Why Everything Feels Broken: The Buffer Economy and How We Built the Information Age Wrong

A Customer Success Manager's Journey to Understanding Civilizational Failure

ANNIE ZNAMIEROWSKI
AUG 21, 2025

I.

For ten years, I spent my days making sure customers didn't quit using software they'd already paid for. As a Customer Success Manager at multiple software companies, I monitored dashboards that tracked how often customers took action, which features they used, and whether they were "healthy" or "at risk."

But the dashboards were just noise. The real skill was seeing patterns they couldn't show—the subtle combination of declining usage, support ticket language, and delayed responses that meant a customer was about to ghost us.

When I spotted these signals, I sprang into action. I scheduled calls, created training materials, coordinated with support, and looped in product teams. I was excellent at it. I could predict failure months before it happened. The software had everything—recorded calls, usage data, support tickets—but none of the intelligence to understand what it meant.

I was that missing intelligence layer.

What I really was, though, was human middleware—a person whose entire professional existence revolved around compensating for software that couldn't ensure its own success. The software we sold promised to make businesses more efficient, but it required me to manually create the conditions that would make customers successful.

This is the paradox of the modern economy: We built sophisticated systems that require armies of people to make them function.

II.

Every office worker knows something is broken. Simple tasks take weeks. Meetings proliferate like invasive species. Everything requires translation between systems that don't talk to each other. We have more technology than ever, yet everything feels slower, more complex, more frustrating.

The problem is architectural. We built the Information Age backwards.

Consider what happens when a customer is about to quit. Your systems capture everything but the data just sits there in silos, meaning nothing. A human has to notice the pattern, understand what it means, and figure out how to fix it. The software tracks everything but understands nothing. The intelligence lives in human heads, not in the system.

Each system is sophisticated in isolation but blind to the whole. So humans become the connective tissue—copying data, translating between systems, manually creating the conditions for success.

This isn't a bug. It's the fundamental design pattern of modern organizations. We built every system to interface with humans instead of with other systems. Then we wondered why everything requires so much human coordination.

The numbers tell the story. Microsoft researchers found that knowledge workers spend 2.5 hours daily in meetings, most deemed unproductive. McKinsey found that 28% of the workweek goes to managing email.

This goes deeper than David Graeber's "bullshit jobs" thesis. These aren't just meaningless jobs created to keep people busy—they're jobs that exist because we built our technological infrastructure backwards. Every Customer Success Manager, every Integration Specialist, every Revenue Operations Analyst is compensating for a specific architectural failure.

It’s as if we invented the automobile and hired millions to push them.

III.

To understand how we got here, we need to understand the three ages of economic leverage.

The Industrial Age was about physical leverage. One person with a machine could do the work of hundreds. The value was obvious and immediate—a mechanical loom produced more cloth, a steam engine moved more goods.

The Information Age promised cognitive leverage. One person with a computer could process information that would take thousands of humans to manage. Databases replaced filing cabinets. Spreadsheets replaced ledgers. Email replaced memos.

But then something strange happened. Instead of reducing the need for human coordination, information systems increased it. Every new system required specialists to operate it, managers to coordinate it, and experts to translate between it and other systems. We automated the storage and processing of information but not the understanding of it.

This created what I'm calling the Buffer Economy—an entire economy of humans serving as the intelligence layer that systems lack. These aren't jobs that create value; they're jobs that prevent value from not existing.

The Buffer Economy manifests everywhere. In healthcare, nurses spend extensive time on documentation and coordination. In banking, relationship managers translate between what customers need and what systems can do. In manufacturing, production planners mediate between demand signals and production systems.

The global professional services market—essentially, humans helping other humans use technology—exceeds $300 billion. Systems integration approaches $500 billion globally. These aren't industries that create new value. They're industries that prevent value destruction caused by architectural failures.

IV.

The rise of Customer Success as a profession is the perfect case study. In 2005, it barely existed. Today, it's one of the fastest-growing professions in America, expanding 10-15% annually.

Why? Because Software-as-a-Service companies discovered that customers couldn't successfully use their software without human help. The software itself couldn't ensure success—it could only provide tools and generate data. Humans had to interpret that data, understand what would make customers successful, and manually create those conditions.

I lived this reality every day. I knew which feature combinations predicted retention. I recognized usage patterns that preceded churn. I understood the unwritten prerequisites for success. But this expertise remained trapped in my head and in my spreadsheets, never becoming systematic capability.

Every SaaS company now employs the same elaborate compensation structure: Customer Success Managers to prevent churn, Implementation Consultants to ensure deployment, Solution Engineers to translate needs into capabilities, Technical Account Managers for strategic relationships, and Revenue Operations teams to coordinate between all of them.

The core problem is software cannot create value without specific user actions, but has no agency to cause those actions. It just sits there, value-inert, waiting. So we hire humans to be the agency it lacks.

Here's the uncomfortable truth: most "tech" companies aren't tech companies at all. They're digital factories running industrial-age physics with subscription models. If you need a Customer Success department, you don't have network effects—where each new user makes the product more valuable for all other users—or emergent effects—where the system improves automatically from usage itself. You have a linear business pretending to be exponential.

V.

The Buffer Economy is accelerating. As we build more systems, we need more human buffers between them. Every new tool that promises to boost productivity actually creates more coordination overhead. We're heading toward an economy where most people exist to compensate for system failures rather than create new value.

This is why productivity growth has stalled despite technological advancement. We're not becoming more productive; we're just adding more human middleware. It's why wages stagnate while work intensifies—the work isn't valuable creation but essential compensation.

