January 20, 2026
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About

I write independent analysis on modern technology and software development with a mechanism-first lens. The goal is not to pick sides in tool wars. The goal is to explain what a system actually does, what it makes easy, what it makes hard, and what it quietly punishes.

Most technology debates are framed as binaries: this vs that, right vs wrong, best vs worst. Real systems don’t behave that way. Every design is a bundle of constraints. Every constraint creates a cost model. That cost model shows up later as failure modes, team friction, maintenance load, and user outcomes. This blog exists to keep the discussion anchored to that reality.

Why this site exists

I wanted a space that treats nuance as the default. Not “both sides” as a posture, but tradeoffs as the underlying structure of engineering. A framework can be ergonomic and still hide costs. A pattern can be popular and still be a poor fit for a given constraint set. A “best practice” can be context-dependent to the point of being harmful when applied blindly.

So the writing here aims to do three things consistently:

  • Name the invariant a tool or pattern is trying to preserve.
  • Identify the constraint that forces the shape of the solution.
  • Make the tradeoff explicit, including where the approach fails.

Mission

The mission is to publish clear, high-signal explanations and references that help readers make informed decisions about the technologies they use and the systems they build.

That means:

  • Prefer mental models over surface-level API knowledge.
  • Treat implementation details as a cost model, not trivia.
  • Make constraints and failure modes part of the main narrative, not footnotes.
  • Write in a way that is readable to non-specialists without diluting technical correctness.

Author

I’m Caleb Cannon. I’m not writing from a “finished” identity like software engineer or frontend developer. I’m writing as a systems-oriented technical analyst: someone who learns by decomposing tools into invariants, constraints, and tradeoffs, then rebuilding a clearer decision rule from what’s left.

A recurring theme in how I think about systems: define boundaries by what’s explicitly prohibited or constrained, not by an ever-growing list of allowed moves. The benefit is adaptability. If the constraints are clear, the system can evolve without renegotiating expectations on every edge case.

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