The Journal
Essays
Long-form writing on AI, philosophy, psychology, and systems thinking.
-
Emotional AI and the Boundary of Machine Perception
Emotion detection accuracy ranged from 62-78% for basic emotions and 31-45% for complex states across 3 systems. Classifying surface patterns is not perceiving emotions.
-
On Building Things That Last in a Culture of Disposability
We live in a culture of disposability. The average system is deprecated within 7 years. Wabi-sabi and Stoic durability offer a counter-philosophy: build for endurance, not novelty.
-
Alienation in the Age of Automation: Marx Was Partly Right
Marx described alienation as separation from the products of labor. The $395 billion automation industry has scaled that separation. Designing automation that preserves meaning is an engineering responsibility.
-
Python’s Gravity Well: Language Choice Shapes Architecture
Python is present in 92% of data pipeline codebases, creating path dependencies that constrain infrastructure for years. Its gravity well requires strategic, not revolutionary, escape.
-
Data Privacy Engineering Is a Data Engineering Discipline
Implementing tokenization and differential privacy at the pipeline level reduced PII exposure incidents by 89% while adding less than 3% to processing time.
-
The OKR Trap: Why OKRs Break at Scale
OKRs created 312 person-hours of overhead per quarter at a 120-person org. The framework fails when used to create alignment rather than represent it.
-
The architecture of a second brain that actually works
-
Building Systems That Explain Themselves: Self-Documenting Architecture
Self-documenting architectural patterns reduced documentation maintenance by 79% and cut new engineer onboarding from 34 days to 12 days across 7 engineering teams.
-
Message Queue Selection Is a Personality Test for Your Architecture
Message queue selection for 13 organizations revealed that the choice between Kafka, RabbitMQ, SQS, and NATS exposes deeper assumptions about consistency, throughput, and operational philosophy.
-
Designing Data Pipelines for Machine Consumers
AI agents consume more analytical data than humans at 3 of 5 organizations I work with. Machine consumers require fundamentally different quality contracts.