← Back to home

Top-Tier AI, Information Parity for Health — Managing My Own Health with Claude Code

Long-Form Video · EP0032 June 7, 2026 10:32
What this episode covers

Friends still working at companies, at the big tech firms, keep asking me the same thing — an agent as expensive as Claude Code, what can it actually do for me personally other than earn money in my business? This episode is one answer: I use Claude Code to manage my own health. Up front: today is purely personal sharing, and it contains no medical advice whatsoever.

Over the past few years, two of them were spent at Xingshulin running a "personal physician for entrepreneurs" business, working with a lot of top-tier hospital specialists to deliver online health management consulting. So I have a decent sense of what good health management looks like. With AI, we can now get pretty far with this at home on our own — not replacing doctors, but helping doctors keep our health records far more detailed, so that when they examine us they consider more of the picture and give better diagnoses and better plans.

This entire episode is personal sharing. It does not constitute medical advice of any kind.

Friends still working at companies, at the big tech firms, keep asking me the same thing: an agent as expensive as Claude Code — beyond me using it to earn money in my own business, what can it actually do for me personally? Today I’ll share one answer: I use Claude Code to manage my own health.

First, some background. Over the past few years, two of them were spent at Xingshulin running a “personal physician for entrepreneurs” business — helping entrepreneurs manage their health, connecting with a lot of top-tier hospital specialists, delivering online health management consulting. So I have a decent sense of what serious health management looks like. My core view: AI isn’t here to replace doctors entirely. It’s here to help doctors manage our health records in far more detail — so that when we go see a doctor, when we go in for tests, the doctor can consider more of the picture and arrive at a better diagnosis and treatment plan.

A six-month follow-up plan

I had my last full checkup around late December and early January. The plan came from the AI, built off my earlier checkup reports and my genome sequencing report: it started by pulling every annual men’s checkup package the big health providers offer — what each costs, what tests each includes — analyzed them, recommended an annual package for me, then picked out a set of add-ons on top of it. And at the end it very thoughtfully flagged two or three tests the annual package simply can’t cover, then told me which department to book at a hospital like Beijing Hospital to get those done.

Six months have passed now, and some things happened in those six months. For instance, I developed allergy symptoms for the first time in my life — I grew up in Beijing and had never had allergies, so it’s probably six months of short sleep plus all the late nights with AI. Every symptom I developed in this stretch, every treatment and test I had, I synced all of it to the AI, and it built me a six-month follow-up plan that spelled out exactly which few things were most worth my attention.

A few examples, one by one:

  • Cubital tunnel syndrome: go back to neurology for follow-up. Anyone who lives at a computer knows this one — it’s an occupational hazard. Keep your elbow bent while typing long enough and your little finger goes numb. The plan it drew up this time is an EMG plus high-frequency ultrasound of the ulnar nerve at the elbow, to get a more accurate, quantified read on how it’s progressing. On feel alone all I can say is “more numb” or “less numb,” and over these six months I specifically added vitamins and did exercise-based therapy — these tests let me quantify whether there’s actually been improvement, and whether surgery is next.
  • Fatty liver / liver fibrosis: its recommendation is grounded in my genome sequencing results — my family genetics make me more prone to liver fibrosis. I’m a Liaoning-Shandong mix and can hold my drink, but the genes say that while I metabolize alcohol reasonably well, alcohol as a liver-damaging substance actually hurts me more than most. My last checkup showed mild fatty liver, so it drew up a set of quantified liver tests.
  • Clot-related markers: my hematocrit runs high, and I also ran a guesthouse in Yunnan for four years — live at altitude long enough and your blood cell count rises, which makes clots more likely. A routine checkup generally doesn’t test for these specifically. But because the genetic risk is established, and because the AI knows my full history of conditions and treatments, it tells me to watch these markers specifically.
  • Plus the cardiovascular panel you should be doing in your forties; this year’s allergy problem (I’m on ebastine now, and it gives me a set of medication warnings — because it knows that among the dozen-plus supplements I take, curcumin interferes with the metabolism of ebastine’s main compound, pushing blood concentration up into dangerous territory); the subtyping for my elevated uric acid; and targeted early cancer screening based on family genetics — it didn’t tell me to test for everything, it flagged tumor markers for two specific cancers it recommends I test for, and it also lists the ones I tested six months ago that don’t need repeating this cycle.

It also gives me an actionable plan. The thing that annoys us most in practice is not knowing which department, which hospital, how to book — it can look all of that up and give recommendations.

The key is being traceable to a source

And these recommendations don’t come with the routine you get from some agents — “sorry, I was wrong, I hallucinated again.” A genuinely good agent, given a good workflow and some real data sources, can produce content it stands behind.

In my setup, the PubMed research API is wired into Claude Code. Every judgment, decision, or recommendation comes with the corresponding reference: based on this specific paper, combined with your current situation, here’s the recommendation — every reference link, every source, traceable.

Supplements, finer-grained than a personal physician

I’ve been taking supplements for a long time, and back when I ran the personal physician business I was a personal physician customer myself. But when my doctor fine-tuned my supplement regimen, there was no way he could get anywhere near as granular as the AI does.

Buying them, too. I used to order from Tmall, but honestly I lost my nerve — those imported supplements all claim to be sourced overseas, and since I studied art I notice capsule color, and every batch I bought looked different. Counterfeits are rampant. So starting last month I switched to iHerb (a US supplement site that ships from Hong Kong) and wired Claude Code into its Hong Kong site: it can see the exact composition of each supplement, the price of a given package size, whether it’s out of stock, and then it gives me a purchase list, recommends what to adjust, what dose, why that dose, when to take it (with breakfast, every other day, with dinner, or before bed) — detailed recommendations on all of it, and it tells me what circumstances each one is based on. When some markers are still uncertain, it says this is a preliminary recommendation and it will give a more accurate target once the other tests are done.

It even explains the science. The broccoli sprout powder I take isn’t a conventional supplement, and it explains exactly what the active compound is and what conditions degrade its effect. Or take the noise a while back about fish oil being useless — it goes and finds the references and tells me plainly which population each null-result study was looking at, what the intervention was, how big the sample was, and what conditions produced no effect — and under what conditions it actually does work. Things like CoQ10 and fish oil may not deliver much in the areas they get hyped for, but for lowering my blood lipids and improving specific organ function they’re still useful. When we watch influencers online, all we get is the conclusion. A report you get after wiring in these sources and having it understand your own data is genuinely something money can’t buy.

Information parity

Never mind how little a Claude Code subscription costs per month — even if I went to the single best health management physician available today, he wouldn’t have the time, the energy, or frankly even the capacity to read all my reports. Think about it: the genetic data alone runs over 1.2 million rows, and that’s only the portion current science can tie to specific health issues and drug responses — and it’s already that large. No doctor could ever produce a report this detailed.

So beyond using AI to “pay it to work for us,” top-tier AI and top-tier agents are enormously useful for ordinary people too — it really is a breakthrough product for information parity, for parity of intelligence.

That’s it for today. Leave a comment if there’s something you want to hear about, and I’ll see you in the next one.

No doctor could ever produce a report this detailed — it really is a breakthrough product for information parity, for parity of intelligence.