By a Software Developer with 35 Years of Experience

For most of my career, software development was about building solutions. We certainly relied on third-party products, operating systems, databases, and networking infrastructure, but there was an underlying assumption that the ecosystem itself was relatively stable.

Today, that assumption feels increasingly difficult to make.

Many veteran developers have noticed a troubling trend over the last five to ten years: the technology ecosystem that modern software depends upon appears significantly more fragile than it once was. Services disappear. APIs change unexpectedly. Development tools become bloated and unreliable. Open-source projects are abandoned. Cloud vendors alter pricing models. Documentation deteriorates. Support channels vanish.

It is becoming increasingly difficult to identify where the responsibility lies when something breaks because modern systems are no longer built—they are assembled from countless dependencies maintained by organizations with competing priorities.

The result is an industry that often feels less stable despite possessing more technological capability than at any other point in history.

From Building Systems to Assembling Ecosystems

In the 1990s and early 2000s, most software teams owned a significant portion of their technology stack.

A typical application might depend on:

• An operating system
• A database
• A networking layer
• A handful of commercial libraries
• Today's applications often depend on:
• Hundreds or thousands of open-source packages
• Multiple cloud providers
• Container platforms
• SaaS APIs
• AI services
• Identity providers
• CDN providers
• Analytics services
• Continuous integration platforms
• Browser vendors
• Mobile operating systems
• No individual engineer fully understands the entire stack.
• No single organization controls it.
• Every dependency represents another point of failure.

Even Development Tools Are Becoming Fragile

Perhaps the most surprising development is that the tools used to build software are becoming increasingly unreliable.

• Historically, development tools were expected to be boring.
• Compilers compiled.
• Debuggers debugged.
• Integrated development environments focused on stability and productivity.
• Today, many developers spend a significant portion of their time fighting their tools rather than building software.
• Modern development environments often include:
• Cloud integrations
• Marketplace extensions
• AI assistants
• Telemetry systems
• Package managers
• Continuous update mechanisms
• A simple IDE installation can now contain dozens of interacting subsystems.
• Problems that were once rare have become commonplace:
• Extensions breaking after updates
• Package dependency conflicts
• Build pipelines suddenly failing
• Cloud authentication issues
• AI-generated code introducing hidden defects
• Tool vendors changing licensing models

Even software development itself has become dependent upon external services that engineers do not control.

When the development environment requires an internet connection, cloud authentication, subscription services, AI inference endpoints, and multiple vendor integrations merely to function, reliability naturally declines.

The Post-COVID Effect

The COVID era accelerated digital transformation faster than many organizations could responsibly manage.

Companies rushed to:

• Move workloads to the cloud
• Support remote work
• Reduce staffing costs
• Increase automation
• Expand online services
• Many decisions that would normally have taken years were compressed into months.
• Technical debt accumulated rapidly.
• Processes were bypassed.
• Institutional knowledge was lost through layoffs, resignations, and organizational restructuring.

While remote work itself is not the problem, the rapid disruption created a generation of systems that were optimized for speed rather than long-term maintainability.

Many organizations are still paying the price.

The Rise of Agile Extremism

Agile development originally emerged as a sensible reaction against bureaucratic waterfall methodologies.

Unfortunately, many organizations transformed Agile from a useful framework into an ideology.

The result is what many experienced developers now describe as "feature factory" development.

Success is measured by:

• Story points
• Sprint velocity
• Release frequency
• Burndown charts
• Rather than:
• Reliability
• Maintainability
• Defect rates
• Architectural quality

In some organizations, developers are actively discouraged from investing time in refactoring, documentation, testing, and technical debt reduction because those activities do not produce immediately visible business metrics.

The irony is that many companies are moving faster while simultaneously becoming less productive because they spend increasing amounts of time repairing defects and managing complexity.

AI: Amplifying Both Productivity and Chaos

Artificial intelligence is the newest force reshaping software development.

