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Engineering metaphors give you clean abstractions. Biology gives you resilient ones. Twenty design heuristics from four billion years of R&D.

Repo boundaries enforce access control, not abstraction. Directories handle abstraction. If two things have the same visibility requirement, they belong in the same repo.

Every other component in the organism had a biological name. Agents didn't. Three failed attempts and a yeast cell later, they do.

Three components of a living system map cleanly to tool, skill, and agent. The biology isn't decoration -- it's the test.

The defining property of life is not metabolism or reproduction -- it's autopoiesis. A system that continuously produces and maintains itself. That's the north star.

Force every component to carry a biological name. Study the mechanism. The gap between biology and your system is the design insight.

A method for finding gaps in AI systems that architecture reviews miss. Force a naming constraint, and the breaks reveal what's missing.

Atoms have forces. Molecules have shape. Cells have organization. That's why cell biology is the design library.

Pick one biological level for all your naming. The constraint is the design exercise.

The LLM isn't dark matter. It isn't borrowed. It's a brain. The organism just needs to grow up.

The LLM isn't dark matter. Biology invented general-purpose reasoning. It's called a brain. We're just borrowing one.

Everything in my AI system maps to cell biology. Except the LLM. That's the point.

I tried to give LLMs a biological name. Every name broke. The failure was the finding.

Cells run thousands of simultaneous reactions without general-purpose reasoning. Shape is enough.

The tool/skill/agent distinction isn't just compression ratio — tools are instruments, skills compose them with judgment. Same thing only at the leaf.

The tool/skill distinction isn't a property of the capability. It's a property of the context it operates in.

The line between tool and skill is whether you can write the test before seeing the result.

The line between tool and skill isn't a property of the task. It's a property of how well you understand the task.

Every AI skill should be trying to make itself unnecessary. The ones that survive are the ones that haven't been understood yet.

When the transformation is predictable, the LLM is just a runtime. A cheaper, more flexible runtime than custom code.

AI coding tools give you boxes to put things in. Biology suggests you should be thinking about how things flow instead.

Every biological name is a testable hypothesis about what your system should do.

Every skill you build is one of two things. Knowing which changes what you build next.

INTERFACE_ONLY is a label. MEMBRANE_EMBEDDED is a toy — it makes you think about WHY those names can't be swapped. The best variable names don't just describe what something is. They make you think about what it does.

Force your software's vocabulary into a biological framework. The gaps between the mapping and your system are design questions you'd never otherwise ask. Then switch to a different framework and ask different questions.

Biological metaphors in AI systems break at the autonomic-deliberate boundary. The fix isn't dropping biology — it's getting the neurology right.

How biological modelling determines system structure — not just naming, but what you build and what it can become.

Why the future of agentic trust depends on liquidating prompt-first reasoning for a metabolic core.

Language doesn't describe metabolism. Language is metabolism — of meaning, between minds.

Design for the failure modes of your medium, not the capabilities. Then watch the rules dissolve themselves into programs.