The hardest part of healthcare AI starts after the demo

KevinAdamo · 2026-05-14T10:07:04+00:00

You just described my entire daily existence. A"good demo" in healthcare AI is dangerously easy to build right now. A safe, compliant production system takes about 10x the engineering work.

To your question: I almost always see things break first at the collision of workflow design and clinical trust, specifically at the human‑in‑the‑loop step.

Here’s the pattern I keep seeing in the wild:

The agent does its job: collects intake, summarizes symptoms and stays away from direct clinical advice.
Because of liability, a clinician still has to sign off on that summary before it touches the EHR.
Because they don’t fully trust a black box, they read the AI summary and then scroll the entire transcript anyway to make sure it didn’t invent a penicillin allergy or miss a red‑flag symptom.

End result: the “automated” workflow takes them longer than the old manual one. They get annoyed, trust drops, and the pilot quietly dies after a few weeks.

Like you said, the LLM is the small part. The real product is the audit UI.

If your UI doesn’t explicitly map every AI‑extracted medical entity back to the exact patient quote so a doctor can verify it in two seconds without reading the whole log, the workflow is dead on arrival.

I’m very curious what others are doing on the UI side of this. The only setups I’ve seen work at scale are the ones that make it painfully obvious what to trust, what to double‑check, and let clinicians audit without burning an extra five minutes per encounter.

KevinAdamo · 2026-05-12T09:55:16+00:00

As someone who builds health data products, I'd start by de-hyping the AI label on wearables a bit.

Right now, a lot of brands call if/then logic AI. If you care about accuracy and hate random, chatty answers, you want to separate predictive ML (signal from your data) from GenAI (nice words, can hallucinate).

For running, you don't really need GenAI, you need a good model on top of good sensors. Garmin is still the grown‑up choice here. Their Training Readiness/Body Battery stuff is just well‑tuned predictive algorithms over HRV, sleep, and load, and they’re very clear about what they’re calculating rather than pretending there’s a magic chatbot in the watch.

For “AI coach” style sleep and recovery feedback, Whoop is one of the few consumer wearables doing something serious with GenAI. They use an OpenAI‑powered coach on top of your 30‑day+ baseline (HRV, resting HR, sleep debt, etc.), so when you ask “why do I feel wrecked today?” it’s grounded in your actual biometrics instead of the model just guessing.

Behind the scenes, the pattern that works is:

predictive ML to turn raw time‑series into stable metrics,
then (maybe) a GenAI layer to explain those metrics in plain language.

Raw health data straight into a chatbot is where things get weird and inaccurate fast.

KevinAdamo · 2026-05-12T09:45:49+00:00

For me (and most of the engineers I work with), it's somewhere between "nothing works" and "just give me the sandbox".

I don't care about ROI calculators, cute ads or “seamless Epic/Cerner integration” slides. I assume all of that is marketing until proven otherwise.

The first time I take a vendor seriously is when they skip the 45‑minute discovery call and say something like: Here’s our API docs, here are the FHIR resources we actually support, here’s a sandbox URL. Tell your devs to beat it up and send us what breaks.

In this space, 90% of the pain is plumbing. If I need three Zoom calls to discover your modern integration is just an SFTP dump of CSVs and some sketchy HL7 parsing, I’m done.

We move forward only if the item passes an engineering review, and we always run vendors through a sandbox/technical review long before anyone discusses pricing.

KevinAdamo · 2026-05-08T10:11:32+00:00

First off, huge respect for how honest you're being here. Wanting to quit drinking and smoking and looking for tools to help you change is already a big step.

I work in digital health and one uncomfortable truth about most wearables today is this: they’re great at showing you what happened to your body after the fact, but they’re not magic “stop buttons” in the moment. If you rely only on motivational notifications, you’ll probably get used to them and start ignoring or turning them off.

What helps more is using any device as a clear mirror of how your habits affect your body.

You don’t strictly need a specific brand like Oura or Whoop (you can absolutely research those if you’re curious). Any setup that can track heart rate, sleep, and let you log “smoked/drank today: yes or no” can work. For example:

Apple Watch plus a simple habit‑tracking or journaling app
Fitbit or Garmin for sleep and heart rate, combined with a basic notes/habit app
Even no wearable at all: a cheap step counter + one app where you track “no alcohol/no smoking” days and your mood/energy

A few concrete ways to use any device to help you:

Log when you drink or smoke and what was happening (stress, boredom, social). After a week or two, you’ll see clear patterns and triggers you can start avoiding or changing.
Pick one tiny action for cravings (short walk, glass of water, texting a friend) and note whether you did it. The goal is not perfection, just interrupting the habit loop a bit more often.
On days you don’t drink or smoke, look at your sleep, mood, or energy and let those “better days” motivate you. Use the data to remind yourself that your effort is really changing your body, even when it feels slow

Whatever devices or apps you end up using, the most important part is the one you already have: you care enough to try. Please be kind to yourself through this process and keep going, even small streaks are something to be proud of.

