PTENES
TRACK 2

🛰️ Research & Analysis

Research without getting lost, detect what is still a weak signal, and turn raw information into coherent vision. They are families 02 (Research and Discovery) and 03 (Analysis and Synthesis).

By the end of the track, you’ll lead everything from a quick scan (/scan) to triangulated deep research (/deepresearch) — and turn findings into models, causes, and explicit trade-offs.

2
Modules
16
Topics
~2h30
Duration
Intermediate
Level
0%
0 of 16
starting question /scan /discover /gaps /trends /deepresearch Synthesis with declared gaps

Scan broadly first (/scan), dig deeper where it matters (/deepresearch), and state what’s missing (/gaps).

Course roadmap

Detailed content

2.1~75 min

🛰️ Research and discovery

The 10 commands in family 02 — structured investigation, scanning, discovery, and trend analysis.

What it is:

Research with defined questions, evidence gathering, synthesis of findings, and a conclusion that identifies gaps and next steps.

Why learn:

It’s the default command for any new topic — it replaces ten scattered searches with a process.

Key concepts:

research question · evidence · stated gap.

What it is:

Expands sources, triangulates evidence, compares interpretations, and documents relevant conflicts between them.

Why learn:

High-stakes decisions call for paid depth: triangulation is what separates research from informed opinion.

Key concepts:

triangulation · documented conflict · depth cost.

What it is:

Searches broadly for emerging signals, players, solutions, and developments without diving too deep too soon.

Why learn:

Avoids the classic mistake of digging deep in the wrong place because the first hypothesis seemed promising.

Key concepts:

breadth before depth · signal · candidate for a deep dive.

What it is:

Look for patterns, adjacencies, combinations, and underexplored areas that conventional search doesn't reveal.

Why learn:

Competitive advantage lies in what’s obvious to few—discovering combinations is a skill you can train.

Key concepts:

adjacency · unusual combination · whitespace.

What it is:

Identifies missing questions, necessary data, risks, exceptions, and overlooked opportunities.

Why learn:

The question nobody asked is often worth more than everyone else’s answers combined.

Key concepts:

missing question · exception · overlooked opportunity.

What it is:

/trends distinguishes fads, sustained growth, emerging signals, and structural change; /signals looks for early clues that anticipate change.

Why learn:

Betting on a fad as if it were a structural shift is the costliest strategy mistake.

Key concepts:

trend taxonomy · weak signal · time horizon.

What it is:

Projects alternative future scenarios to test the robustness of plans and bets.

Why learn:

A plan that only works in the optimistic scenario isn't a plan — it's wishful thinking.

Key concepts:

scenario · key uncertainty · robustness test.

What it is:

/benchmark compares performance against market benchmarks; /landscape maps the full ecosystem of players, forces, and moves.

Why learn:

Without a map of the landscape, you're competing against your own assumptions about the competition.

Key concepts:

reference · ecosystem · relative position.

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2.2~75 min

🧪 Analysis and synthesis

The 10 commands in family 03 — breaking things down, modeling, separating cause from correlation, and simplifying without losing the essence.

What it is:

Breaks the problem into analyzable parts using an explicit method.

Why learn:

A poorly decomposed problem produces a well-written answer to the wrong question.

Key concepts:

decomposition · explicit method · subproblem.

What it is:

Integrates multiple findings into a coherent view, keeping conflicts visible instead of dissolving them into an average.

Why learn:

Poor synthesis erases exactly the information that mattered: the differences between sources.

Key concepts:

integration · tension preserved · single view.

What it is:

Builds an explanatory model of how the system being studied works—variables, relationships, and dynamics.

Why learn:

A good model predicts what happens when you change a variable; a list of facts predicts nothing.

Key concepts:

variable · proposed causal relationship · predictive power.

What it is:

Creates a reusable structure for analyzing cases in the same family (dimensions, axes, criteria).

Why learn:

Framework turns one-off analysis into a permanent team capability.

Key concepts:

dimension · axis · analytical reuse.

What it is:

Separates correlation from causation, proposes causal mechanisms, and tests alternative explanations.

Why learn:

Acting on correlation without a causal mechanism is a gamble—with a company’s budget.

Key concepts:

mechanism · confounding factor · rival explanation.

What it is:

Tracks consequences of consequences—the second-order effects that arrive late and hit harder.

Why learn:

Every incentive creates a counterincentive; anyone who ignores second-order effects is surprised by them.

Key concepts:

indirect effect · delay · feedback.

What it is:

/tradeoffs spells out what you gain and give up with each option; /constraints maps the real constraints (time, money, regulation, people).

Why learn:

A proposal without a stated tradeoff hides the cost somewhere—usually in the future.

Key concepts:

concession · hard constraint · possible boundary.

What it is:

/leverage finds the points where little effort produces disproportionate change; /simplify reduces complexity while preserving the essential function.

Why learn:

Simplification is the most elegant way to improve performance—and the most overlooked.

Key concepts:

leverage point · essential function · deliberate cut.

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