumbing them down.

KTH Royal Institute of Technology, Stockholm | M.Sc. ICT InnovationSaarland University / Max Planck Institute | M.Sc. Computer ScienceProduction Multi-Agent SystemsTechnical Solutions Leadership7 yrs Automotive Infotainment6+ Countries

Your job description is changing
whether you asked for it or not.

Doomscrolling AI headlines won't prepare you. Neither will the hype. The people who'll thrive are the ones who understand what's actually happening and why it matters. Join the waitlist. Build the foundations that don't expire.