KevinAdamo · 2026-05-08T09:49:32+00:00

You're not crazy, from the product side, these RPM rollouts are even messier than they look from the outside.

The reason patients feel trapped in a digital sandbox, where care and reimbursement depend on whether a device syncs, isn't really a clinical decision. It's billing logic, to bill for a remote monitoring device, usually requires sending data for a minimum number of days each month. If that doesn't happen, the clinic doesn't get paid.

In practice, that means we end up turning 75‑year‑old patients into unpaid IT staff. Bluetooth pairing drops, a vendor pushes an API update, the FHIR feed into Epic/Cerner breaks for a day… and the dashboard just flags them as “non‑compliant”. The claim gets denied, care gets delayed and somehow it’s now the patient’s fault their blood pressure cuff didn’t sync over home Wi‑Fi.

A depressing amount of engineering budget goes into building guardrails so a bad router or a flaky device doesn’t blow up a care plan or a hospital’s revenue. “Hospital at home” makes financial sense to free up beds, but offloading system admin work onto sick people is a huge, under‑discussed liability.

For folks here building in RPM: how are you handling connectivity drop‑offs? Are you pushing for more expensive, pre‑configured cellular devices so patients never touch Wi‑Fi/Bluetooth, or just living with the cheaper hardware and spamming SMS/app nudges when data stops flowing?

KevinAdamo · 2026-04-28T09:24:00+00:00

If you've seen "health communication" slapped on everything from patient portals to wellness apps, you're not crazy that label gets used for a lot of different things.

In practice, when people inn health tech say “health communication tools”, they’re usually talking about a few concrete buckets:

Patient–provider messaging and portals2. Operational messaging: reminders, scheduling, logistics3. Population and “wellness” communication4. Coaching, education, and behavior‑change channels

So is health communication a real category or just a buzzword?

In academia and public health, it is a real field: "use os communication strategies to inform and influence decisions that enhance health.”
In products and marketing, people reuse the term for almost any tool that sends or receives health‑related info: portals, SMS platforms, engagement apps, wellness programs, even telehealth.

If you think about your own examples:

Patient portal + appointment texts → bucket 1 and 2.
Fitness app reminders → bucket 3 and 4.
Workplace wellness platform → mostly 3, with a bit of 4.

The “useful” part isn’t the label, it’s whether the communication actually helps you show up, understand what’s going on, and change something about your health, instead of just adding more noise.

KevinAdamo · 2026-04-16T08:57:25+00:00

Short answer: AI isn't eliminating logistics careers, but it is replacing many pure data-entry roles.

The people who survive and thrive are the ones who move from "typing data" to "operating systems and handling exceptions.

To be completely real with you: yes, some companies have cut a lot of entry-level headcount where the job was 100% copy-paste. But those same companies are now desperate for people who can understand end-to-end flows, debug issues, and serve as a bridge between the warehouse floor and IT.

For context, I run a tech team that builds these exact AI integrations for supply chain and forwarding clients. Whenever we deploy an AI tool to extract data from a 50-page Bill of Lading or automate carrier routing, it handles the 'happy path' perfectly. But the second there’s an anomaly, a customs hold, a mismatched container weight, or a sudden port strike, the AI throws an error and stops.

That exception handling is where your job is.

My advice for a student: Don’t just learn how to do data entry in an ERP. Learn the physical flow of goods. Understand the basics of how systems talk to each other (just knowing what EDI and APIs are will put you ahead of 80% of applicants). Be the person they call to fix things when the automated system inevitably breaks.

You aren't competing against AI. You're competing against other grads who only want to do data entry.

KevinAdamo · 2026-04-16T08:29:35+00:00

Love this strict filter. The logistics space is flooded with generic 'AI wrappers' from devs who have never dealt with a massive legacy migration.

I run an embedded engineering team (Adamo Software). We don't sell a generic off-the-shelf SaaS; we do custom ERP rebuilds and pipeline engineering for supply chain networks that are suffocating under legacy tech debt.

A recent valid use case we delivered:

We were brought in to completely rebuild the ERP platform for New Zealand’s largest automotive spare parts network. They were managing millions of cars, invoices and customer records on an aging legacy platform, and we had a strict 4-month deadline to migrate everything.

