beauty is the residue of understanding; value is the residue of care.¹

2025 marks ten years since I started programming. This essay is a set of reflections on the idea of craft in building software.

I remember reading Peter Norvig’s “Teach Yourself Programming in Ten Years” in college and wondering what that would feel like. A decade in, the future of software feels both more optimistic and more dichotomous than ever. People say the era of personal software is here.

The most satisfying change I made this year was a deletion. No new feature, no clever abstraction—just removing a fragile branch and replacing it with a simpler path. The system got quieter. Fewer pages, fewer edge cases. My laptop fans stopped screaming during local runs. Craft felt like subtraction, and it looked like calm.

I didn’t start there. I started fast: small apps, large confidence, adrenaline as process. Cleverness looked like progress because it moved the graph. I shipped by duct tape and heroics and felt invincible until the bill arrived. Hidden costs collected in corners: flaky tests that failed only when I needed them most, names that hid intent, dead code that still shaped behavior. Speed without comprehension is deferred pain; code that can’t be reasoned about slows everyone—especially our future selves.

So I slowed down on purpose. Practice became a loop I could trust: name, test, refactor, delete. I wrote to think, and tests became letters to future me—little contracts to lean on when memory failed. I shipped small and reversible. I looked for seams, split behavior cleanly, and defined boundaries by their promises instead of their internals. I measured twice: dry runs, feature flags, shadow writes. The thrill of novelty gave way to the steadiness of boring tech. Minimal machinery with maximal clarity wasn’t decoration; it was how speed becomes sustainable.

With time, the job felt less like heroics and more like stewardship. I cared more about rollback plans than release notes. I deleted more than I added. I wrote runbooks first and optimized feedback loops: fast tests, fast CI, tight local iterations. I tried to make change cheap. Resilience stopped being a slide and became a sensibility—design for failure paths first, prefer reversible moves, assume partial outages, keep the blast radius small. Observability wasn’t an afterthought or a dashboard; it became the way the system spoke—a language for telling us how it felt and where it hurt.

Deliberation wasn’t slowness; it was the discipline that let us go fast without breaking ourselves. The craft move wasn’t to wait; it was to stage risk, to isolate it, to run in shadow, to toggle, to keep pull requests small enough to reason about. “Slow is smooth; smooth is fast” survived contact with reality. Feature flags mattered more than clever dependency injection. A good migration plan mattered more than a new pattern. Deleting an abstraction shipped more value than polishing it.

Quality turned out not to be a vibe but a set of small constraints that compound. Use names that tell the story; if the name feels vague, the design probably is. Keep surfaces small—fewer methods, narrower contracts, less to hold in your head. Prefer simple data and composition over deep inheritance. Make invariants explicit and write tests that freeze them in place. Choose boring tech that keeps edges sharp. Default to deletion; if it isn’t pulling its weight, remove it. Beauty emerges, if it’s going to, as residue of those choices—the clarity that remains when you stop trying to be clever and start trying to be understood.

Under pressure, craft shows itself. Incidents are joinery tests—where boundaries meet and fail. The systems I’m proud of degrade gracefully; they tell us what’s wrong; they can be steered back without heroics. Chaos drills become muscle memory, not theater. We write down rollback steps. We keep blast radii small. We practice recovery. Calm systems keep teams humane.

And then there’s the problem itself. A beautiful solution to the wrong problem is a perfect answer to a question nobody asked. Ten years taught me to front‑load definition: talk to users, trace the workflow, cut scope, say no. Ship less but truer. When the problem is crisp, execution becomes honest—minimal parts, maximal insight. Outcomes over output. Users over tickets. Conversation over ceremony.

Along the way I kept a handful of rules: measure twice; stage risk; keep changes reversible. Name before you design; if you can’t name it, don’t build it. Treat tests as contracts—start with invariants, catch edge cases early. Delete bravely; simplicity is a feature. Prefer boring tech; speed lives in feedback loops.

I’m still unsure about a few things: when to embrace novelty for long‑term leverage versus when to double down on the boring, proven path; how to measure craft without turning it into theater; how to align incentives so deletion and risk‑reduction are celebrated instead of quietly undervalued. But I’m clearer about what I’m aiming at: systems that feel quiet and teams that feel calm—places where beauty and value show up not because we chased them, but because we practiced deliberate understanding and care long enough for their residue to remain.