To understand AI today, start at the beginning.
Four live webinars that walk from the first disruptors in human history to how large language models actually work. Each session builds on the one before it, so by the fourth, today's AI makes sense instead of feeling like magic.
Series starts Wed, Dec 2, 2026 · 9:00 PM ET
Four steps. Each one unlocks the next.
The order is deliberate. Skip a step and the next one is harder to follow, the same way a medical student learns anatomy before surgery.
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The History and Evolution of Disruptors
From hunter-gatherers to today. How farming, writing, the printing press, steam, electricity and computing each upended the world, and what the people living through each shift got right and wrong.
- What makes something a true disruptor, not just a new tool
- The pattern every disruption follows, and how long each took to spread
- Who adapted, who didn't, and why
Why it comes first: it gives you the lens. AI is the newest chapter in a very old story.
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Infrastructure and the Making of Modern Technology
The physical world behind the screen: power grids, undersea cables, chips, data centers and the internet itself. How the pieces were built, and why each one depended on the last.
- How electricity, telecommunications and semiconductors made computing possible
- What the internet really is, physically
- Why infrastructure decides who can use a new technology, and when
Why it comes second: every disruptor in Session 1 needed infrastructure to scale. AI is no different.
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The History of Cloud Compute
From mainframes and time-sharing to the rented, on-demand computing power that runs much of the internet today, and why that shift opened AI development to far more companies.
- Mainframes, PCs, client-server and the move to the cloud
- Renting computing power like electricity, and what it changed
- Why AI models are trained and run in giant data centers
Why it comes third: the cloud turns the infrastructure from Session 2 into something anyone can rent, and that sets the stage for AI.
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Introduction to LLMs and How They Work
What a large language model is, how it learns from text, how it produces an answer, and where it falls short, explained in plain language with no math required.
- Training, prediction and "tokens," in plain words
- What LLMs do well, where they make mistakes, and why
- From chatbots to agents: where this is heading next
Why it comes last: with the first three sessions behind you, an LLM is the logical next step, not a mystery.
Like learning to read.
You learn letters, then words, then sentences, then stories. Jump straight to the story and the letters look like noise. Many AI courses start at the story. This series starts with the letters.
Anyone who wants to understand AI, not just use it.
Leaders and managers
Who will be asked to approve AI budgets and want the context behind the pitch.
Professionals and students
In any field, who want to see where AI came from and where their work fits next.
The curious
Who hear about AI every day and want the whole story in plain language.
Pick one session, or take the whole journey.
Series starts Wed, Dec 2, 2026 · 9:00 PM ET
Single webinar
$39.99 per session
- One live session of your choice
- Good for filling a gap in what you already know
- Pay once, no subscription
- Full refund if you cancel at least 24 hours before your session starts
The full series
$99 for all four
- All four live sessions, in order
- Less than $25 a session, compared with $159.96 bought one at a time
- One payment, no subscription
- Full refund if you cancel at least 24 hours before Session 1 starts; non-refundable after that
Sessions included
Secure online checkout by Stripe. See the cancellation policy.
No recording. Sessions are live only and may not be recorded, screenshotted or rebroadcast by anyone, including the host. This protects everyone in the webinar. For example, during the live Q&A, attendees can ask questions and share what is happening at their own organizations without it being captured.
Miguel Morel, MBA
Founder of Elaria Agentic, with nearly 20 years across insurance, education and healthcare operations, including time as a New York City public school teacher. MBA, Montclair State University; Executive MHA candidate, Columbia University Mailman School of Public Health. Every session is taught as a master class: a clear story, plain language, and room for questions.
Before you sign up
Do I need a technical background?
No. The series is built for people who are not engineers. Every idea is explained in plain language with everyday comparisons.
Do I have to take the sessions in order?
It's strongly recommended. Each session builds on the last, which is why the full series runs all four in sequence. You can still buy a single session if you only want one topic.
How long is each session?
Each webinar runs one hour: a 45-minute presentation followed by 15 minutes of live Q&A.
What is the cancellation and refund policy?
Single webinar ($39.99): cancel at least 24 hours before that session begins for a full refund. Within 24 hours of the start, the purchase is non-refundable.
Full series ($99): cancel at least 24 hours before Session 1 begins for a full refund. After that point, the series is non-refundable, including any sessions you miss.
Can I record a session or get a replay?
No. Sessions are not recorded, and attendees may not record, screenshot or rebroadcast them. This is done to protect everyone in the webinar. For example, during the 15-minute Q&A, attendees can ask questions and share what is happening at their own organizations without it being recorded. Please plan to attend live.
How do I join?
Each session is a live virtual session. We'll email your session details and your secure link to join before your session.
Can my organization buy seats for a team?
Yes. Use the request a proposal form and mention the webinar series.
Start at the beginning. Finish understanding today's AI.
Four sessions. One story. $99 for the full series.