Bitter Makes Durable
Case of the Week, Min Wu, PhD · ai-public-health.com
Last year my backyard cucumbers came in well enough that this spring I gave the same small bed to beans too — same seed, same watering routine, same daily few minutes of attention that had worked the year before. Two months in, both plants were coming along fine. Then, almost overnight, the beans were gone. Not yellowed, not diseased — cleared down to bare stems. Three feet away, the cucumber vines are still standing, untouched.
The Part I Didn't Plant
The explanation turned out to be simple: something — a rabbit, by the look of the bite marks — had eaten the beans for exactly what they are, a meal. Beans, it turns out, were the wrong plant for that bed.
Cucumber vines, stems, and leaves are covered in small, stiff hairs that make them unpleasant to chew. The leaves also carry cucurbitacins, compounds that taste distinctly bitter — bitter enough that a rabbit or squirrel typically quits after one exploratory bite. None of this is a response to anything. The plant isn't noticing a predator and reacting to it. The defense was built in before any predator arrived, and it asks nothing of the plant to keep working.
Beans carry no equivalent. To a rabbit, they are soft, palatable, and worth the trip. The only thing standing between my bean plants and a hungry animal was a fence I never built. Whatever decided this outcome was decided back in April, long before anything showed up in July to test it.
A Structural Parallel
That isn't really a story about gardening technique. It's a story about where defense lives. Internal focus is useless if you ignore external predators — a rule that applies as much to a public health program as to a raised garden bed. Effort spent perfecting the thing you're growing doesn't count for much if none of it went toward what happens when that thing meets an environment that was never designed to be kind to it.
Where PMCO-AI Comes In
I built PMCO-AI, my human behavior-change framework, around a simple claim: opportunity comes first. It extends COM-B — the Capability-Opportunity-Motivation model from Michie, van Stralen, and West — by adding AI as the mechanism that personalizes each ingredient and delivers it in real time: Personalized Motivation, Personalized Capability, Personalized Opportunity. In most of the cases I've built it around — dementia care, heat response — opportunity is what varies. A caregiver's feasible option changes minute to minute depending on the patient's mood and the room they're in; an older resident's feasible option in a heatwave depends on whether a cooling center has capacity right now. When opportunity is the thing moving, opportunity decides the outcome, and motivation or capability alone can't compensate for its absence.
The garden is the opposite case, and it's worth naming precisely because it's opposite. The cucumber and the bean shared the same yard, the same rabbit, the same July. Opportunity — in the sense of exposure, of what the environment made available to a predator — didn't vary between them at all. What varied was Capability: the cucumber's built-in bitterness and rough texture, present before the rabbit ever arrived, against the bean's lack of any equivalent. When opportunity is fixed across two agents in the same environment, capability is the variable left standing to explain the different outcomes.
That's not a contradiction of PMCO-AI's opportunity-first claim. It's the claim's boundary condition: opportunity decides the outcome when it varies; capability decides it when opportunity doesn't.
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