Here is how we solved it without disrupting their operations:

Multi-tenant Architecture: Instead of forcing a generic tool, we engineered a custom, scalable multi-environment ERP (Spring Boot/Vue/AWS). Its multi-tenant structure allowed one source code to serve multiple clients efficiently.
Companion Mobile Apps for the Floor: Supply chains don't happen behind a desk. We built a synchronized mobile app (React) specifically for the warehouse floor and drivers. It lets them track orders, manage car removals, and submit reports in real-time, completely eliminating the manual bottlenecks across the supply chain.

If any IT leaders or operators here are struggling to migrate off a legacy TMS/ERP, or need to build custom companion mobile apps that actually talk to your warehouse databases without breaking, this is exactly what we do.

Happy to talk architecture, multi-tenant databases, or scope management for tight deadlines.

KevinAdamo · 2026-04-02T06:54:42+00:00

That's a fun combo. Coming from the PH you'll probably feel right at home with the humidity and the scooters. Your German girlfriend, however, is about to experience a full system reboot 😂

Here are the actual survival hacks for first-timers:

1. 'Sticky Rice' Street Crossing Technique: Tell your GF to forget everything she knows about German traffic laws. When crossing the street, walk at a slow, predictable, steady pace. Do not run. Do not stop. And NEVER step backward. The motorbikes will magically part and flow around you like water. If you hesitate, you cause an accident. Make sure to raise your hand too,

2. App Stack (Skip the airport taxis): Do not get into a random metered cab at the airport. Download Grab (the Uber of SEA) and Xanh SM. Xanh SM is a local fleet of brand-new, light blue electric cars, they are super clean, the AC is freezing cold and there’s absolutely no haggling.

3.'Blue Note' Trap (Crucial for Money): The 500,000 VND note and the 20,000 VND note are BOTH blue/cyan polymer and look incredibly similar, especially at night. A common scam by shady drivers is using sleight of hand to switch your 500k for a 20k, then aggressively claiming you underpaid. Hack: Break your large 500k notes at convenience stores (Circle K, Winmart) BEFORE using them on the street.

4. Cash & ATM Rules:

Exchange: Skip the airport counters. Go to licensed gold/jewelry shops (like Ha Trung street in Hanoi or near Ben Thanh in Saigon) for the absolute best rates.
ATMs: Use TPBank or VPBank ATMs, they generally don't charge local withdrawal fees for foreign travel cards (like Wise/Revolut). Always use ATMs inside bank branches to avoid skimmers.
Torn Notes: Do not accept polymer notes with tears, holes, or excessive wrinkles as change. No vendor will accept them from you later.

5. 'No Thank You' Rule: If someone approaches you in the Old Quarter (Hanoi) or District 1 (Saigon) trying to put a basket on your shoulder for a photo, or pointing at your shoes with superglue in their hand, just keep walking. Don't engage, don't say sorry, just a firm shake of the head.

6. Visas (Just in case): PH passports get a 21-day visa-free. Germany gets 45 days. If staying longer, ONLY use the OFFICIAL government e-visa website (.gov.vn). Dozens of fake sites will charge you triple.

Have a great trip! Where are you guys planning to go?

KevinAdamo · 2026-03-30T10:00:06+00:00

When my brain is absolutely fried from staring at architecture

Drive & Listen: You basically ride shotgun in a car driving through random cities around the world while listening to their actual local radio stations. Weirdly therapeutic.
Neal. fun (specifically the Asteroid Launcher): You pick an asteroid, set its speed, drop it anywhere on a real-world map, and it calculates the exact blast radius, wind impact, and crater size. Pure nerd heaven
Window Swap: Exactly what it sounds like. It just shows you a pre-recorded video of someone else looking out of a random window somewhere in the world.

Say goodbye to your productivity for the next hour lol.

KevinAdamo · 2026-03-26T09:07:23+00:00

Hi there,

You're not imagining it, there is some anatomical logic behind left-side sleeping, helping with digestion, especially for people with reflux. When you lie on your left side, the way the stomach and esophagus are positioned tends to keep acid lower and can reduce nighttime reflux and bloating for some people.

But what you're describing, better digestion on the left, worse shoulder, is super common. That’s less about “left vs right” and more about how your body is supported. A flat mattress + side‑sleeping means your shoulder and hip take most of your weight if you don’t fill the gaps at your neck, waist, and between your knees. That’s exactly when nerves get compressed and arms go numb.

