unless you've been building healthcare operations for years and the ai is what you built from inside the work
in that case the truth wasn't found, it was earned, one operating decision at a time
it’s difficult to build healthcare ai without operational truth
it’s difficult to rely on 3rd party vendors for operational truth
you have to find the truth yourself and only then do you earn the right to build something actually transformative
Claude: “That may be difficult to implement.”
@Replit: “Hold my beer.”
Supabase connected.
GitHub synced.
Stripe live.
Working platform shipped.
Then Claude reviews it and starts complimenting the architecture.
We’re entering a different era of building.
@billgnofficial Caidir — the AI decision platform for healthcare to design workflows, govern AI safely, and measure what actually improves care.
https://t.co/Cw8NvmQbYP
Top 3% of builders. Manager of Parallel Agent. 🥇
What happens when you combine intentional design, autonomous AI agents, and one free @Replit build day?
A healthcare AI platform — and our first enterprise client. https://t.co/YXyCHv0jPp
Supabase. Stripe. Anthropic. Governance. Workflow orchestration. Connected end-to-end.
Thanks @raymmar@MannyBernabe #ReplitBuildathon
12 hours into @Replit Buildathon, tired and leaning on Claude—and it’s praising Replit Agent.
"The rhythm here is good. Agent flags ambiguities, you resolve them precisely, agent ships clean. This is what well-instrumented AI-assisted development looks like — and frankly it's what the Decision Tracker itself is modeling for healthcare AI deployments. You're eating your own dogfood without trying to."
The first call isn't to a clinician, it's to a mother, sibling, partner, or friend. That's the layer being replaced, not primary care. And it's worth pausing on what's lost in the swap: those people weren't just triaging symptoms, they were providing context, reassurance, and co-regulation. An LLM can do the 'what is it' part well. The 'should I worry' part is where the substitution gets harder.neighbor.
Harvard just tested every major AI model — GPT-5, Grok 4, Claude 4.5 — on clinical reasoning.
80% failure rate at differential diagnosis. The task that starts every patient encounter.
The art of medicine is still human.
New post: https://t.co/LowxMlGhpF
The flip side:
Leading LLMs produce up to 14.6 severely harmful recommendations per 100 clinical cases when deployed broadly.
Same models. Catastrophically different results.
Construct determines efficacy. Not capability.
The flip side:
Leading LLMs produce up to 14.6 severely harmful recommendations per 100 clinical cases when deployed broadly.
Same models. Catastrophically different results.
Construct determines efficacy. Not capability.
83% reduction in note-writing effort. 112% ROI on documentation AI. 18.7% reduction in sepsis mortality.
These aren't pilots. These are enterprise deployments with documented results.
83% reduction in note-writing effort. 112% ROI on documentation AI. 18.7% reduction in sepsis mortality.
These aren't pilots. These are enterprise deployments with documented results.
The AI tools winning in clinical settings aren't the most sophisticated ones.
They're the ones built around how clinicians actually work.
Same technology. Radically different outcomes. The difference is construct.
The AI tools winning in clinical settings aren't the most sophisticated ones.
They're the ones built around how clinicians actually work.
Same technology. Radically different outcomes. The difference is construct.
Stanford's 2026 AI Index dropped today.
423 pages. I read the medicine chapter so you don't have to.
The finding that matters most for healthcare leaders 🧵
Stanford's 2026 AI Index dropped today.
423 pages. I read the medicine chapter so you don't have to.
The finding that matters most for healthcare leaders 🧵
Sorry to hear about your wife and hope she's healing well.
What you saw isn’t surprising. AI in healthcare isn’t absent, it’s fragmented. A bit of a buckshot now. Tools exist, but there’s no system for deciding where, when, and how they should be used. Plus doing it in a regulatory environment.
That gap is where I’ve spent my career. I’m building Caidir as a decision layer for health systems, helping leaders prioritize AI use cases (like nurse retention and scheduling), assess readiness, and deploy with governance that actually holds up in clinical environments.
Would welcome a conversation. https://t.co/YXyCHv0jPp
Been a minute since I’ve posted…
I’ve spent the last 6 weeks in ICUs, hospitals, and rehab facilities with my wife, and the wild part is there’s basically zero AI anywhere.
One veteran nurse told me they don’t use it at all, even though their biggest problems are nurse retention and scheduling.
Reminder: we’re backing at least one new team every month with $100K to $1M initial checks.
If you’re building AI in this space, I want to meet you and back you.
This app in our Buildathon is fantastic! Scan your site and you'll get a diagnostic that Replit was able to digest and make immediate fixes! Nice job @Thor_ne2k
Replit buildathon is having 6,400 participant now, figure not everyone can get feedback from judges and replit team. So I built this Scout Check Or Wreck to help anyone trying to get real feedback on your app not just "looks good!"
Scout Check Or Wreck tells you: → does your UI actually make sense to user → would anyone pay for this → is there a real market for what you built → what's broken that you haven't noticed yet
Just paste your URL and AI agents crawl your app like a real user. you get specific findings + a fix prompt you can paste straight into Replit Agent to address each issue
I build this using replit and backend is what I borrow from Scout - built by Katalon + AWS AgentCore — not a simple vibe wrapper
It free and took around 2 min if you use check mode, and around 30 second for wreck mode:
https://t.co/VRzdONRLw8
Exactly right. That reaction isn't enthusiasm, it's a calculation happening in real time. The compliance burden in healthcare is so heavy that even partial relief registers immediately.
@ROARHealth@Replit healthcare compliance is one of those spaces where the 'I could spend all day on this' reaction is actually the signal, because the person saying it isn't being polite, they're doing the math on hours saved in real time.