Context Engineering: The Hidden Art of Building with AI

I've been thinking about something that most developers miss when working with coding agents.

The best programmers aren't those who write the most elegant algorithms. They're the ones who communicate clearly. This truth becomes sharper when building with AI.

The Real Work Happens Before the Code

When a model fails to output what you need, the problem isn't the model. You haven't understood your own requirements deeply enough.

I structure my work around specs—multiple layers of them:

API documentation defines the contracts. Base goals anchor the vision. Coding style maintains consistency. And crucially: no assumptions, no bias. Just clear boundaries.

Then I attach examples. Real ones. The model needs to see what success looks like in your context.

Supply these specs by feature, not all at once. Feed the intelligence what it needs when it needs it.

A Glimpse Into Tomorrow

The software company of the future looks different than today's structure.

Programmers write code specs. Product managers write product specs. Legal teams write legal specs. And someone new emerges: AI engineers who synthesize everything, wielding models as instruments to build the actual product.

This person understands systems. They solve human problems through orchestration rather than implementation.

What About Writing Code?

Coding remains part of engineering. But it's not the end goal—it never was.

Engineering is about understanding systems and solving human problems. The code is simply one expression of that understanding.

When you provide your biome.json and style configurations to the model, you're not just setting preferences. You're encoding years of architectural decisions into a language the model comprehends.

The elegance isn't in the code itself. It's in how clearly you've thought through what needs to exist.

Let Your Specifications Whisper

I don't believe in tutorials that hold your hand through every keystroke. Better to share the philosophy and let capable minds extrapolate.

If you can't write a spec that produces what you envision, you don't understand your vision yet. Keep refining until the path becomes clear.

The future belongs to those who can translate human intention into systematic instruction—whether the executor is human or machine.

Build with clarity. The rest follows.