Compound Thinking: From Factorio Logic to Multi-Variable Systems Optimization
I’ve been fascinated lately by different approaches to exponential improvement versus linear growth. Most people think additively - do more of X to get more of Y. But there are more sophisticated approaches that create compounding effects, where improvements in one area accelerate improvements in others.
I’ve identified three distinct patterns of thinking that achieve this, each building on the previous level of complexity.
Factorio Thinking: The Automation Mindset
Factorio Thinking comes from the game Factorio, where you build increasingly complex automated factories. The core principles translate perfectly to real-world optimization:
- Automate today what you did yesterday
- Automate tomorrow what you do today
- Always think the meta of the current task
- End up increasing complexity and capacity exponentially through system building
What I find compelling about this mindset is how it forces you to constantly step back and ask: “What am I doing repeatedly that could be systematized?” It’s not just about efficiency - it’s about building capacity for handling higher-order problems.
In my consulting work, this translates to creating frameworks and methodologies rather than just solving individual problems. Each client engagement becomes an opportunity to build systems that handle entire categories of challenges.
Clicker Thinking: Resource Ratio Optimization
Clicker Thinking comes from incremental games where you optimize resource generation rates. The key insights:
- Install agents to do what you do (delegation and automation)
- Increase impact/resource ratio as fast as possible, not just impact
- Move to next generation of agents/systems to increase the rate of ratio improvement
This differs from Factorio thinking in its focus on ratio optimization rather than pure automation. It’s about constantly asking: “How can I get more output per unit of input?” rather than just “How can I automate this?”
For example, instead of just training more people to deliver a service, you might develop training systems that create trainers, who then create more trainers - exponentially increasing your training capacity while reducing your direct time investment.
Single-Variable Compound Thinking: Classic Compounding
This is the most familiar form - where one variable builds on itself over time:
Financial Compounding: Interest from this year stacks with principal from last year, creating more compound interest next year. Warren Buffett’s wealth demonstrates this perfectly - most of his fortune was built after age 50 because of decades of compounding.
Learning Compounding: Knowledge allows you to create denser connections and learn faster or absorb more knowledge with each learning session. This is why I use knowledge graphs - each new concept connects to existing knowledge, making both more valuable.
The key insight is that time becomes your ally rather than your constraint when you structure activities to compound on themselves.
Multi-Variable Compound Thinking: Systems Reinforcement
This is where it gets really interesting - working on several variables that have positive functions on each other. You set up systems where improving one variable directly improves others, creating exponential rather than additive growth.
Example 1: Money-Knowledge Compound Loop
Variables: Increasing money (sales) and increasing knowledge (learning)
System Design:
- Use money to access premium learning opportunities (paid training, elite programs)
- Select learning with credentials that can increase sales
- Prioritize fields that increase earning potential (financial intelligence, high-value domains like banking, defense, executive education)
The result: money buys better learning, which increases earning capacity, which funds even better learning opportunities. Each cycle amplifies the next.
Example 2: Data-Platform-User Compound Loop
Variables: Data quality, platform value, user base
System Design:
- More data → more intelligent platform features
- More intelligent platform → more user referrals
- More users → more data generation
This creates a virtuous cycle where each element reinforces the others exponentially.
The Limiting Variable Principle
In multi-variable compound thinking, the key is identifying and addressing limiting variables - the constraints that prevent the compound loops from accelerating.
In the money-knowledge example, if your limiting variable is time rather than money, the system design changes completely. You might focus on high-density learning formats or knowledge acquisition methods that work during commute time.
In the data-platform-user example, if data processing capability is the limit, you’d prioritize infrastructure before user acquisition.
Connection to Broader Systems
This thinking connects to several frameworks I’ve been developing:
ECC Method: Multi-variable compound thinking applied to organizational transformation - where breaking one silo enables breaking others more easily, creating compound organizational intelligence.
Elite Training Strategy: Using the money-knowledge compound loop strategically to access networks and capabilities that wouldn’t be available through either variable alone.
Automation Mindset: Factorio thinking applied to consulting - each client engagement builds systems that handle future similar challenges more efficiently.
Implementation Challenges
The sophistication of these approaches also creates implementation challenges:
Complexity Management: Multi-variable systems can become too complex to manage effectively. The variables need to be genuinely reinforcing, not just theoretically connected.
Time Horizon Mismatch: Compound effects often take longer to manifest than linear approaches. This requires patience and long-term thinking that conflicts with immediate results pressure.
Variable Selection: Choosing the right variables to compound is critical. Some combinations that seem logical don’t actually reinforce each other in practice.
Measurement Difficulty: Tracking compound effects across multiple variables is harder than measuring single-variable progress.
From Personal to Organizational Application
What excites me most is how these principles scale from personal optimization to organizational transformation. Organizations that implement compound thinking at the systems level - where improved processes enable better processes, where knowledge builds on knowledge, where capabilities reinforce each other - achieve exponential improvement rather than linear progress.
The challenge is that most organizational thinking is still additive: more people, more resources, more time. Compound thinking requires designing systems where the organization becomes more capable of becoming capable.
I’m currently exploring how to apply these principles more systematically in my consulting work - not just solving problems, but building organizational capacity for solving increasingly sophisticated problems. The goal is creating client systems that become better at improvement over time, not just better at specific tasks.
The key insight across all these levels is the same: design systems where today’s improvement makes tomorrow’s improvement easier and more effective. Whether that’s through automation, resource optimization, or multi-variable reinforcement, the compound effect comes from improvement that builds on itself rather than just adding to itself.