The firehose problem: why more data made us worse at deciding
We've never measured ourselves more precisely, and never been more paralyzed by what we found. The fix isn't another metric — it's a decision.
Signal 01 · The MethodFor a decade I built models that turned market chaos into a single call — buy, hold, or sell. The desk didn't reward the prettiest dashboard. It rewarded the person who could look at a wall of conflicting signals and commit to one move before the window closed.
Then I went home and did the opposite. I owned a ring, a watch, a scale that graphed my body fat to one decimal place. I had more data about myself than any athlete in history — and most mornings I had no idea what to actually do with it. Train or rest? Push or hold? The numbers all pointed in slightly different directions, so I did nothing, or I did whatever I felt like, which is the same thing dressed up.
That gap has a name now, at least in my head: the firehose problem. We've never had more information about our health, and we've never been more unsure what to do with it. And I've come to believe that gap — between everything we measure and the choices we actually make — is the most expensive problem in modern wellness.
Measurement is not the same as a decision
The wearables industry sold us a quiet lie: that if you could just see the number, the right behavior would follow. It doesn't. Visibility and action are different skills, and we've spent a decade over-investing in the first while starving the second.
Think about what your ring actually gives you on a bad night: a readiness score, an HRV trend, a sleep-stage breakdown, a temperature deviation. Four signals, and they don't agree. Your HRV is down but your sleep looks fine. Your temperature is up but you feel great. So which one wins? The app won't tell you — it just renders all four beautifully and leaves the hardest part, the decision, entirely to you.
And the cost of the unmade decision is never zero. Every morning you don't decide is a morning decided by default — by momentum, by mood, by whichever app shouted loudest. A dashboard is a decision you've postponed; twelve charts are twelve postponements. On a trading floor, deferral at least shows up on a P&L by Friday. In a body, the invoice arrives years later, itemized as nothing in particular.
"The enemy was never too little information. It was too much — and no one to turn it into a single, confident move."
On a trading desk, a model that output thirteen charts and no position would be laughed off the floor. Its entire job is to collapse uncertainty into an action you can be held accountable for. Health tech does the reverse. It expands one honest question — what should I do today? — into a museum of graphs, and calls that empowerment.
Where the years quietly go
Put a rough price on it. You'll make something like a thousand train-or-rest calls in a decade, ten thousand bedtimes, thirty thousand meals. Each one is small; the volume is enormous. Nudge even five percent of them from “default” to “deliberate” and you've made a material trade on the largest position you hold. That's the whole pitch — not perfection, just a slightly better hit rate, compounding quietly for years.
Here's the shape of it in one ordinary week. Monday you wake under-recovered but train hard anyway, because the plan said so and nothing said otherwise. Tuesday you're wrecked, skip entirely, and eat like it. Wednesday through Friday you're negotiating with yourself instead of training. One deliberate call on Monday — go easy today so Tuesday exists — and the week is a different week. Multiply by fifty-two, then by a decade. Nothing about that requires heroics. It requires a decision, delivered at the moment it's useful, in a form you can act on before coffee.
The research keeps circling the same point from different angles: long-term outcomes track daily behaviors, daily behaviors track decisions, and decisions fail at the moment of translation — the moment the number was supposed to become a move. We built an industry that measures everything and asks nothing of us. The asking is the product I actually wanted.
The three moves that actually matter
When I finally pointed my old risk framework at my own body, the method got embarrassingly simple. Three steps. I call it Decision for Performance, and it's the same loop whether you're managing a trading book or a training week.
01 — Measure less, on purpose
Not everything that can be tracked is worth acting on. Most days, six signals decide the call: sleep debt, HRV, resting heart rate, training load, glucose variability, and subjective mood. Everything else is noise that makes the noise louder. Muting a metric is not ignorance — it's a decision about where your attention is worth spending.
02 — Model honestly
A signal only matters relative to your baseline, not a population average printed in a glossy app. The same engines that price risk under uncertainty — Bayesian updating, simple regime detection — work beautifully on a person. They don't need to be fancy. They need to be honest about what they don't know, and to widen their confidence bands when the data gets thin. A model that can't say “I'm not sure” will eventually lie to you with a straight face.
03 — Decide, with a number attached
The output is never a dashboard. It's one line: given your last two weeks, do this today — with a confidence score attached, so you know when to push and when to back off. Deload. Easy Zone 2, forty minutes. Confidence 0.82. That's a decision you can be accountable to tomorrow. Thirteen charts are not.
What this asks of the builder — and of you
A one-line call is a serious thing to hand somebody at six in the morning, so the line has to earn its authority. It must show its work. It must admit its error bars. And it must never pretend to be your doctor — my rules are public and non-negotiable: the system never diagnoses, never replaces your clinician, never sells you a supplement. A model that wants the right to tell you what to do earns it with humility about what it doesn't know.
It asks something of you, too: a willingness to act at less-than-certain, to log what happened, and to let the model be wrong out loud so it can get better in public. Trust, like everything else in this method, compounds.
From measuring yourself to deciding for yourself
The shift I want for people is small to describe and enormous to live: stop measuring yourself and start deciding for yourself. The data was always supposed to be a means to that end. Somewhere along the way we made the measuring itself the hobby, and quietly forgot it was supposed to change what we do.
You don't need another chart. You need the next decision. That's the whole thesis, and everything I build — the open-source engines, the weekly notes, even the little flower project that isn't for sale — is just a different way of closing the same gap: one good decision at a time. The firehose isn't going away; you'll own more sensors next year than you do now. The goal was never more water. It's a cup you can actually drink.