Daniel Hanover HIRING GREAT CV/ML ENGINEERS

Solve for information asymmetries! Architecture & Civil Engineering - Layout interpretation ~other industries: Healthcare - <Prescription> interpretation Financial Products - <Subject to market risks documentation> interpretation Loans - <Fine print> interpretation There’s going to be a slew of startups commercialising this year with a value prop of simplification using AI

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I've been seeing way more front desk AI automation startups that are targeting private practices. Some are founded by physicians and others by non physicians. Here's what they're both getting wrong about private practice SMB as a customer. 1. The persona willing to adopt AI automation is rarely looking to scale into a traditional private practice model with the traditional panel of patients. Their willingness to adopt is not related to their willingness to pay. Meaning you will not hit venture revenue scale with this customer. 2. The persona that is willing to scale into the traditional private practice model is not willing to adopt AI automation. Once they do scale they most likely will do so using traditional staff or traditional managed services, NOT AI AUTOMATION. Instead the staff or managed services will use AI, but not the practice itself. Meaning the TAM is a lot smaller if your only value is just an AI tool. I've seen startup after startup over the last 6+ years struggle with this issue. They'll encounter a few early adopters and get convinced that their excitement applies to the entire TAM of physicians when in reality, they are the outliers and the market consists ONLY of one of the two options listed above. #PrivatePractice

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As someone who’s sold SaaS to the US Healthcare industry during its transition to Value-Based Care, I’m seeing a familiar story unfolding with AI for SaaS. Remember when US Healthcare shifted from “Fee-for-Service” to “Fee-for-Value”? It was messy. Established players resisted because the old model's misaligned incentives were predictable and highly profitable—even if it wasn’t working for the system as a whole. Guess what? SaaS is at a similar crossroad. With Outcome-as-a-Service models gaining traction (thanks to AI), subscription stacking is becoming harder to justify. Buyers are demanding results—not just access—and the pressure is building to prove real ROI. Here’s what SaaS can learn from healthcare’s transition to value-based pricing: 1️⃣ Co-Creation Is Key: In healthcare, patients, providers, and payers had to collaborate to drive better outcomes. For SaaS, that means involving customers in co-creating AI features and value metrics. Deep feedback loops aren’t optional—they’re essential. Customers want to shape what they pay for and see the value clearly. 2️⃣ Post-Sales is the New Battleground: Healthcare’s success in value-based care relied on proactive care coordination and ongoing patient engagement. SaaS needs a similar shift. Customer success, onboarding, and post-sales service will be critical to ensuring customers see continuous value—and stick around. 3️⃣ Data is the Foundation: Healthcare had to adopt advanced analytics and data integration platforms to track outcomes. SaaS companies need to do the same. Think integrated dashboards that quantify impact like time saved, revenue uplift, and reduced churn in real-time for customers. The highly profitable “build it and they’ll pay for access” model is crumbling. The future of SaaS pricing is all about outcomes, and AI is accelerating that shift. I’m having fascinating conversations with SaaS founders and product leaders about how they’re navigating this transition—and I’d love to hear from you, too. How are you tackling this shift? Hit me up in the DMs or drop your insights below. #SaaS #AINative #OutcomeAsAService #ValueBasedCare #Innovation

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One thing I'm most proud of with DBOS is how simple it is to use. All you have to do to durably execute a workflow is add @DBOS.workflow() to the workflow and @DBOS.step() to each step. Do that and your workflow is crashproof, even if it takes many hours or days to run. You can call a workflow just like any other Python function--no special syntax required. DBOS runs entirely inside your program--there's no separate "workflow server." All data is stored in Postgres. You can deploy your app to DBOS Cloud with a single command: "dbos-cloud app deploy". It's completely serverless, automatically scales to meet your load, and bills only for the CPU time you actually use--you don't need to configure or manage cloud resources or pay for servers you aren't actively using.

