Why Systems Fail #
Anything that requires someone who is already very busy to spend time on something where the gains don’t appear worthwhile is likely to fail.
Most systems don’t fail because of a single catastrophic error. They fail because complexity outpaces cognition.
As Richard I. Cook noted in How Complex Systems Fail:
High-risk environments rarely collapse from a single error. Instead, many small factors accrue until the complexity that individuals must manage exceeds their ability.
The Hidden Cost of Poor Cognitive Design #
Modern platforms often treat developers as end users — but they’re not designing for how people actually think and work.
Instead of supporting decision-making under uncertainty, systems add friction by:
- Hiding critical information
- Requiring excessive context switching
- Failing to surface what truly matters
Teams become overwhelmed, coordination costs rise, and decisions are made with incomplete or ambiguous understanding.
This is where Developer Experience (DX) becomes more than usability — it becomes cognitive scaffolding.
Developer Experience as Cognitive scaffolding #
Observability is the process through which one develops the ability to ask meaningful questions, get useful answers, and act effectively on what you learn.
– Observability is a Team Sport
Developer Experience should be designed to support human cognition.
This means:
- Shifting salience before addressing load — help teams notice what matters first
- Supporting relevance realization — filter noise, highlight actionable signals
- Enabling inference about cause and effect — so teams can make sense of hidden variables
When done right, DX becomes the bridge between infrastructure and intention — turning tools into instruments for intelligent action.
Balancing Tensions: Reliability, Integrity, and Relevance #
No system exists in isolation. Every platform must balance competing priorities:
- Reliability: Ensuring stability and safety
- Integrity: Maintaining consistency and correctness
- Relevance: Aligning work with business goals
These aren’t trade-offs to resolve — they’re dimensions of fitness that evolve over time. By balancing them intentionally, we allow models to adapt, improving alignment between perception, context, and action.
From Platform Engineering Book, Camille Fournier:
The next stage in removing our production training wheels as an industry is to tear down the fence between SRE and Product Engineering, and make rational investments in reliability as a mindset, based on specific needs.
Toward Win-Win #
Win-win doesn’t mean everyone gets exactly what they want — it means:
- Teams operate with shared intent
- Decisions are made with reliable context
- Trade-offs are transparent and intentional
Platforms must evolve from infrastructure enablers to intelligence layers — supporting not just execution, but the thinking that makes execution possible.
Let’s build systems that think with us, not ahead of us.