Six months ago, Olivia Lipkin’s managers started referring to her as “Olivia/ChatGPT” in Slack messages. She was a 25-year-old copywriter at a San Francisco tech startup, good at her job, valued by clients. By April 2023, her anxieties proved warranted. She was fired.
Olivia’s story isn’t unique. AI has already replaced the cogs. It’s coming for the linchpins next. But here’s what I’ve discovered through years of building companies and advising marketers: we humans possess something AI cannot replicate. We are syntropy creators.
Syntropy is a transdisciplinary principle describing the universal tendency toward order, complexity, structure, and organization. It stands as the direct counterpart to entropy — the Second Law of Thermodynamics that describes the tendency of isolated systems toward disorder, randomness, and energy dissipation.
The term derives from Greek roots: *syn-* (σύν) meaning “together” and *-tropy* (from *tropos*, τρόπος) meaning “a turn” or “tendency.” Literally: “turning together” or converging tendency. This etymology reveals something profound — the word itself describes the very process it represents: convergence toward order.
While entropy describes how things fall apart, syntropy describes how they come together. While entropy explains death and decay, syntropy explains life and growth. While AI accelerates entropy through content generation, humans create syntropy through meaning generation.
The modern scientific formulation emerged in 1941 when Italian mathematician Luigi Fantappiè made a startling discovery. Working on equations that unite quantum mechanics and special relativity, he found two sets of solutions for wave phenomena:
His insight was revolutionary: these converging waves exhibited the exact properties of living systems — energy concentration, increasing differentiation, formation of complex structures. He named the principle governing these waves “syntropy” and declared it the essence of life itself.
The mathematical relationship is elegantly simple:
1 = Syntropy + Entropy
This equation shows entropy and syntropy as complementary polarities of a single reality. Where entropy dominates, things dissipate. Where syntropy dominates, they organize.
Biology is syntropy’s primary domain. Living systems are the quintessential examples of matter defying entropy, maintaining and increasing internal order in a universe trending toward disorder.
Consider metabolism’s dual nature:
Life exists in the dynamic balance between these opposing flows. We consume order (food, oxygen) and export disorder (heat, waste) while maintaining our internal syntropy.
Nobel laureate Albert Szent-Györgyi, who discovered Vitamin C, proposed in 1974 that syntropy should replace “negentropy” to describe life’s ordering principle. He noted the fundamental difference between machines that wear out with use and organisms that improve through activity. “The living organism is characterized by an innate drive toward self-perfection,” he wrote — a perfect description of syntropy in action.
Fast forward to today. Large language models don’t “think” — they guess. As Stephen Wolfram explains, they’re probability engines predicting the next word based on patterns in training data. Each iteration loses fidelity. Insight decays into cliché. Truth dissolves into plausible-sounding nonsense.
Research reveals AI models trained on AI-generated content exhibit “model collapse” — a death spiral where systems become increasingly disordered. Without fresh human input, they enter an entropic cascade:
MIT’s Media Lab Project NANDA found that 95% of enterprise AI initiatives show zero measurable return. The reason? Not technical failure but lack of syntropy — clear purpose, aligned strategy, human curation.
Poor data quality already costs the global economy $3.1 trillion annually. Large enterprises lose an average of $12.9 million each year to entropy in the form of wasted hours, bad decisions, missed opportunities, and brand erosion. AI is accelerating this entropy at an unprecedented scale.
In my work building companies and advising B2B SaaS leaders, I’ve seen the workforce bifurcating into two categories:
Suumit Shah, CEO of Dukaan, fired 23 of 25 customer support staff after building an AI chatbot. Resolution time dropped from 2 hours to 3 minutes. Costs fell 85%. IBM automated 94% of routine HR tasks with “AskHR,” eliminating 200 positions while achieving $3.5 billion in productivity gains.
These aren’t cautionary tales — they’re previews of the acceleration ahead. The question isn’t whether AI will replace certain jobs. It’s which humans will become irreplaceable by becoming syntropy creators.
If noise is entropy at work, then signal is syntropy made visible. Signal isn’t just the absence of noise — it’s the presence of intentional, coherent, audience-aligned meaning.
Creating signal requires answering two fundamental questions:
These questions force coherence. They prevent entropy. They’re the operational constraints that transform random information into meaningful communication.
AI can detect signal — it cannot create it. While AI remixes existing information into endless variations, each generation slightly less sharp than the last, humans inject experience, judgment, and meaning into systems that would otherwise decay into chaos.
The relationship between humans and AI follows a three-phase cycle:
Phase 1: Signal Extraction
AI processes human-created data, surfacing hidden patterns at superhuman speed. A 3–5% improvement in transcription accuracy (using human transcribers over machines) can transform insight quality from customer interviews.
Phase 2: Signal Dilution
Without fresh input, AI remixes its own outputs. Each generation loses fidelity. Innovation gives way to imitation. Your competitor’s strategy deck starts looking identical to yours.
Phase 3: Signal Injection
Humans introduce novel experiences, observations, and judgments that don’t exist in training data. The cycle resets, stronger than before.
