Core Concept

Business Leverage

The strategic distinction between working IN your business (executing tasks) versus working ON your business (designing systems). Master both types of leverage to transform from operator to architect.

ON the Business
Design systems that scale
IN the Business
Execute with AI agents
Compound Effect
Multiply your impact

The Core Insight

Most founders and product leaders are trapped. They spend 90% of their time working in the business—writing code, answering support tickets, creating content, managing tasks. They become the bottleneck of their own organization.

The Leverage Equation

Impact = (System Quality) × (Execution Capacity)
System Quality (ON)

How well your processes are designed. Improved through Value Stream Mapping, systems thinking, and strategic work.

Execution Capacity (IN)

How much work gets done within your systems. Multiplied through AI agents, automation, and delegation.

The breakthrough insight: you need both. A perfectly designed system with no execution capacity produces nothing. Massive execution capacity within a broken system just creates waste faster. The magic happens when you optimize both simultaneously.

Working ON vs IN: A Comparison

🔧

Working IN the Business

Operational work. The tasks that keep the lights on. Essential, but doesn't scale.

Writing code

Each feature requires your time

Answering support tickets

One question at a time

Creating content

Manual production each time

Running meetings

Synchronous time investment

Characteristic: Linear returns. 2x effort = 2x output.
🏗️

Working ON the Business

Strategic work. Designing systems that produce results without you.

Value stream mapping

Design efficient workflows once

Creating documentation

Enable others/AI to execute

Building templates

Reusable frameworks

Designing processes

Systems that self-correct

Characteristic: Exponential returns. Work done once, used forever.

The Time Audit Question

Track your time for one week. What percentage is spent ON vs IN?

90% IN / 10% ON
Operator mode (common)
60% IN / 40% ON
Transitioning
30% IN / 70% ON
Architect mode (goal)

Value Stream Mapping: Leverage ON the Business

Value Stream Mapping is the quintessential "working ON the business" activity. When you step back and visualize your entire workflow—from customer need to delivered value—you're not doing the work. You're redesigning how work happens.

Why VSM Creates Strategic Leverage

See the Whole System

Most people are stuck in their corner of the workflow. VSM forces you to see end-to-end, revealing bottlenecks invisible from any single position.

Identify Waste

The 8 wastes (waiting, motion, defects, etc.) are only visible from above. You can't eliminate waste you can't see.

Design Future State

Once you see current reality, you can architect an improved future. This is pure "ON the business" work.

One-Time Investment, Ongoing Returns

A well-designed value stream keeps delivering value long after the mapping session ends.

The Strategic Leverage Multiplier

🗺️
Before: Ad-hoc improvements

Teams make random optimizations based on gut feel. No way to know if changes help.

📊
After: Targeted improvements with measurable impact

Know exactly where the bottleneck is. Measure before/after. Every improvement compounds.

AI Agents: Leverage IN the Business

AI agents represent a paradigm shift in operational leverage. For the first time, you can multiply execution capacity without proportional cost increases. But here's the key insight: AI agents are only as good as the systems they operate within.

The AI Agent Execution Model

🎯

Clear Inputs

Well-defined triggers, contexts, and data. Comes from good system design.

🤖

AI Processing

Agents follow your designed workflows, making decisions within defined boundaries.

Quality Outputs

Consistent results that feed into the next step of your value stream.

💬

Customer Support Agents

AI handles tier-1 support, answers FAQs, routes complex issues to humans.

Leverage: 1 person + AI = capacity of 5-10 support reps
📝

Content Creation Agents

AI drafts content from templates, follows brand guidelines, prepares for human review.

Leverage: First draft in minutes vs hours, human focuses on polish
🔍

Research Synthesis Agents

AI processes interview transcripts, surfaces patterns, generates initial insights.

Leverage: 10 interviews synthesized in hours vs days
💻

Code Generation Agents

AI writes boilerplate, implements specs, handles routine coding tasks.

Leverage: Developer focuses on architecture, AI handles implementation

The Critical Dependency

AI agents amplify whatever system they're plugged into. This is why "ON the business" work must come first:

AI in a Bad System

Produces garbage faster. Amplifies waste. Creates new problems at scale.

AI in a Good System

Multiplies throughput. Maintains quality. Frees humans for creative work.

The Compound Effect: ON × IN

The real magic happens when you combine strategic leverage (ON) with operational leverage (IN). This is multiplicative, not additive.

The Leverage Matrix

Low Execution
(Manual Only)
High Execution
(AI Agents)
Poor Systems
(No VSM)
Struggling

Waste everywhere, no capacity

Scaling Chaos

AI produces waste faster

Good Systems
(VSM Optimized)
Efficient but Limited

Good systems, capacity constrained

Maximum Leverage

Optimized systems + scaled execution

Real Example: Research to Backlog

Before (No Leverage)
  • • 18 days from research to backlog
  • • PM manually synthesizes every interview
  • • PRDs written from scratch each time
  • • Tasks manually entered into Linear
After (ON × IN)
  • • 4 days from research to backlog
  • • AI synthesizes interviews immediately
  • • PRDs generated from templates + insights
  • • Tasks auto-created via Linear API
4.5x faster with same team

The Implementation Framework

1

Audit Your Time (Week 1)

Track every task for one week. Categorize: is this ON or IN work?

Key Questions:
  • • What percentage of time is spent IN vs ON?
  • • Which IN tasks are most repetitive?
  • • What ON work keeps getting postponed?
  • • Where am I the bottleneck?
2

Map One Value Stream (Week 2-3)

Choose your most painful workflow. Apply Value Stream Mapping.

Steps:
  • • Document current state with all wait times
  • • Identify the 8 types of waste
  • • Design future state (where can AI help?)
  • • Calculate potential lead time reduction
3

Deploy One AI Agent (Week 4-5)

Pick the highest-leverage point in your mapped value stream. Deploy an AI agent there.

Good First Agents:
  • • Research synthesis (interview → insights)
  • • First draft generation (brief → draft)
  • • Support triage (ticket → category + suggested response)
  • • Code scaffolding (spec → boilerplate)
4

Measure and Iterate (Ongoing)

Track the metrics that matter. Continuously improve both system design and AI capabilities.

Key Metrics:
  • • Lead time (total time from input to output)
  • • % of time spent ON vs IN the business
  • • AI agent success rate (outputs used without modification)
  • • Personal capacity freed for strategic work

The Architect Mindset

The shift from operator to architect isn't just about tools or processes. It's a fundamental mindset change in how you approach your work.

Operator Questions

"How do I get this task done?"
"What's next on my todo list?"
"How do I work faster?"
"Can I handle this myself?"

Architect Questions

"How do I design a system that handles this?"
"What system produces the right work automatically?"
"How do I eliminate the need for this work?"
"What would make this task obsolete?"

The Daily Practice

Every morning, before diving into execution, spend 15 minutes asking:

  1. 1. What task will I do today that I'll have to do again next week?
  2. 2. Can I document/template/automate it instead?
  3. 3. If I had an AI agent, what would I have it do?
  4. 4. What's stopping me from deploying that agent now?

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