Step-by-Step Teaching Guide

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STEP 1: Understand the Core Problem Being Solved

The Problem with Traditional Legal Work

Before AI, legal teams faced a fundamental constraint:

Time Available  <<  Work That Needs Doing

Real-world example from the article:

• A junior lawyer is asked to review hundreds of contracts overnight
• They can only realistically review a fraction of them
• Important risks in unreviewed contracts go undetected

Why This Matters

Key Takeaway

The scarcest resource in legal work is not knowledge — it is time and capacity

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STEP 2: Understand What "Agentic AI" Means

Definition First

Before understanding Legora, you need to understand the term "agentic"

Traditional AI Tool:

Human asks question → AI answers → Human acts

Agentic AI:

Human sets goal → AI plans steps → AI executes autonomously
→ AI reviews its own output → AI delivers result → Human reviews

Think of It Like This

Imagine hiring an intern vs. hiring an autonomous contractor:

• An intern waits for your instructions at every step
• An autonomous contractor takes a brief, works independently, and returns with completed work

Agentic AI behaves like the autonomous contractor

Why "Operating System" Language?

Legora calls itself an "agentic operating system" — this is intentional language

Just as Windows runs programs on a computer, Legora runs legal workflows powered by AI agents

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STEP 3: Learn the Three Layers of Transformation

The article demonstrates AI transformation happening at three distinct levels

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Layer 1 — Speed (Doing the Same Work Faster)

Example: NDA Review

Before Legora:

• Lawyers manually read every NDA
• Consumed ~20% of legal team capacity
• Slow, repetitive, low-value work

After Legora:

• AI takes a first pass on every incoming NDA
• Flags terms outside acceptable parameters
• Lawyer only reviews flagged exceptions
• Now consumes under 1% of capacity

The Math:

20% capacity → under 1% capacity = 95%+ reduction

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Layer 2 — Scope (Doing Work That Was Previously Impossible)

Example: Due Diligence in M&A

Traditional approach:

1,000 contracts available for review
Time/cost allows review of → 50 contracts
950 contracts = unreviewed risk

With Legora's Tabular Review:

1,000 contracts available for review
AI reviews all 1,000 in minutes
Lawyer reviews AI-surfaced findings across all 1,000

This is not just faster — it is fundamentally broader

Risks that previously hid in unreviewed contracts are now surfaced

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Layer 3 — Quality (Better Output, Not Just Faster Output)

This is the most counterintuitive insight in the article

Most people assume:

Faster = cutting corners = lower quality

But the article argues:

Faster + Broader = Higher Quality

Why?

• More contracts reviewed = fewer missed risks
• Lawyers freed from repetitive work = more mental energy for judgment
• AI handles pattern recognition = humans handle strategic thinking

"AI doesn't just make you faster. It also increases quality." — Emma Kadri Bergström, General Counsel

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STEP 4: Understand the Human-AI Collaboration Model

The Key Principle: AI Augments, Humans Judge

The article never suggests AI replaces lawyers. Instead:

AI handles:                    Humans handle:
─────────────────              ─────────────────
Pattern recognition            Strategic judgment
Volume processing              Client relationships
First-pass review              Final decisions
Log searching                  Interpretation
Document comparison            Negotiation

The 9.5 Hours Example

One Fortune 100 customer returned 9.5 hours per lawyer per week

Ask yourself: What does a lawyer do with 9.5 extra hours?

• Deeper client strategy
• More complex negotiations
• Business development
• Higher-value advisory work

The goal is not to eliminate lawyer time — it is to redirect it

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STEP 5: Learn How AI Transforms Internal Operations (Not Just Products)

A Critical Insight Often Missed

Legora doesn't just sell AI — they use AI internally

This creates two parallel transformations:

The Compounding Effect

AI improves the product
↓
Better product attracts more customers
↓
More customers generate more feedback
↓
AI helps engineers process feedback faster
↓
Faster iteration improves the product further
↓
(cycle repeats)

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STEP 6: Understand the Leadership Lessons as Principles

The article provides five leadership principles — learn these as a framework

Principle 1: Lead by Using

Fact: When 75%+ of leaders actively use Legora
Result: Median usage across the org is 3× higher

Lesson: Adoption follows leadership behavior, not mandates

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Principle 2: Start with the Problem

Wrong approach: "We have AI, what can we do with it?"
Right approach: "What do people need to accomplish? Where can AI help?"

Lesson: Technology serves workflow — not the other way around

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Principle 3: Build a Network of Champions

Early adopters → Internal advocates → Sustained adoption

Lesson: Peer influence drives deeper organizational change than top-down directives

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Principle 4: Be Ready to Rebuild

Model improves → Previous assumptions become outdated → Rebuild

Lesson: In fast-moving AI environments, flexibility beats optimization

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Principle 5: Design for Trust

Legal work requires: accuracy, transparency, accountability
Therefore AI in legal must have: evaluation, testing, explainability

Lesson: In high-stakes domains, trust is a design requirement, not an afterthought

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STEP 7: Understand the Future Direction

Two Parallel Advances Coming

Advance 1 — Longer Context, Greater Autonomy

Current: AI reviews hundreds of contracts
Future: AI runs overnight due diligence on millions of pages
        → Lawyer arrives to completed analysis in the morning

Advance 2 — Real-Time Collaboration

Current: Human gives task → AI returns result (asynchronous)
Future: Human and AI work back-and-forth in real time (synchronous)

The Bigger Shift: From Bottleneck to Business Partner

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Summary: The Complete Mental Model

PROBLEM
Legal work is time-constrained → valuable work doesn't get done

SOLUTION
Agentic AI operating system → handles volume, pattern, repetition

THREE TRANSFORMATIONS
1. Speed    → Same work, dramatically faster
2. Scope    → Work previously impossible, now possible
3. Quality  → Broader coverage = fewer missed risks

HUMAN ROLE
Shifts from: execution of routine tasks
Shifts to:   judgment, strategy, high-value decisions

RESULT
Legal teams become business partners, not bottlenecks

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Quick Self-Assessment Questions

Test your understanding:

1. What is the difference between a traditional AI tool and an agentic AI system?

2. Why does reviewing MORE contracts lead to HIGHER quality outcomes?

3. What did Legora's legal team do with the time saved from NDA review?

4. Why does the CTO say the roadmap must be reconsidered every two weeks?

5. In your own words, explain why "AI increases quality" seems counterintuitive but is actually logical

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Core Learning Achieved: You now understand how agentic AI systems transform professional workflows not just by accelerating existing tasks, but by expanding what is possible — and how the human role evolves from execution to judgment in an AI-augmented environment.