At Kalungi, our B2B SaaS marketing agency, we faced this reality in Q3 2024. Competitors used AI to copy our website, presenting incomplete variations at lower prices. We had to evolve or die.
I’ve now seen three types of agencies emerge:
Content Mills: Using AI to churn out more work at lower costs, racing to the bottom.
Craft Purists: Clinging to handcrafted work — noble but unsustainable as clients see cheaper alternatives.
Syntropy Agencies: Understanding their value isn’t production but human insight generation. They embed themselves in client operations not to bill hours but to observe dynamics that never appear in briefs. They attend customer calls, sit in sales meetings, walk factory floors — wherever real human experience happens.
These Syntropy Agencies command premium pricing because they offer something genuinely scarce: unique human insights that improve AI outputs in ways competitors cannot replicate.
I’ve identified these specific human capabilities that position us as irreplaceable syntropy creators — not coincidentally all beginning with ‘C’:
Here’s a technique I learned from Dutch creativity consultant Jan Willem van den Brandhof that AI cannot replicate:
Set a timer for 7 minutes. Write 100 potential taglines. The impossibility triggers panic. Your brain floods with norepinephrine and dopamine. Your prefrontal cortex — that careful editor keeping you in patterns — partially shuts down.
Around idea 35, when you’ve exhausted the obvious, your brain stops reaching for cached responses and starts creating genuine connections. By idea 80, something shifts. Real syntropy emerges.
AI feels no pressure generating 100 variations. No cortisol floods its circuits. It simply remixes without the productive panic that forces human brains into genuine creation.
Another powerful method is the Why/How Ladder for customer interviews:
This extracts signal that would never appear in surveys or AI-generated research.
Swiss farmer-researcher Ernst Götsch transformed the concept into practice through “syntropic agriculture.” His approach turned 1,200 acres of degraded Brazilian land into productive agroforests without external inputs.
The methodology mirrors syntropy principles:
This isn’t metaphor — it’s syntropy in action. Agriculture becomes regenerative rather than extractive. Order increases rather than decreases. The system improves through operation.
Traditional economics assumes scarcity and competition. Syntropic economics recognizes abundance through cooperation. Consider two business models:
- Bills hours for output
- Competes on price
- Creates commoditized deliverables
- Margins compress over time
- Prices for clarity creation
- Competes on unique insights
- Builds proprietary knowledge
- Margins expand as insights compound
The Syntropy Economy values order creation over volume production. Organizations that master syntropy generation command premium pricing because they offer what’s truly scarce: the ability to transform entropy into energy, confusion into clarity, noise into signal.
Fantappiè’s theory offers a profound model of consciousness. We experience reality through two streams:
1. The Entropic Stream: Information from the past, processed as memories, governed by causality. The push of what has been.
2. The Syntropic Stream: Information from the future, experienced as emotions and intuition, guided by attractors. The pull of what could be.
Free will emerges at the intersection — our capacity to navigate these opposing forces and choose which path to follow. This isn’t philosophical speculation. Researchers like Antonella Vannini have demonstrated pre-stimulus heart rate responses, suggesting consciousness operates through syntropically-mediated anticipation.
Mental health maps onto this framework:
In 2016, I joined cohort #7 of Seth Godin’s altMBA. For four weeks, I shipped daily and received feedback that stung. The most important lesson wasn’t in the curriculum. It was watching Seth prepare professionals for a world that didn’t yet exist.
Seth Godin taught us that being a linchpin — creating unique value through creativity, empathy, and initiative — would make us indispensable. But AI has learned to mimic linchpin behaviors. We must evolve further.
Becoming a syntropy creator isn’t optional. In a world where AI will generate 70% of all content by 2027, syntropy isn’t just valuable — it’s existential for every knowledge worker and the industries that rely on them.
The choice is stark: become an entropy processor and face obsolescence, or become a syntropy creator and become irreplaceable.
My book “Syntropy” emerged from watching talented professionals become “Olivia/ChatGPT” — reduced to their replaceability. But also from seeing others transcend that fate by understanding their irreplaceable role.
AI hasn’t made human insight obsolete. It’s made it scarce. And scarcity drives value.
While others worry about being replaced, focus on becoming irreplaceable. Generate the signal that feeds the system. Create the experiences that become tomorrow’s training data. Build the judgment that separates insight from noise.
The intelligence mirror is powerful. But someone still needs to stand in front of it.
That someone is you.
I learned the hard way that being right too early feels exactly like being wrong. In 2023, we started asking at Kalungi what impact AI would have. We knew transformation was coming. We didn’t know it would accelerate this fast.
Here’s a simple framework to begin your syntropy journey:
1. Write down what you’re worried about. Clarity reduces anxiety.
2. List ten things you could do about those worries. Agency emerges from action.
3. Pick one and start**. Movement beats meditation.
Every day, ask yourself: Did I create signal or noise today? Did I add to entropy or syntropy? Did I process information or generate meaning?
The marketers who thrive in the next decade won’t be those who resist change or surrender to it. They’ll be those who transcend it — who use AI as leverage to amplify human judgment, experience, and creativity.
That’s your opportunity and your responsibility. The tools are here. The frameworks are proven. The path is clear.
What remains is your choice.