Thanks @HealthcareAIGuy for spotlighting @confidohealth on this Agentic AI market map: 1. Payment Collections 2. Scheduling & Contact Center 3. Intake & Triage Our AI agents across Voice, Text, Email help patients schedule appts, verify ins, refill meds, pay bills, and more.

We've entered the next phase in healthcare AI adoption, and the value so far speaks for itself- faster and greater than expected 🔥. We asked 226 healthcare enterprises across payers, providers, and Pharma. Read our report for the details 👇

some ideas for “muse for healthcare”: - a morning digest pre-charting all patients for the day - ambient monitoring for results (labs, imaging, etc) and notification of clinically actionable findings - in-basket prioritization and triage - auto-dialing other clinical sites to obtain records or other info - monitoring of ED visits, admissions, or other specialist visits for a patient “watch list”

I've been a cardiologist for 25+ years. The last 90 days changed medicine more than the last decade, and almost nobody noticed. Here are the 10 biggest AI breakthroughs, and why you should be excited, not afraid 🧵 1/ 37,000 AI agents. One "virtual biotech." It analyzed thousands of trials, figured out which drug targets actually work in humans, and independently proposed a lung cancer strategy that a major pharma company later pursued. AI isn't a search engine anymore. It's a co-scientist. 2/ The first drug discovered AND designed entirely by AI (Insilico's rentosertib) just entered Phase 3. In patients, it reversed biological age by 3–6 years across six different aging clocks. Read that again! 3/ As a cardiologist, this one gives me chills. The FDA authorized "Queen of Hearts," an AI that reads a standard ECG and catches heart attacks, including the hidden ones doctors miss. 2x the sensitivity. Far fewer false alarms. It pages the cardiology team itself. In a heart attack, minutes are muscle. 4/ EchoNext spots 6 types of hidden structural heart disease from a cheap, 10-second ECG, and it does it better than cardiologists. It already flagged a patient who went on to get a heart transplant. Screening that used to need an echo lab now needs a test any clinic can run. 5/ UpDoc is the first FDA-cleared AI that talks directly to patients. It checks in between visits, adjusts insulin within limits the doctor sets, and documents everything in the chart. Chronic disease no longer has to wait for your next appointment. 6/ An autonomous AI agent called MIRA, with full access to medical records, went head-to-head with ER physicians on hundreds of real cases. AI: 87.8% correct Doctors: 78.1% It ordered the tests, read the results, and wrote the plan. 7/ Google released MedGemma 1.5 and MedASR, open medical AI for imaging and clinical speech that anyone can build on. Every hospital. Every researcher. Every country. Open models mean medicine moves at internet speed. 8/ The FDA authorized Aletta, the first robot that draws blood on its own. It gets the vein on the first stick 94–95% of the time, even hard veins. One technician supervises three robots. The most common procedure in medicine just got automated. 9/ UCLA's SLIViT matches specialists on 3D MRI, CT, ultrasound, and retinal scans, and it's 5,000x faster. It isn't a new model for every organ. One architecture reads them all. 10/ The FDA has now authorized 1,600+ AI medical devices. They cover radiology, cardiology, and surgery, including real-time AI that checks breast cancer margins while the patient is still on the table. This isn't coming. It's here. What this means to you: → Drugs that took 10–15 years are showing human results in a fraction of the time → Heart attacks get caught on a cheap ECG, not after a collapse → Doctors get hours back → Patients get answers between visits → Aging itself is becoming treatable This isn't "AI will replace your doctor." It's AI finally becoming good enough that medicine starts to compound. The next 18 months will feel different. Bookmark this. We're early. Stay positive!!!

A 10x EBITDA multiple for a healthcare media business. Likely the events and subscriptions drove most of the pricing. Huge outcome. Nice reporting @amediaoperator amediaoperator.com/news/beck…

Every CEO is now faced with two options in front of them 1/ Integrate yourself into the AI platforms and potentially risk getting dis-intermediated by OpenAI, Anthropic or Meta 2/ Build a castle around your platform and product, ban any API calls and potentially risk giving up hundreds of millions in revenue and web traffic Don’t think anyone really knows what the right answer is, but the path you take determines the entire future for your business Not a fun time to be a decision maker at a large company right now

the Muse product format of deeply connected chat-based agent + multi-model backend would do numbers in healthcare

