PTENES
PATH 1 · 🥉 APPRENTICE LEVEL

🧭 Fundamentals & Setup

Understand the opportunity, learn the Factory’s anatomy, and build your arsenal. By the end of this track, you’ll run your first consulting package—even before you learn how to build one.

3
Modules
18
Topics
~2h
Duration
Basic
Level
🥉 Apprenticeyou are here 🥈 Synthesizer 🥇 Builder 💎 Engineer 👑 Consultant

Learning path map

Detailed content

1.1~40 min

📈 The Opportunity: AI + Consulting Now

Why this is the best time to get started, what AI consulting looks like in practice, and the thesis that guides everything: minimal input, maximum output.

What it is:

Every company needs an AI strategy for 2026, but few know where to start. There's a gap between wanting to act and actually executing.

Why learn:

28,974 people pay for Wharton's AI strategy course alone. Demand is enormous—and those who deliver, not just talk, win the market.

Key concepts:

Window of opportunity · execution vs. intention gap · first-mover advantage.

What it is:

Diagnose where the company is, find where AI creates value, and deliver a concrete plan (roadmap, ROI, governance) that the client can execute.

Why learn:

This is exactly what the Factory automates. Understanding the service inside and out keeps you in control of what the machine produces.

Key concepts:

Diagnosis · value opportunity · actionable deliverable.

What it is:

You enter the company name and description and get 19 deliverables. The effort goes into building the machine, not into each deliverable.

Why learn:

It’s the principle that separates a freelancer from a product. Build once, deliver infinitely.

Key concepts:

Leverage · productization · near-zero marginal cost.

What it is:

Three paths for the same engine: use it in your company, sell it as a service, or productize it as a recurring offer.

Why learn:

Define how you’ll monetize. Jason Liu scaled an AI consulting business from $170/hr to $100k/month in one year by productizing it.

Key concepts:

Internal use · project · retainer · productized offer.

What it is:

Claude Code writes and runs the code. Your job is to direct it: describe what you want, review, and adjust.

Why learn:

Removes the barrier that holds most people back. Non-developers build the entire Factory by asking Claude Code.

Key concepts:

Orchestration · vibe coding · review > write.

What it is:

5 tracks = 5 levels. Each module ends with a practical Mission and gives you a reusable resource (skill, agent, prompt).

Why learn:

You always know where you are and what you’ve gained. Clear progression keeps you moving toward the capstone.

Key concepts:

Levels · Mission with payoff · growing arsenal.

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1.2~40 min

🔧 Anatomy of the Factory

The 19 deliverables, the 3-phase pipeline, and why the result looks like elite consulting. A map of what you'll build.

What it is:

15 Markdown documents + 2 PPTX presentations + 2 Word documents. From the technical inventory to the closing SOW.

Why learn:

Knowing what comes out defines what you can sell. Each item is a deliverable clients pay a premium for.

Key concepts:

Markdown · PPTX · DOCX · executive package.

What it is:

Research (Perplexity) → Synthesis (Gemini, 15 prompts) → Generation (PPTX/DOCX/PNG). Each phase feeds the next.

Why learn:

It’s the course’s backbone. Each learning path explores one part of this pipeline in greater depth until you master the whole thing.

Key concepts:

Pipeline · chained phases · separation of responsibilities.

What it is:

Research gathers current company facts; Synthesis turns facts + frameworks into documents; Generation formats them for delivery.

Why learn:

Understanding the "why" behind each phase helps you avoid using AI as a black box—you know where to intervene and improve.

Key concepts:

Current facts · guided synthesis · professional formatting.

What it is:

The prompts were built using real playbooks from McKinsey, BCG, KPMG, OpenAI, and IBM, distilled into cheat sheets.

Why learn:

The output inherits the rigor of those consultancies. That's what makes the package look (and feel) like elite work.

Key concepts:

Distilled knowledge · borrowed authority · perceived quality.

What it is:

A tour of the files generated for a company: roadmap, ROI, AI policy, deck, and SOW.

Why learn:

Seeing the destination before the journey gives you a quality benchmark and concrete motivation.

Key concepts:

Final deliverable · quality reference · big-picture view.

What it is:

How the 5 tracks connect: knowledge → skills/agents → the factory → the client.

Why learn:

You move through each track knowing which part of the Factory you’re building at that moment.

Key concepts:

Logical sequence · incremental build · capstone.

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1.3~40 min

⚙️ Building your arsenal

Claude Code, accounts and keys (Perplexity + Gemini), clone and run the repo, the build-in-public mindset, and how to control costs. By the end, you’ll run the first package.

What it is:

The development assistant that clones, installs, configures, and runs the Factory based on natural-language instructions.

Why learn:

It’s what makes everything possible without coding. Mastering how to make good requests is the course’s number one skill.

Key concepts:

Natural language · install/run · iterate through conversation.

What it is:

The API that researches the company online in real time. Generate a free key in Settings → API.

Why learn:

It’s what keeps the deliverables up to date—it doesn’t make things up; it finds recent facts about the company.

Key concepts:

API key · live research · .env.

What it is:

Gemini 2.5 Flash generates the documents: affordable and with a huge context window. Key created in Google AI Studio.

Why learn:

It’s the writing engine. Its low cost is what makes it possible to deliver an entire package for less than US$1.

Key concepts:

Gemini 2.5 Flash · large context · low cost.

What it is:

Download the ai-strategy-factory project, run setup, and launch the web interface at localhost:8888.

Why learn:

Ask Claude Code to "clone and run the Factory for me" — and watch it get up and running in minutes.

Key concepts:

git clone · setup.py · webapp localhost.

What it is:

Building in public: share the process, including mistakes (context limits, API, wrong model name).

Why learn:

Builds authority and attracts clients. Showing the actual process connects more than just the polished result.

Key concepts:

Transparency · authority · proof of work.

What it is:

Two research modes: quick (~US$0,05) and deep (~US$0,50). You choose based on your budget.

Why learn:

Controlling costs is what keeps margins high. Documentation is cheap in tokens; split up large requests.

Key concepts:

Quick vs deep · token budget · margin.

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