When Capacity Changes, Boundaries Become Architecture
During my third round of chemo, a feature flag failure exposed how tunnel vision, unshared load, and poor boundaries can export work strain into the people closest to us.
Posts
Moral Adulthood in a Tribal Age
I am wired for binary thinking, and tribalism comes naturally to me. This is my attempt to choose a better standard: sacred people, fallible ideas, and restrained power.
The Synergy Trap: Why Human-AI Collaboration Needs Better Goals
Everyone promises human-AI “synergy” will make 1+1=3. Six months later, you’re managing more overhead than you saved. Maybe synergy isn’t the goal we should be chasing.
Faithful in Babylon
Jim Amos warned about AI agents and I responded with defiance. Then I realized we were both right—and both incomplete without each other.
You're Not a Victim of AI—You're Just Making Excuses
A response to the ‘AI agents are a betrayal’ narrative that challenges developers to own their agency instead of waiting for permission to adapt.
Emotional Version Control: The AI Feature We Need But Don't Have Yet
I was coding across two different codebases while the Minnesota situation occupied my brain. Cognitive dissonance: historical conservative voter watching behavior I can’t support. Social media amplify
What Freud and Maslow Can Teach Us About AI
Maximizing AI effectiveness requires understanding the difference between how humans and AI internalize feedback. That understanding comes not from more code—it comes from deeper study of what makes us human.
Edge AI Isn't a Placement Decision. It's a Capability Unlock.
Cloud AI keeps tightening the rules. Edge and private data center restore control, privacy, and durable context where the work happens.
Agentic AI for Anyone: From Assistant to Orchestrator
Moving beyond chat-based AI to orchestrated multi-agent systems. Free playbook and starter kit. No gatekeeping.
Feedback Loops Are Essential—But Not the Way You Think
Our instincts for human collaboration mislead us when working with AI. Understanding the difference is where effectiveness is won or lost.