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Today, I’m incredibly proud to announce a major milestone for PayZen: we’ve just closed a $232 million Series B round in equity and debt, led by New Enterprise Associates (NEA). This round includes $32 million in equity and a new $200 million credit warehouse from Viola Credit and a syndicate of insurance companies. I’m thrilled to welcome Mohamad Makhzoumi, NEA’s Co-CEO, as a PayZen board member! Partnering with the right investor at each stage of our company’s growth is both an art and a science (with a bit of luck thrown in). We were fortunate to find strong alignment with the NEA team in terms of business philosophy, mission, market, and strategy. With their extensive experience and stellar track record, I look forward to collaborating with the NEA team as we guide PayZen into the future. This funding will enable us to continue leveraging our AI-powered platform to tackle healthcare affordability. Our proprietary AI/ML models and seamless EMR/EHR integration simplify patient payments for health systems while making it easier for millions of patients to access and afford the care they need. We’re committed to driving innovation in the Revenue Cycle Management market and are excited to expand our affordable, customized healthcare payment options to even more Americans. This partnership with NEA brings back memories. Twenty-five years ago, I fondly recall pitching Webex Communications to NEA alongside my then CEO and mentor, Subrah. That investment certainly worked out for everyone! Time seems to fly, but it’s comforting to know that some things remain constant. I want to thank all the investors and individuals that supported us along the way (Viola Ventures, Omry Ben David, SignalFire, Chris Scoggins, 7wireVentures, Lee Shapiro, Alyssa Jaffee, Ido Vigdor). Mostly, I want to thank my team for raising the bar every day, creating magic and making all of this possible. #healthcare, #fintech, #affordability, #RCM,

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Did you know that the ACA covers 21M Americans? This makes the individual insurance market an incredibly large and stable risk pool. Oscar Health unveiled its 3 year strategy a few weeks ago and shared how we plan to build on our strong position in the ACA market. We believe ICHRAs (Individual Coverage Health Reimbursement Arrangements) can transform the health insurance landscape – we will bring our Oscar Magic to small and medium-sized businesses. By moving these employees to the individual market, we create a win-win: employees get more choice and differentiated plans, while employers have more control over their benefits expense (often a business’s second largest after salaries!). And we all win when we drive down rising health care costs. I’m so excited to see what we can do by bringing our Oscar Magic to more of the health care ecosystem!! See some highlights from Investor Day here:

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I recently spoke at the Healthcare x GenAI event hosted by HealthTech Hang. I discussed the nuances of building reliable GenAI products for healthcare. LLMs are unpredictable, but that unpredictability is a feature (not a bug). It's what makes them creative and generalizable. The thing to solve for isn't the predictability of outputs but ensuring that the *quality* and *accuracy* of AI outputs are predictable. This challenge is why we built Autoblocks AI, and it's why health tech companies trust us to deliver reliable AI solutions.

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We have a saying at Koa Health that Everything Product is Clinical and Everything Clinical is Product. While I can understand the sentiments here, and agree wholeheartedly that working in healthtech is different, I don’t feel posts like the one below are helpful. ✅ You of course should ALWAYS build an MVP - but minimally viable in healthcare requires ethics, safety, and compliance. ✅ Execute fast, Discover meaningfully. - things will and should be broken in our system, but the breaking requires close guidance and thoughtful approaches WITH clinicians. ‼️PLG is definitely more tricky in Healthtech but I don’t understand why this is even called out here. It’s irrelevant how growth should or should not happen as long as it’s ethical and in the best interest of health outcomes. 💡I can get on board with investing in the support of your users more than traditional tech - but again… I don’t see why this is a general statement about healthtech products. It’s based on the needs of your users. If tech can facilitate it effectively and safely, go for it. ✅ stages aren’t bad. Over promising and making unproven claims on stages is bad. Let’s focus on the root problem, not the forum.

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I'm looking for senior front-end engineers to build tools that enable healthcare providers to get paid fairly and quickly. https://lnkd.in/gXUzdCvJ At Anomaly we're solving one of the biggest problems in healthcare-- payments. We are on a mission to fix the broken payment system in healthcare. Despite billions of $ invested in EMRs, revenue cycle vendors, clearinghouses and insurance companies, the outcomes have only gotten worse for everyone (except...shockingly...insurance companies). Providers see 15%+ of all claims get denied and lose 3%-5% of net revenue due to fatal denials, millions of patients have care delayed and receive unnecessary bills, and we all end up paying for the $300+ billion in annual administrative waste that plays a big role in the double digit annual increases in insurance premiums. We are using healthcare expertise, modern ML techniques, and common sense to break through the crap and reinvent the way financial transactions work in healthcare. We are early in the process and have a lot of work ahead of us, but we have the best client partners, a big vision, backing from great investors, and an amazing team...if anyone can do it, we will. Please share and email me at [email protected] if you're interested

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Third in the series of articles about HEI and why it is important for #MedicareAdvantage plans to think about it now.