• AI tools can dramatically increase productivity.
• They can generate boilerplate code, explain unfamiliar APIs, create tests, and accelerate learning.

However, AI also introduces a new challenge.

Historically:

• Writing code was expensive.
• Reviewing code was relatively cheap.

Today:

• Writing code is becoming inexpensive.
• Reviewing code remains expensive.
• Organizations can now generate functionality faster than they can properly understand, test, or maintain it.

The long-term implications are still unknown.

What is clear is that AI has increased the rate at which complexity can enter software systems.

The New Fraud Economy

Another major source of instability is the growth of fraud as an industry.

Modern organizations face threats that barely existed at scale twenty years ago:

• Supply chain attacks
• Dependency poisoning
• Fake software packages
• Credential theft
• Deepfake social engineering
• Ransomware
• API abuse
• Account takeover schemes

As fraud grows more sophisticated, vendors respond with increasingly complex security measures.

The result is additional layers of authentication, verification, compliance requirements, monitoring systems, and access controls.

While these measures are necessary, they also increase operational complexity and create more opportunities for failure.

The Political and Regulatory Environment

• Political instability also affects technology.
• Global supply chains have become more volatile.
• Trade disputes affect hardware availability.
• Government regulations continue to evolve.
• Data sovereignty requirements vary across jurisdictions.
• Geopolitical conflicts influence technology investment decisions.

Technology companies increasingly find themselves responding not only to customer demands but also to political pressures, regulatory concerns, activist investors, and public relations campaigns.

This creates uncertainty throughout the ecosystem.

The Oligarchic Technology Landscape

Perhaps the most concerning trend is the concentration of power within a small number of technology companies.

Much of modern computing now depends on a handful of organizations controlling:

• Cloud infrastructure
• Search
• Advertising
• Mobile platforms
• AI services
• Social media
• Software marketplaces

When a small number of companies become gatekeepers, the incentives begin to change.

Historically, customers were often treated as assets to retain.

Today, customers sometimes feel more like products being monetized.

Features increasingly serve:

• Data collection
• Advertising objectives
• Investor expectations
• Market dominance strategies rather than direct customer benefit.

Many users have experienced situations where products become objectively worse while revenues increase.

The frustration is not merely technological.

It is economic.

Customers often have fewer alternatives than they once did.

The Disappearance of Ownership

One of the biggest differences between modern and historical software development is the loss of ownership.

When something failed twenty years ago:

• You could inspect it.
• You could debug it.
• You could patch it.
• You often controlled it.

Today, failures frequently occur within systems owned by someone else.

The problem may originate from:

• A cloud provider
• An API vendor
• An AI platform
• An open-source maintainer
• A browser update
• A package registry
• A CI/CD service

You may have no access to the source code and no ability to fix the issue yourself.

The engineer's role has shifted from builder to orchestrator.

While orchestration provides enormous leverage, it also creates dependence.

A Paradox of Modern Technology

Despite all of these concerns, it is important to recognize that many individual technologies are more capable and reliable than ever before.

• Cloud infrastructure is remarkably resilient.
• Databases scale to extraordinary levels.
• Deployment pipelines are vastly more sophisticated.
• Observability tools provide insights that previous generations could only dream about.

The paradox is that individual components have improved while the overall ecosystem feels more fragile.

The reason is simple.

• Complexity grows faster than reliability.
• Every layer of abstraction creates new opportunities for failure.
• Every dependency introduces risk.
• Every convenience comes with a tradeoff.

Conclusion

• Many veteran developers are not imagining the changes they are observing.
• The industry has undergone a profound transformation.
• Software engineering has evolved from building systems we control to assembling systems we depend upon.
• The productivity gains are undeniable.
• The capabilities are extraordinary.
• But the cost has been a growing fragility that many experienced professionals now feel every day.
• The challenge facing the next generation of engineers is not merely building faster.

It is rediscovering how to build systems that remain understandable, maintainable, and trustworthy in a world increasingly defined by complexity.