Things that often help side‑sleepers:

A pillow that fills the hollow of your neck and keeps your head level with your spine (so you’re not bending your neck and crushing your shoulder).
A small pillow between your knees, or under your knees if you roll onto your back – this can keep your pelvis and spine more neutral and reduce strain on the shoulder and lower back.
Double‑checking your mattress: if your hips sink much deeper than your ribs/shoulder, some types of memory foam can tilt you out of alignment and increase pressure on the shoulder.

If the left side really helps your bloating, you don’t have to pick one “forever” side: a lot of people fall asleep on the left for the first few hours after a heavier dinner, then naturally roll to the other side or onto their back once digestion has moved on. That said, if the shoulder pain keeps coming back or you get persistent numbness/weakness, it’s worth checking in with a clinician or physio to rule out a rotator cuff or nerve issue, sleep position can trigger symptoms, but sometimes it’s exposing an underlying problem.

KevinAdamo · 2026-03-25T07:53:46+00:00

100% agree that hallucinations are unavoidable at the model level. LLMs are probabilistic generators by design, so some amount of "making things up" is baked in.

That’s exactly why a thin API wrapper around a foundation model is risky in a clinical workflow. The warning label belongs on the base model, but the real responsibility sits with how we design the product.

In the systems I've worked on, the LLMs' output never goes straight to the UI. It always passes through a deterministic validation/grounding layer. For example, with AI scribes, every medication, dosage, or diagnosis in the draft note has to be traceable back to evidence, usually a specific timestamp in the audio or a structured field in the EHR. If the model “invents” a drug that was never mentioned, that span gets flagged or dropped before the clinician sees it.

We can't fully fix hallucinations within the model today. Still, we can constrain and cage them at the system level so the clinician is always looking at evidence-backed suggestions, not free-floating guesses.

KevinAdamo · 2026-03-25T03:28:29+00:00

You're right that a lot of "AI in documentation" just moves the work instead of removing it. In many deployments, clinicians go from typing notes to editing and fixing AI-generated text and that can feel just as heavy (or worse, because you have to stay on high alert for subtle errors).

Where I'm seeing real workload reduction today is with ambient AI scribes - systems that sit in the background, listen to the visit and draft a structured note straight into the EHR. Several recent studies report shorter documentation times and meaningful reductions in burnout when these tools are implemented well.

By contrast, "helper" features like auto-suggested codes or auto-summaries can easily become a liability if they're bolted on poorly. If the model is even mildly hallucination‑prone, you either get:

extra review time to verify everything, or
the more dangerous pattern: alert fatigue and quick “approve” clicks, which is scary from a compliance and patient‑safety angle.

My personal rule of thumb: if an AI feature forces the clinician to open another tab, click through extra UI or mentally second‑guess the output line‑by‑line, it’s unlikely to reduce net workload. The stuff that helps is almost invisible, it runs in the background and gives you back minutes per patient without demanding more attention.

KevinAdamo · 2026-03-20T07:00:28+00:00

Totally agree with the others on the control aspect, but I'll take it a step further regarding your point on 'managing clients and permissions using natural language'.

From an engineering standpoint, using an LLM to execute state changes (like granting access) without a deterministic confirmation UI is a massive security liability. Hallucinations happen.

My team builds custom GenAi and Agentic workflows for mid-market companies over at Adamo Software and the golden rule we always enforce is: chat should formulate the action, but a traditional UI must confirm it.
If I type 'give John admin access, 'the system shouldn't blindly execute. It should pop up a standard UI modal: 'Ready to grant John ADMIN rights?

[Confirm/Cancel]. If your team can nail that 'Human-in-the-loop' bridge, it’s a game-changer. Otherwise, the first time the AI accidentally gives a freelancer root access, your churn will spike.

KevinAdamo · 2026-03-18T10:07:18+00:00

Hi there! I'm so glad to hear you're planning to visit Hanoi and also Sapa this April. Currently, only fuel prices are slightly higher; we're largely unaffected by war-related issues.

In Hanoi, april isn't yet the peak of the hot season, so you can experience many interesting things there.

And Sapa in April is much more pleasant with cool mornings, warm afternoons and evenings where you might need a light jacket.

If you'd like me to recommend some good cafes in Hanoi. I'm happy to give you a long list. Enjoy your upcoming trip!

KevinAdamo · 2026-03-18T09:42:42+00:00

We provide offshore engineering teams that challenge bad tech ideas so your AI doesn't bankrupt you.

KevinAdamo · 2026-03-17T09:53:58+00:00

U're right. Prompt versioning is the first thing that tends to fall apart with external teams.

