Welcome to my blog! Here you'll find my thoughts on software development, technology trends, and creative problem-solving approaches. I write about everything from technical deep-dives to strategic insights in the tech world.
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Timing and momentum matter more than talent, but there's a third term missing: resonance. This dynamics layer extends the Quest Engine with the physics of coupling (how your sustained force meets the world's readiness to receive it).
Archimedes asked for a long enough lever to move the world. Engineering is the discipline of building those levers (correctly sized stairs, daily practice, scaffolded learning, and iterative cycles) so any wall becomes climbable.
Exploring a secular approach to life's meaning through three forces: Discovery (the search for understanding), Play (the drive to engage), and Joy (the renewal of purpose). These aren't abstract ideals — they're diagnostic tools for a life that matters.
When working with AI agents, craftsmanship, judgment, and taste are what humans contribute. Craftsmanship builds expertise through exploration, judgment determines what you control versus delegate, and taste guides what's worth building. These map to searching, being driven, and renewal in the Quest Engine.
Tracing the phrase 'Stay Hungry. Stay Foolish.' from Stewart Brand's Whole Earth Catalog through Steve Jobs' Stanford address to the mindset of permanent, joyful pursuit that drives self-advancement and connects to Quest Engine.
The Objective Function sits above all operational cycles and defines what success means. Through Search, Drive, and Renew, it ensures humans and agents continuously align on what 'better' looks like, what each can control, and whether they're still optimizing for the right thing.
Quest Engine is a methodology built on three recursive action steps that help you solve problems at any scale. Through Searching, Being Driven, and Renewing (you compound your capability continuously). AI coding agents amplify these natural processes as tools that multiply your leverage.
Why effort tracking (where is my time going?) needs to be separate from work tracking (what am I building?) and how centralizing effort in one tool provides visibility that scattered work-tracking systems can't.
How worklogs transformed my workflow with AI coding agents (capturing context across sessions, using GitHub Issues as a backend, and turning structured logs into an agentic work queue).
Reflecting on my experience using AI coding tools since Claude Opus 4.5, contrasting Rust and scripting language development, and insights on multi-agent workflows.