PTENES
TRACK 3

🚀 Advanced: AI Specialists

The next step for anyone who stops “using AI” and starts architecting it: climb the pyramid from prompt to architecture, replace prompt engineering with context engineering, know when to use an agent—and build your own Jarvis, a partner that runs on its own in the background.

Prompthow you ask Contextwhat the AI knows AgenticAI acts Architecture the intent that matters
4
Modules
24
Topics
~2h30
Duration
Advanced
Level
Track progress0 of 24 · 0%

Learning path map

Detailed content

3.1~40 min

🔺 The AI Pyramid

The five levels of AI mastery — from everyday prompting to the architecture of intent that decides everything.

What it is:

A five-step map — prompt, vibe code, context, agentic, and architecture — from the basics to the greatest leverage.

Why learn:

Shows you where you are: you know which step you’re on and what comes next.

Key concepts:

Mastery levels, foundation × peak, progression.

What it is:

The foundation: asking AI well—clarity, examples, and the expected format.

Why learn:

It’s the entry point, but only the first step.

Key concepts:

Instruction, example, output format.

What it is:

Build real things by talking with AI, without writing every line by hand.

Why learn:

You become a builder, not just someone who asks—the prototypes come together in minutes.

Key concepts:

Fast iteration, creating through conversation, prototyping.

What it is:

Feed the AI with what’s in your head and your data—not just the request.

Why learn:

It's the most durable rung: context is your differentiator.

Key concepts:

Context, your IP, unique output.

What it is:

AI that reasons, uses tools, and performs tasks with little supervision.

Why learn:

It's where leverage takes off — but so does the risk.

Key concepts:

Agent, tools, autonomy.

What it is:

Design the system: context, rules, goals, and validation — your intent.

Why learn:

It's the top of the pyramid and what gains the most value in the AI era.

Key concepts:

Intent architecture, validation, system design.

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3.2~40 min

🧠 Context Engineering & Your AI OS

A prompt is how you ask; context is what the AI knows. The most durable step of the pyramid.

What it is:

The distinction between how you ask (prompt) and what the AI knows (context).

Why learn:

Shifts the focus of effort from the lowest-return area to the highest-return one.

Key concepts:

Prompt, context, leverage.

What it is:

Models improve and absorb prompt tricks, but they still need what's in your head.

Why learn:

Invest in what doesn’t become obsolete with every new version.

Key concepts:

Durability, obsolescence, tacit knowledge.

What it is:

Use projects and GPTs with documents, calendar, and priorities already built in.

Why learn:

Stop re-explaining everything and get tailored responses.

Key concepts:

Projects, GPTs, persistent context.

What it is:

A repository of your knowledge: transcripts, emails, DMs, and videos that AI can consult.

Why learn:

AI starts to know you better than you remember everything.

Key concepts:

AI-OS, knowledge base, external memory.

What it is:

Without onboarding, AI is a clever intern guessing; with context, it gets it right.

Why learn:

Gives you a practical sense of how much context to provide.

Key concepts:

Onboarding, sufficient context, calibration.

What it is:

Poor data produces generic output; taking good care of your context makes the result unique.

Why learn:

What sets your output apart is your IP, not the model.

Key concepts:

Data quality, IP, differentiation.

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3.3~40 min

🦾 Agentic & the Intent Architecture

When to use an agent, when a workflow is enough — and why intent is what really matters.

What it is:

A system that reasons, uses tools, and completes tasks, not just answers.

Why learn:

Separate hype from real architecture.

Key concepts:

Reasoning, tools, task completion.

What it is:

A workflow is a vending machine (always the same); an agent is a slot machine (nondeterministic).

Why learn:

The analogy helps you decide when you need predictability.

Key concepts:

Deterministic, nondeterministic, predictability.

What it is:

Deterministic task = inexpensive workflow; ambiguous task that requires reasoning = agent.

Why learn:

Avoids paying a lot for something unstable when a simple workflow will do.

Key concepts:

Cost, ambiguity, choice of tool.

What it is:

You design the context, rules, goals, and validation—the AI carries out your intent.

Why learn:

It's what remains human and is most valued.

Key concepts:

Rules, goals, validation.

What it is:

Without you watching, an agent’s mistake goes straight to the customer.

Why learn:

The more autonomy, the more fail-proof the system needs to be.

Key concepts:

Human-in-the-loop, failure, safeguard.

What it is:

Solve it more cheaply and safely without AI when AI doesn't add value.

Why learn:

More impressive than putting AI everywhere — it shows judgment.

Key concepts:

Judgment, simplicity, value for money.

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3.4~40 min

🤵 Build Your Jarvis: Always-On Partners

From triggered by you to self-triggering: systems that run quietly in the background.

What it is:

An always-on partner that notices things and acts before you even ask.

Why learn:

It's the pyramid's destination — AI in service of your routine.

Key concepts:

Always-on, proactive, a partner.

What it is:

Map predictable triggers: email X arrives, every Monday, a new lead in the CRM.

Why learn:

Every predictable trigger is a candidate for automation.

Key concepts:

Trigger, pattern, automation.

What it is:

The real leverage is what runs while you sleep, not what you launch.

Why learn:

Gets you out of the bottleneck—the system works without you being there.

Key concepts:

Manual trigger, automatic trigger, leverage.

What it is:

Without you in the loop, the system needs to be fail-safe and thoroughly tested.

Why learn:

Autonomy without safeguards puts your reputation at risk.

Key concepts:

Fail-safe, test, safe limit.

What it is:

The ones who win don’t have 100 tools: they run cheaply and do real work.

Why learn:

Simplicity that delivers beats complexity that impresses.

Key concepts:

Background work, lean process, real results.

What it is:

The course wrap-up: context + intent + an agent at the service of YOUR profession.

Why learn:

Aim for the partner who amplifies your potential, not the replacement that erases you.

Key concepts:

Partnership, synthesis, a protected career.

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