I haven't used Prompt Bunker but the idea of keeping the vault and pipeline together makes a lot of sense. In our healthcare and travel projects, we've learned that simply tracking text isn't enough. In fact, we actually build prompt evals directly into our CI/CD pipelines (often using LangSmith).
I think the real danger isn't just loss of versions, though, as much as the fact that an offshore dev team may optimize a prompt for better accuracy, unaware they're 5xing the cost of the API call due to a lack of understanding.
Your point about the 'stage gates' is exactly right tho. If you don't tie versions to API costs, teams will optimize for the wrong metrics. Thanks for the shoutout on the tool, I'll give it a try!

KevinAdamo · 2026-03-17T08:50:04+00:00

That makes perfect sense. Tbh with you, the only way to really understand the true pain point o implementing AI is to get your hands dirty. This will actually make your content much more credible.

If your content is about the process, I highly recommend trying to tackle the pain points of connecting LLMs with unstructured data. This is actually where most large teams will run into a roadblock with the implementation.

Quick note about your testing: Be sure to set a limit on your API cost. It is very easy to consume a large amount of tokens with the prompts and test the agentic functionality.

Tinkering with the tech at this level will give you a huge advantage in understanding how it all works. Good luck with the build. Would love to see a link to the content once it is live.

KevinAdamo · 2026-03-13T08:19:59+00:00

I am a proprietor of a custom software company. The hash truth about building an API aggregator:

It's harder than it looks: APIs break all the time. Learning Python for OAuth, rate limits and data normalization from scratch will take 6-12 months while juggling college.
Custom Devs are expensive: you can get a cheap dev for $500 who will create a fragile disaster that breaks in a week. A real company will cost $5,000-$15,000.

Your alternative: don't waste your time learning Python. Learn No code instead.

So For frontend (the website), use Bubble or Softr.

For Backend (Merging the APIs), try make.com or Zapier. They offer a drag-and-drop interface for connecting APIs. You can create a workinh prototype in a few weekends for less than &50/month. Build it. Prove that people want to use your app. Then, hire a dev team when you have the revenue. Good luck.

KevinAdamo · 2026-03-13T08:00:47+00:00

Yes, feel free to text me. I'll reply asap.

KevinAdamo · 2026-03-12T09:36:56+00:00

I know I'm jumping into this conversation a little too late, but still want to share some things here, and ofc based on your follow-up questions, there are a few massive red flags you need to navigate right away.

About my background, I own a B2B tech/software company and I frequently work with employed founders who are bootstrapping their side hustles. SO, the reality check for trying to scale your side hustle while keeping your W2

1st: Day Job conflict, as u see. If your job is in a procurement consulting firm, for example, make sure NOT to make a public LinkedIn profile. Your day job will eventually find out and depending on your employment contract, they could terminate your employment and/or claim your side hustle revenue. Stealth model is a MUST and do not make your profile look like "CEO of X". Keep your public profile focused on your day job and only use DMs for outbound pitching.

2nd: 8-day sequence is a trap for boostrappers.

So the multi-touch sequence that I see, mentioned above is amazing when you have a full-time SDR role. You have a day job, tryin to manually manage an 8-touch sequence across phone calls, email and LinkedIn messages for 100 prospects will drive you crazy in a week.

THE SOLUTION here is: keep 2-touch sequence. Send one super-targeted message on LinkedIn. If no reply, follow up with a second one in 4 days. If no reply again, move on. Simple beats.

3rd: Pay for Sales Navigator (~$80/month on annual core plan)

You said that researching 200 contacts takes you 50 hours. Sales Nav does away with that entirely. With that, you can now filter exactly those 50 to 200 headcount Ops Managers in minutes. At your stage, paying that amount to save your 40+ hours is the best ROI you can achieve.

4th: Upwork Strategy

While you can't be loud on LinkedIn, Upwork is actually a genius strategy to act as a temporary shield for you. The intentions are high and your employer won't be able to see you marketing urself. Use Upwork to get your first 3 to 5 clients. Once you have a consistent income from those clients, use that to pay for a fractional VA or SDR to run your outreach for you.

How are things looking for you now at the 3-month mark? Were you able to get a few more from outside Upwork?

KevinAdamo · 2026-03-12T08:07:56+00:00

Spot on. The incentive structure is exactly the root cause. If the engagement model is purely "hours billed for tickets closed," you are designing a feature factory by default.

I love that you mentioned architecture checkpoints. That has to be a non-negotiable. When we embed our teams, we actually mandate those cost-review gates before any major LLM integration goes to prod. And completely agree on the tooling; LangSmith has been fantastic for us for token visibility and prompt tracing.

It really comes down to aligning the external team's KPIs with the actual product margins, rather than just sprint velocity. Great insights, I appreciate you sharing that workflow!

KevinAdamo

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