I just read what Zuck wrote about Muse connectors. A few things I think this means: 1. We’re witnessing the agentification of consumer apps. 2. Zuck believes Muse reaching 100M+ users feels entirely possible. 3. Whoever you connect to becomes your new landlord, so pick carefully. 4. Connectors become the new app listings (valuable real estate). 5. Being early could be as valuable as being early to the App Store in 2009. 6. Meta sees what people want, which providers convert, and what users will pay. That gives it the power to rank connectors, charge for distribution, and launch competing services. 7. The opportunity map includes agent native APIs, connector agencies, SEO for agents, identity and reliability infrastructure, and vertical connector marketplaces. 8. We’re moving from humans choosing apps to agents choosing businesses. 9. Every business will need an agent strategy, just like every business needed a mobile strategy. 10. Kinda crazy to say but a 3 person API company could reach 10M+ users through one great connector. 11. Connectors could create an entirely new second-order economy. The biggest opportunity may be helping businesses distribute, price, and optimize their services for agents. 12. Your API becomes more important than your app. Weird to think about but true. 13. Zuck wants Muse to own the moment between wanting something and getting it. He is coming for the app economy. Will he win? Right now it's Instinct vs Muse vs Grokbot. TBD.

Someone told me recently that 70% of their marketing budget for next year is dedicated to events and field marketing because their online marketing channels have gotten such low conversion At least for b2b sales feels like more and more dollars are going to get converted to in-person marketing

Electricity reached factories in 1882. Factory productivity didn't move for almost 40 years. The motor was never the bottleneck, and the same thing is happening to AI right now. Edison's Pearl Street station opened in New York in 1882. By 1899, electric motors powered less than 5% of machinery in American factories. A skeptic in 1900 could point at the dynamo and say it was everywhere except the productivity statistics. He'd have been right. The reason is the shape of the building. Steam factories ran off one giant engine turning a central shaft, with belts and pulleys dragging power to every machine. Everything had to sit close to the engine, so factories were stacked five stories high around it, and the machines were arranged by distance to the shaft rather than by the order work actually flowed. When electricity arrived, owners did the obvious thing. They pulled out the steam engine, bolted a big electric motor to the same shaft, and kept everything else. Same belts, same layout, same workflow. Economists call it group drive. It saved a little coal and changed nothing. The gains only showed up in the 1920s, when a new generation of factories put a small motor inside every machine. That let them tear out the shafts, spread onto a single floor, and lay the machines out in the order the product moved. Manufacturing productivity grew more than 5% a year through that decade. Electricity accounted for roughly half of it. Four decades after the plug went in. Now run the last three years through that lens. GPT-4 arrived and every company did group drive. They hooked a chatbot to a workflow designed for humans and kept the org chart, the approval chain, and the software stack exactly as they were. That is why the disruption Sam expected never showed up on schedule. Nobody rebuilt the floor. Unit drive for AI means rebuilding the process around the agent instead of the person, and that requires ripping out working systems that still make money. In 1900 no owner would scrap a serviceable plant to find out. In 2026 no CIO will scrap a serviceable Salesforce instance either. The technology is ahead of Sam's 2023 timeline. The buildings are 30 years behind it.

In healthcare ai apps (and likely in most vertical ai apps) the most important layer is very rapidly becoming the action layer Insights are now everywhere and it’s actually incredibly frustrating as a patient to have ubiquitous insights from the LLM on your phone, but no clear path to action In healthcare, actions are hard. They are (appropriately) regulated, require a high safety bar, and often fragmented across many (physical) sites of care in the real world As I meet startups and see new healthcare ai products emerging, most excited by the teams who are *maniacally obsessed* with actions. Speed to action, correctness of action, impact of action…it’s a culture

Only 44% of Americans visit the dentist today. What's holding dentistry back—and how can AI help? In this Becker's Healthcare and Dental + DSO Review podcast, hear leaders from @SmileBrandsTeam and @confidohealth discuss predictive care, workforce transformation, and what the dental practice of 2030 could look like. Listen here: podcasts.apple.com/us/podcas… Watch here: youtube.com/watch?v=Tkufbyuc… #HealthcareAI #Dentistry

The age of AI has now fully shifted into the era of AI agents.

Gift Link: nytimes.com/2026/06/22/healt… First Case Report of AI Diagnostics Leading to Heart Transplant: nature.com/articles/s41591-0…

We invented a new biomarker for cardiovascular disease. The New York Times tells our story (link in comments).

seems like 2026/27 is the year where every startup tries to become an AI neolab (with their own models and benchmarks) or gets left behind Ramp -> AI finance lab Harvey -> AI law lab Cognition -> AI coding lab Decagon -> AI customer service lab

Gotham

🏆 Congrats! The 25-26 New York Knicks are the first champions that: 1) don’t have a 1A 2) lost the KAT trade definitively 3) got gift-wrapped a path to the finals 4) will regress to the mean on 3s 5) never have anything to do with anything 6) haven’t actually won any playoff games. Opponents just lost all 16.

Parade. Thursday. Manhattan.

This is actually insane. The patient facing tools are performing better than the clinician facing tools. Direct model access is a big deal. 🤯