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I had the great pleasure of sitting down with a startup CEO, a medical professional, who wanted to get ahead of codebase health before her product went to the App stores... (stay tuned for a plug of her product) We came upon an analogy for understanding code metrics to health care metrics. I thought it was a great way to think about what we do at Sema and how we partner with technologists. There are three levels of understanding metrics about code, just like three levels of understanding patient information. The first level is the raw data. In health care, that could be a blood pressure reading. In code metrics, that could be the raw count of high-risk security warnings from Open Source code, aka CVEs. In both cases, we can make some general statements: it is generally better to lower your blood pressure; it is generally better to have fewer CVEs. But that guidance is quite generic. The second level is benchmarked results. In the health care example, that could mean blood pressure levels among men in their fifties. For code, that could be high-risk CVEs among tech companies that are at least 5 years old and 100-250 all-time developers. The trick is to get a comparison group small enough to be useful, without overfitting and missing the big picture. The question of specificity vs. generalizability is not an easy one. Benchmarked results are a big improvement over raw data, but it's still not enough. That's why a third level is needed: expert discussion. Of course in medicine that looks like a conversation with a health care professional. With code stats that looks like an Engineering expert, whether a sophisticated CTO, a Tech Operating Partner, or an external Advisor. The best experts, whatever hat they wear, know the details of their field while also being able to explain the results to a broad audience. That expert discussion leads to further contextualization of the results-- understanding the patient's family history / cholesterol levels / heart rate variability, or maybe the codebase is safely behind firewalls and for internal use only. Perhaps even more important, that expert can start shaping the improvement plan. What does that mean for Sema? At the raw data level, we have collected the broadest set of codebase health metrics for a deep and diverse set of software organizations. For benchmarked results, our Snapshot gives a ready comparison of codebases compared to organizations of similar size and stage. For experts, we are honored to partner with many outstanding experts, who can take the scan results combined with their own investigation and insights and guide their "patient" to the next level of success. I am the son of a computer programmer and a math teacher, so my heart (and genes?) will always be with looking at data to make things better. A proper approach to data-driven improvement covers all three levels.

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Hiring and working with excellent people is what makes starting a company so fun

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2 years ago, I signed my biggest client in healthcare software development. I quickly learned that the 'Minimum Viable Product' (MVP) approach can be a dangerous myth in this field. Here's why: Patient Safety Isn't Negotiable → Healthcare software must be reliable from day one. → An MVP that 'just works' isn't enough. → Bugs and glitches can lead to realworld harm. Regulatory Hurdles → Healthcare is heavily regulated. → An MVP that doesn't meet compliance standards can cost you more than just money. → It can delay product launch by months or even years. Trust and Credibility → Healthcare providers need to trust your software. → Releasing a barebones MVP can destroy that trust. → It’s hard to rebuild once shattered. Integration Complexity → Healthcare systems are complex and multifaceted. → An MVP that doesn’t integrate well can cause more problems than it solves. Longterm Vision → An MVP is often a shortterm solution. → Healthcare software requires a longterm vision. → Planning for scalability and sustainability from the start is crucial. So, what’s the alternative? → A Minimum Lovable Product (MLP) Focus on creating a product that not only meets but exceeds expectations. → Ensure it’s safe, compliant, and reliable. → Invest in thorough testing and user feedback. Healthcare is not just another industry. → It’s about improving lives and saving them. Don’t risk it with shortcuts. What are your thoughts? Have you experienced the downsides of the MVP approach in healthcare? Share your stories and let's discuss!