The psychological toll is severe. Every day, I translated between systems, attended coordination meetings, and manually created conditions that should have been automatic. I wasn't building anything. I was just preventing things from breaking. The exhaustion wasn't from hard work—it was from the Sisyphean nature of it. Every customer I saved would need saving again.

No wonder work feels meaningless. No wonder burnout is epidemic. No wonder everyone senses something is fundamentally wrong.

VI.

The solution isn't automation—it's architecture. We need systems that think, not tools that wait.

Start with connection. Amazon's 2002 API mandate proved the first principle: systems can talk directly to each other without human translation. Every team had to expose their functionality through APIs, eliminating the human copy-paste between systems. Estonia's X-Road took this further, connecting every government agency. These were breakthroughs—they eliminated human data-pushing.

But they only solved half the problem. APIs let systems share data, but the systems still can't create value autonomously. They still need humans to interpret patterns, make decisions, and force users to take the right actions. Connection without intelligence just moves the bottleneck.

The real breakthrough is emergent intelligence. When I identify that customers who don't integrate within 30 days have an 30% churn rate, that insight shouldn't stay trapped in my head. It should become permanent systematic capability. The system should automatically create conditions for integration, not just report on failure.

Netflix and Spotify cracked this second layer. They don't just have APIs—they have intelligence about what creates user success built into the system itself. Every user makes the system smarter for everyone else. They don't track what you watch—they learn what captivates humans and actively create those conditions.

This is the profound difference: Current software is a sophisticated diary that requires a therapist to interpret it. What we need is software that IS the therapy. Software that doesn't need a Customer Success department because success is encoded into its DNA.

The shift is from Human-in-the-Loop—where human judgment guides execution—to Intelligence-in-the-System—where systems create their own success conditions and humans handle only true exceptions. My expertise compounds rather than dissipates.

This could transform every domain where humans currently serve as middleware. In agriculture, sensors could communicate directly with equipment, supply chains, and markets—optimizing planting and harvesting without human coordination. In healthcare, diagnostic systems could communicate with treatment protocols and insurance platforms—creating care pathways without administrative burden. In energy, consumption could communicate with generation and storage—balancing grids without human intervention.

Not by automating the middleware, but by eliminating the need for it entirely. Systems that don't just connect but genuinely think—recognizing patterns, creating conditions, evolving from use.

VII.

Not all middleware is waste. Some coordination genuinely requires human judgment that can't be encoded: relationship capital from years of trust-building, context-switching between radically different worldviews, ethical judgment in unprecedented situations, creative problem-solving when systems hit edge cases.

The tragedy isn't that these roles exist—it's that we can't distinguish between necessary human judgment and unnecessary human middleware. In my Customer Success role, maybe 20% required genuine human insight. The other 80% was compensating for systematic failures. But because we bundle them together, we can't eliminate the waste without losing the value.

As I write this, the world is gripped by AI fever. Companies are rushing to implement large language models, chatbots, and AI agents. But look at what we're actually building: AI Customer Success Managers. AI to predict churn, to send follow-up emails, to coordinate between systems that don't talk to each other.

We're training these AIs on data generated by our broken processes, teaching them to navigate the same systemic failures I navigated manually. We're automating the Buffer Economy rather than eliminating it.

The hottest AI startups are building tools to summarize meetings that shouldn't exist, write emails between systems that should directly communicate, generate documentation for processes that should be self-evident. This is garbage in, garbage out at civilizational scale—training AI on the exhaust fumes of coordination overhead, then using that AI to generate more coordination.

We're not eliminating buffer jobs; we're creating new categories of them. Prompt Engineers translate between human intent and AI capability. AI Integration Specialists connect AI systems that don't talk to each other. AI Success Managers ensure companies successfully use their AI that was supposed to ensure success. We've added another layer to the stack of failures.

The alternative would require asking different questions. Instead of "How can AI make this process better?" we could ask "Why does this process exist?" But many AI investments come from companies whose business models depend on managing complexity rather than eliminating it.

We're using humanity's most powerful technology to amplify our architectural failures. We could be curing the disease. Instead, we're automating it.

VIII.

We stand at an inflection point. The Buffer Economy is approaching unsustainability. We cannot continue adding human middleware at the current rate. The coordination overhead will eventually exceed value creation.

Let's be honest about what fixing this means: millions of middle-class jobs would evaporate. Not gradually, but suddenly. The Buffer Economy employs a significant percentage of the developed world's knowledge workers. These aren't just jobs—they're identities, mortgages, college funds.

Any CEO who genuinely eliminated their Buffer Economy would face a revolt—not from workers, but from other executives whose power depends on coordination complexity. The board would see chaos, not clarity. The stock market would punish the temporary disruption without waiting for the long-term efficiency.

This is why change will come from new organizations, not transformation of existing ones. Startups can build without buffers from day one. But existing organizations? They're trapped. The Buffer Economy isn't just their inefficiency—it's their structure, their culture, their entire operating system.

IX.

The best companies of the next decade won't just reduce their reliance on human middleware. They'll distinguish between the 20% of human judgment that creates value and the 80% that compensates for failure.

They'll encode intelligence into systems rather than trapping it in heads—building networks where every user's experience makes the system smarter for everyone else.

The tragedy is civilizational. We're wasting our brightest minds on coordination instead of creation, their potential consumed by architectural failure rather than unleashed by it.

The Information Age isn't over—it's just built wrong. The future doesn't require more human coordination. It requires systems that can coordinate themselves. When we stop forcing humans to be middleware, we can start being human again.

Everyone else will remain digital factories, mistaking coordination for creation, adding more buffers to prevent collapse.

Feeling broken isn’t natural. It’s architectural—and architecture can be changed.