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TRACK 1

🟢 Fundamentals

Why researching with five perspectives beats a single prompt. Here you’ll understand the STORM method, learn about the five expert lenses, and discover the three pillars that make the result reliable: subagents, a contradiction map, and source verification.

3
Modules
18
Topics
~2h
Duration
Basic
Level
Track progress0%
0 of 18 topics
Topic single 🛠️ practical 🎓 academic 🔍 skeptic 💰 economist 🏛️ historian Briefing multiple perspectives

Each lens researches the same topic from a different angle (cyan), and everything converges into a single briefing. It's the mind map for Track 1.

Course path map

Detailed content

1.1~40 min

🎯 The single-prompt problem

Why a single prompt leaves gaps in research — and what the STORM method does differently.

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What it is:

STORM is a research method that brings together multiple perspectives on a topic instead of relying on a single angle. Here, it becomes the skill storm-research for Claude Code.

Why learn:

This is the foundation of everything: understanding the core idea explains why the pipeline has five lenses and a verification phase.

Key concepts:

Multiple perspectives · synthesis · source verification · HTML briefing.

What it is:

A single prompt carries a single frame—and everything that frame fails to see is left out of the research.

Why learn:

Recognizing the blind spot is what motivates asking for more than one perspective.

Key concepts:

Framing bias · coverage · source diversity.

What it is:

Deep research launches hundreds of generic agents; STORM uses a few deliberate, verified perspectives.

Why learn:

Shows that more agents don’t mean better research—structure matters more than volume.

Key concepts:

Cost · rate limit · structure vs. volume.

What it is:

A skill is a set of instructions (a master prompt) that Claude reads and executes when you invoke it.

Why learn:

Understanding that "skill = prompt" demystifies installation and shows that you can edit it.

Key concepts:

SKILL.md · frontmatter · invocation · self-contained.

What it is:

A standalone HTML file with a summary, findings ranked by reliability, and verified references.

Why learn:

Knowing what the deliverable looks like helps you judge whether STORM is what you need.

Key concepts:

Autonomous · ranked · verified · actionable.

What it is:

STORM shines on contested, multi-perspective topics; for a simple factual query, it’s overkill.

Why learn:

Using the right tool saves time and agent costs.

Key concepts:

Contested topic · cost · fit.

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1.2~45 min

🔭 The five expert lenses

Professional, academic, skeptic, economist, and historian — and why each one finds a hole the others miss.

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What it is:

The lens of someone who works with the topic every day: real-world friction, what works, and what tends to be overlooked.

Why learn:

Reveals the gap between theory and operational practice.

Key concepts:

Friction · case study · operational reality.

What it is:

The lens that cares about peer-reviewed studies and effect size, not anecdotes.

Why learn:

Grounds claims in rigorous evidence and flags where it is weak.

Key concepts:

Peer review · effect size · preprint.

What it is:

The lens that builds the strongest counterargument—rigorous, not contrarian for sport.

Why learn:

Exposes what supporters conveniently ignore.

Key concepts:

Refutation · failure · contradictory data.

What it is:

The lens that tracks revenue, valuation, funding, and incentives behind the narrative.

Why learn:

Shows who profits from the hype and how money shapes research.

Key concepts:

Incentive · unit economics · market size.

What it is:

The lens that looks for genuine historical parallels and what we learned from how they played out.

Why learn:

Set expectations: who won, who lost, and what stabilized.

Key concepts:

Cycle · analogy · pattern.

What it is:

Each lens has distinct priorities, so it sees what the others ignore. Together, they cover more.

Why learn:

This is the principle that justifies the entire panel.

Key concepts:

Complementary coverage · diversity · blind spot.

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1.3~45 min

🧱 Subagents, contradictions, and verification

The three pillars that make the result reliable—and why verification is what sets STORM apart from an ordinary report.

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What it is:

In STORM, the main session talks to five subagents — which don’t talk to one another (unlike an agent team).

Why learn:

Defines the pipeline’s cost and behavior.

Key concepts:

Subagent · orchestration · agent team.

What it is:

The five lenses were written by the same author; agreement among them is a strong hypothesis, not independent proof.

Why learn:

This is the method’s most important intellectual safeguard.

Key concepts:

Author bias · convergence · honesty.

What it is:

The step where direct conflicts between lenses are named and the stronger evidence is weighed.

Why learn:

This is the raw material for the findings and the “supports/challenges” chips.

Key concepts:

Direct conflict · evidence hierarchy.

What it is:

What all the lenses confirm (likely finding) and what none addressed (the missing sixth lens).

Why learn:

Feeds the "boundary question" and shows the panel’s limits.

Key concepts:

Universal agreement · blind spot · sixth lens.

What it is:

Rate by source quality: peer-reviewed causal evidence > official data > single research study > analogy > preprint.

Why learn:

Reliability isn’t subjective confidence—it’s the strength of the evidence.

Key concepts:

Hierarchy · causal · official data.

What it is:

Check every citation against the actual primary source, correcting, downgrading, or removing anything that doesn’t hold up.

Why learn:

Without this phase, it isn’t a STORM report.

Key concepts:

Primary source · verdict · verification banner.

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← Course home Track 2: Practice →