Stop Using AI Like a Beginner (2026 Framework)

I have helped over a thousand people better understand AI, and most of them were stuck at the same place: chatting with ChatGPT and calling it a day. In this walkthrough I give you the three levels of AI adoption for 2026, with the concrete tools at each level. Whether you are a business owner, a student, a freelancer, or an employee, this is the entire panorama in one place.

What you need

• Accounts on the big LLMs to follow along: ChatGPT, Gemini, Claude
• Nothing else; level 2 and 3 tools get their own dedicated tutorials

1. Level 1: AI awareness (0:37)

Level one has two families of tools: LLMs, large language models, and AI wrappers. Most people get stuck here. ChatGPT made the fastest route to one million users in history and made anyone at least twenty percent more productive by killing the tiny tasks: hunting for the right information online, finding the correct tone for an email. But people fail to see beyond those use cases.

2. Deep Research, the feature that pays for itself (2:13)

Deep Research lets ChatGPT browse deep into the web. Be honest: when did you last look past page two of Google? Two starter use cases:

• Product comparison (2:55). A precise document with the pluses and minuses of two products, fed with your personal context, instead of drowning in reviews.
• Sales research (3:48). Run Deep Research on a person before any meeting. I ran it on myself and found information I did not know existed about me. It also finds decision-makers inside companies.

That power is why privacy matters more than ever. Do this right now (5:20):

Settings > Data controls > Improve the model for everyone > Off

If that toggle is on, they are keeping your data.

3. Custom GPTs for support and internal teams (6:02)

Customer support is never the priority in a young business, so build an FAQ bot. My demo custom GPT was built from one small AI-generated document about my services and answers questions like "What are the services this company offers?" from its knowledge base without hallucinating. Visitors do not need a paid license; only the creator pays. Internally, the same trick enforces marketing tone and format guidelines across a whole team.

4. Gemini and the massive context window (8:45)

Gemini started as a model called Bard back in 2023 and was not very good. Now it has the largest memory out there, five times ChatGPT's. In the demo I feed it a 150-page financial report from Meta that would take me two to three days to read. Gemini reads it in about thirty seconds to a minute and returns every value I asked for, with the page and line where each number was found. If a figure looks off, I jump straight to that page and verify.

5. Nano Banana Pro and working by voice (11:31)

For visualization, Gemini uses Nano Banana Pro, one of the biggest breakthroughs in image generation in 2025. It is a visual reasoning model: it adapts the words it puts inside images to the information you give it, and it can even find fractures in X-ray images. I no longer type; I use my voice:

Hey Gemini, can you create an image of the financial KPIs
year on year that you extracted from that report, please?

Then I turn the same data into a reusable slide, or an infographic like gold extraction explained for kids, reworded on request for a geologist. Vulgarization is an art, and this puts it in any technical person's hands.

6. Claude and artifacts (15:51)

Claude, by Anthropic, is my favorite tool. It does not generate images, but artifacts make up for it: customized applications you can put online and share. Flashcards, data dashboards, client portals. Live in the video I type:

I just want you to generate a very simple coin toss game
with heads and tails.

It builds the whole app in front of us, and you can iterate: multiplayer, scores, anything, and even AI inside the artifact itself.

7. AI wrappers: Perplexity and Lovable (18:21)

Wrappers are applications that do not own the brain they run on. Perplexity took OpenAI's model and built the one thing early ChatGPT lacked: web search, and later the first deep research, the feature you now see everywhere. Lovable went further: the fastest startup in Europe to reach 100 million US dollars annual revenue, and it lets you build applications with no code. Dashboards, client portals, CRMs. One team rebuilt eduSign with Lovable in a couple of days and got a cease and desist for their trouble. Entire functioning businesses with real recurring revenue have been built this way by non-technical teams.

8. Level 2: AI integration (23:02)

Everything you do on a computer is a series of steps, a workflow. Integration starts when you replace one block with a small AI block. Blunt truth: a lot of what businesses should automate does not require AI at all and could have been automated five to ten years ago. First write your core workflows down as SOPs.

My favorite no-AI example (25:39): late invoices. In Make.com, a Google Sheet holds every invoice sent; while an invoice stays in the sheet, the client automatically gets an email at 5, 7, 14, 21, 30, and 60 days, each a bit more aggressive. No AI needed whatsoever.

AI-enhanced automations (26:48) add one reasoning bubble. My n8n workflow watches job posts, which reveal a company's tech stack and prove it has both a problem and budget. A ChatGPT node reads each post and decides: does this look like someone Miguel could talk to? If yes, into the database.

Agentic automations (29:31) hand the AI real decisions about which tools to use. My WhatsApp agent, six nodes glued together, was built for a coach getting 20 to 30 messages a day: it interviews prospects about motivation, budget, and start date, then briefs the coach only on the serious ones. Agents were an unreliable buzzword in early 2025; models now follow instructions consistently enough that 2026 is their year.

9. Level 3: AI adoption and Antigravity (31:45)

Level three is where AI-native companies live, and the thing to learn is agentic workflows. Antigravity is an IDE, which just means software used to create software. You do not need to write code, the same way your friend understands Spanish without speaking it: you need the high level, what an API is, how batching works, and the judgment to check the output. Everything on your computer is code, so everything on your computer becomes automatable.

Antigravity looks like ChatGPT but is ten to a hundred times more powerful: it has access to the browser, the web, and your files. Live demo:

Hey Gemini, can you go to the Apple website and give me
the latest products they released, please?
Just create a list for me after you browse it.

It opens Chrome and clicks through the site itself. For web people this means testing accessibility, responsiveness, and animation bugs automatically. My Observer workflow, inspired by the founder of Swan.ai, finds the people interacting most with my LinkedIn posts and qualifies them against my target profile, and my personal website was created one hundred percent with AI using Antigravity and Claude Code. Claude Code is the same Claude model from level one, in a different place, and twenty to fifty times more powerful.

10. My two predictions for 2026 (40:52)

First, memory: models are already smart enough for business use cases; context is the limiting factor, and whoever cracks bigger memory takes a huge step up. Second, image and video generation: Nano Banana Pro arrived one to two years ahead of schedule.

11. The 5 core AI skills (43:37)

AI is a transversal skill, not a tool skill. Following Nate B. Jones's breakdown:

1. AI strategy. Should AI even be in this workflow? You become a manager of robots, but a manager nonetheless.
2. Prompting. Not typing prompts manually, but reading an AI-generated prompt, spotting the vague part, and testing to pinpoint the problem.
3. Workflow integration. If yes, which tools, how do they glue together, and where does the human sit?
4. Human evaluation and taste. AI output without a tasteful human overseer becomes AI slop. The human evaluates; the AI executes.
5. Ethics. Nano Banana Pro can generate passport pictures. Where do you put the guardrails, and how do you earn your customers' trust?

Pitfalls and tips

• Do not bolt AI onto a business without SOPs. You cannot automate steps nobody has written down.
• Ask "does this need AI?" before every automation. Invoice reminders and onboarding do not.
• The tool matters less than the driver. Full value from a twenty dollar subscription beats an expensive stack with no method.

Where to go next

Go deep on level one with Get Your Money's Worth from ChatGPT and Get Your Money's Worth from Claude.