The Real Problems Engineering Leaders Face

After 20-30 years, large-scale software becomes digital archaeology. People change, but legacy systems remain. Here's what we hear from engineering leaders every day.

The Universal Challenge: Software Engineering is Like Gardening

Code must be tended day in and day out. Under business pressure to deliver features, the essential tending of software falls by the wayside, creating compound technical debt that eventually threatens business continuity.

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20-30 Year Lifecycle
Software outlives its creators
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Knowledge Dependency
Critical systems depend on 1-2 SMEs
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Documentation Rot
Documentation rots faster than food
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Quality vs. Speed
"Ship now, refactor later" (never)
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CTO / Engineering Leader

The Legacy Code Trap
"We have 15-year-old applications that generate $50M+ in revenue, but adding a simple feature takes 6 months instead of 6 weeks. My best engineers spend 80% of their time fighting technical debt instead of building competitive advantages."
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Engineering Manager

The Velocity Erosion
"My team delivered 20 features per quarter 2 years ago. Now we deliver 8, with the same team size. Every sprint, 60% of our capacity goes to 'technical maintenance' that I can't explain to product managers."
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Systems Architect

The Documentation Decay
"I'm responsible for system architecture across 50+ applications, but the documentation was last updated 3 years ago. Architecture reviews become archaeology expeditions."
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Senior Developer

The Context Switch Penalty
"I spend more time trying to understand what code does than actually writing new code. I waste 3 hours just figuring out how to make a 5-line change safely. This isn't programming; it's digital archaeology."

Why LLMs Alone Create Technical Debt, Not Sustainable Solutions

LLMs without proper software engineering foundations create a dangerous illusion of productivity that often leads to technical debt, unmaintainable code, and system failures.

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Code Quality and Architecture

Snippet-level thinking

LLMs excel at generating code snippets but lack understanding of broader system architecture. Without engineering principles, developers end up with:

  • Tightly coupled components that become impossible to modify
  • No separation of concerns, making debugging nightmarish
  • Inconsistent coding patterns across the codebase
  • Missing error handling and edge case considerations
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Testing and Reliability

Function-level focus

LLMs can write individual functions but don't inherently understand comprehensive testing strategies. Engineers who rely solely on LLM output often skip:

  • Unit tests, integration tests, and end-to-end testing
  • Test-driven development practices
  • Performance testing and load considerations
  • Security vulnerability testing
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System Design Blindness

Missing the big picture

LLMs operate at the code level, not the system level. Without engineering expertise, you miss:

  • Scalability planning and bottleneck identification
  • Database design and query optimization
  • API design principles and versioning strategies
  • Monitoring, logging, and observability requirements
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Technical Debt Accumulation

The hidden cost

The most insidious problem is that LLM-generated code often works initially but creates massive technical debt:

  • Quick fixes instead of proper solutions
  • Copy-paste solutions without understanding context
  • No consideration for future maintenance or feature additions
  • Inconsistent data models and business logic
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Security and Performance Gaps

Critical vulnerabilities

LLMs don't inherently prioritize security or performance best practices:

  • SQL injection vulnerabilities and other security flaws
  • Memory leaks and inefficient algorithms
  • Missing input validation and sanitization
  • Poor resource management
Learn More: Why LLM Alone Will Not Help