PTENES
PATH 2 · 🥈 SYNTHESIZER LEVEL

📚 Knowledge Synthesis

What makes the package feel like elite consulting isn't the AI—it's the knowledge you feed into it. Here, you learn the frameworks worth their weight in gold, compress huge PDFs into cheat sheets, and build the consultant's brain that powers the Factory.

3
Modules
18
Topics
~2h
Duration
Interm.
Level
PDF · 46 pages chunk ~10k tk chunk ~10k tk chunk ~10k tk synthesis Gemini 2.5 Flash 1 page compresses

Learning path map

Detailed content

2.1~40 min

📊 The Frameworks Worth Their Weight in Gold

The six frameworks the Factory uses under the hood: maturity, quick wins, build vs. buy, ROI, roadmap, and governance. They make the output look like—and deliver the value of—BCG and KPMG work.

What it is:

The BCG maturity curve: Passive → Aware → Active → Operational → Transformational. You place the company at one of the 5 stages and score 7 dimensions from 1 to 5.

Why learn:

It’s the first deliverable: it shows where the company is today. Without it, everything else (the roadmap, ROI) floats in midair.

Key concepts:

BCG maturity curve · 5 stages · 7 dimensions · readiness radar.

What it is:

AI initiatives that run in <60 days, cost <US$50k, carry low risk, and have demonstrable ROI. Prioritized in an effort × impact matrix.

Why learn:

They’re the quick proof of value that unlocks budget. This is the framework for your Mission in this module.

Key concepts:

Low effort × high impact · <60 days · demonstrable ROI · momentum.

What it is:

A weighted decision matrix (time, 3-year cost, customization, internal capacity, maintenance, risk) that indicates whether the company should build or buy for each use case.

Why learn:

It’s the million-dollar question in every AI project. A clear framework prevents decisions based on guesswork.

Key concepts:

Weighted matrix · 3-year TCO · vendor comparison · vendor lock-in.

What it is:

Four sources of value (efficiency, revenue, risk reduction, strategic value) become simple ROI, payback, and 3-year NPV with a 10% discount rate.

Why learn:

It’s the deliverable that convinces the finance team. Numbers speak louder than a pretty slide.

Key concepts:

4 sources of value · simple ROI · payback · NPV · sensitivity analysis.

What it is:

Five time-based phases: Foundation (30) → Quick Wins (60) → Scale (90) → Optimize (180) → Transform (360), each with goals, milestones, and owners.

Why learn:

It’s what turns "use AI" into a plan the client opens on Monday and starts executing.

Key concepts:

5 phases · checkbox milestones · owner per activity · leading vs. lagging indicators.

What it is:

Data classification (Public → Restricted), what can and cannot become AI training/input/output, roles (CDO, stewards), and compliance (LGPD, GDPR, CCPA).

Why learn:

It’s the deliverable that puts legal and the board at ease. Without governance, no pilot makes it to production.

Key concepts:

Data classification · acceptable use policy · data stewards · LGPD/GDPR.

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2.2~40 min

🗜️ Lazy RAG: huge PDF → cheat sheet

McKinsey, BCG, and KPMG playbooks are 28–46 pages long—they blow past any context limit. The solution is lazy RAG: split them into chunks, summarize each one, and create an ultra-compressed cheat sheet.

What it is:

Dumping an entire 46-page PDF into Claude Code exceeds the context limit—and fills the window with useless buzzwords. You need the valuable information, not the volume.

Why learn:

Understanding the bottleneck is what justifies the technique. Without that, you waste expensive context on junk.

Key concepts:

Context limit · signal vs. noise · token cost · value density.

What it is:

Extract the text from the PDF, count tokens with the tokenizer, and split it into chunks of ~10.000 tokens. Each chunk fits comfortably in an API call.

Why learn:

It’s the heart of lazy RAG: process one part at a time instead of everything at once.

Key concepts:

10k-token chunk · tokenizer (cl100k_base) · PyMuPDF · process in parts.

What it is:

A prompt that asks only for frameworks, statistics, actionable insights, citations, and terms — preserving numbers and cutting buzzwords. A block with no value gets the [MINIMAL_CONTENT] label.

Why learn:

The prompt is where the cheat sheet's quality comes from. A bad prompt = a generic, useless summary.

Key concepts:

Structured extraction · preserve numbers · cut buzzwords · empty content marker.

What it is:

The model that synthesizes: huge context, rock-bottom price, with exponential retries and delays between calls to respect the rate limit.

Why learn:

It’s what makes it possible to distill an entire PDF library for pennies. The right model in the right place.

Key concepts:

Gemini 2.5 Flash · low cost · exponential retry · rate limit.

What it is:

Combine the synthesized blocks in order, discard those marked as empty, and generate a single Markdown file with a header, sections, and a "check against the original" footer.

Why learn:

It’s the output that goes to Claude Code. Well put together, it becomes a reusable reference; poorly put together, it becomes noise.

Key concepts:

Concatenate by index · discard empty values · header + footer · final Markdown.

What it is:

The actual script: reads a folder of PDFs, saves progress in progress.json, skips blocks already completed and supports --dry-run e --single-pdf.

Why learn:

Just ask Claude Code to run it. Resuming ensures you don’t pay twice for the same block.

Key concepts:

ProgressTracker · resumable · --dry-run · skip completed blocks.

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2.3~40 min

🧠 Your consultant brain

Standalone cheat sheets aren't enough—they become powerful when organized into a knowledge base that Claude Code can consult on demand. Here you build your personal consultant library: curated, versioned, and ready to inject.

What it is:

Generating text is cheap; space in the context window is expensive. Distilling means trading volume for density: every token that goes in needs to earn its relevance.

Why learn:

It’s the mindset that separates those who fill the context with junk from those who inject only gold. It defines the quality of everything.

Key concepts:

Distillation · information density · context efficiency · signal vs. volume.

What it is:

Choose authoritative sources: the free guides McKinsey, BCG, KPMG, OpenAI, and IBM publish to showcase their expertise. You get elite knowledge for free.

Why learn:

The quality of the foundation depends on the quality of the source. Garbage in, garbage out—choose authoritative sources.

Key concepts:

Authoritative sources · free guides · curation · borrowed authority.

What it is:

The fixed structure of a good cheat sheet: concepts & frameworks, critical statistics, actionable insights, quotes, and terminology. Always easy to scan.

Why learn:

Consistent structure is what makes the foundation searchable and injectable. Each leaf becomes a modular piece.

Key concepts:

Fixed sections · scannability · bolded term · 1 page per source.

What it is:

Organize the folder conhecimento/ by topic, date each cheat sheet, record the source, and version it with git. The knowledge base evolves without becoming a mess.

Why learn:

Curated knowledge is an asset that grows in value over time—if you don’t lose control of it.

Key concepts:

Folders by topic · date + source · version with git · knowledge base as an asset.

What it is:

Instead of dumping the entire knowledge base, you pull only the cheat sheet relevant to the current task. Lazy RAG: the human does the retrieval on demand.

Why learn:

It’s what keeps the window lean and the response sharp. Right context > more context.

Key concepts:

Lazy RAG · manual retrieval · on demand · lean context window.

What it is:

The folder conhecimento/ consolidated: several curated cheat sheets that power the entire Factory and go with you from project to project.

Why learn:

It’s the brain that makes the Factory sound like an elite consulting firm. Built once, used with every client.

Key concepts:

Reusable library · feeds the Factory · portable asset · compounding advantage.

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