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I'm excited to share that I'm co-founding HealthSpark with my college classmate Stephen Grinich, and we were recently backed by Y Combinator! HealthSpark is empowering physical therapists to launch, run, and grow their own AI-native independent practice by automating their administrative tasks including insurance, scheduling, calls, texts, and charting. If you know any physical therapists, we'd love to get in contact! https://lnkd.in/gRFRknXz

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I advice 1-2 CEOs each week on how to select their CTO or founding engineer The average tenure of a startup CTO is < 2 years But the impact on the company - positive or negative lasts a long time after they are gone -> Early-stage companies lose momentum by choosing the wrong CTO So it is mission-critical to look for the right attributes in your first/next CTO: 1/ Hands-on capabilities Should rollup their sleeves and get into the dirty details from day#1 2/ Experience working with offshore teams Such CTO can handle cultural & language barriers much better 3/ Obsessed about creating value every week Huge red-flag if they focus on fancy tech And complex architectures or expensive tools 4/ Clearly connects with your mission Startups are a slog A clear connection with your mission goes a long way 5/ BONUS: Has some entrepreneurial experience Can empathize with the tradeoffs a CEO has to make every day If you need more help selecting your CTO DM me with the message “world-class CTO”

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Appreciate the #LeedsDigitalHealth shoutout Vladlen Shulepov! 🙌 Some very exciting and innovative digital health businesses listed here, well worth checking out.👇

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Halfway through our Y Combinator batch, over 60% of the startups in our cohort (including us) were stuck pivoting. That’s when Paul Graham flew in from England to talk about finding a great startup idea. Here’s what he told us: 1️⃣ Turn off the three ‘bad idea filters’: By turning off the ‘bad idea filters’ in your head, it instantly becomes easier for good ones to emerge. 1/ The sanity filter: Often, the greatest startups come out of ideas that originally seemed insane. So don’t shut down ideas because they seem impractical. For eg, when Airbnb started, no one ever thought people would let strangers sleep in their homes. 2/ The money filter: Money is important for a startup, but if you’re able to drive strong growth without generating revenue, don’t discard the idea. For eg: JustinTV (now Twitch), began with a guy live-streaming his life with a camera strapped to his head. There was no revenue stream initially. 3/ The schlepp filter: Don’t dismiss an idea just because it seems like too much work. For eg: Stripe had to handle unholy amounts of legal and regulatory work to get banks onboard their payments platform. Still, they did the hard work, and Stripe solved a problem that hundreds of their contemporaries were afraid to work on. Often, the impractical hard work becomes the moat that protects your startup from competition. 2️⃣ Don’t build for boomers   If you’re only building for boomers, your company will die with them. Whatever you’re building needs to become popular amongst the younger generation. If you’re a college student and you find a lot of your peers using what you’re building (and not just because they’re your friends), it could well be the start of something big. 3️⃣ Stop thinking all the best ideas are taken As founders, we often come up with an idea only to realize another company has already built it. We then find ourselves wishing that such other company didn't exist. You need to throw that mentality out the door. One quote I’ll always take away from PG’s talk is that there are billions of years of existence left. It would be practically impossible (and quite frankly depressing) for all the good ideas to run out by 2024. These tips really helped us zero in on what we’re building today. At our last startup, Desklamp, we’d spend weeks on end producing each feature launch video. During our pivot phase, PG’s talk inspired us to ask ourselves if we could automate that process using AI. That bold question led us to Clueso (YC W23): end-to-end AI automation for producing software videos for companies. #startups

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Hi everyone! I don’t share too often on here, but we’re at a very exciting moment at AptDeco, and I wanted to let you all in on it. AptDeco opened a community investment round and the response has been incredible. We’ve raised over $2M so far from institutional investors, customers and supporters. Nothing is more validating than customers doubling down with their own capital. And now, I’m inviting you, my network, to be part of our journey. When we started AptDeco, we set out to make buying and selling furniture easier. Over the years, many of our competitors have come and gone, but AptDeco continues to thrive. Why? Our technology, logistics and branding continues to set us apart and that's why major retailers including West Elm, Pottery Barn, La-Z-Boy, Article and 30+ more have partnered with us. The beauty with this investment round is that anyone can be an investor. Learn more and invest directly at wefunder.com/AptDeco.

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