Dan Lambert

The difference between a $10K contract and a $100K contract is which budget you're competing for. Why startups can land contracts that are 10x larger than incumbents: A large platform focused on serving HVAC companies captures ~1% of their revenue. For example, a typical HVAC company making $1M pays the platform $10k. A startup, also specifically targeting HVAC companies, captures 4-10% of their revenue. The same $1M HVAC company pays the startup $40-100k. The difference is that the big-player platform is just another software expense, while the startup enables companies to operate with fewer employees. Replacing work lets your product capture a payroll budget that's 10x larger. This shift redefines your startup’s entire approach, while traditional platforms focus mainly on selling more seats and subscriptions. You focus on one industry and learn its operations inside out. You become part of their team. Big cos can’t work like this b/c they can’t focus solely & completely on a single vertical problem. Small teams can… and they have to. I’m interested in vertical AI companies that control entire workflows and are built by small teams close to operational work.

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Hot take on AI's value as a product in our daily lives. 1. For most, AI is a nice-to-have, not a must-have It is impressive how AI creates content, generates spreadsheets, vibe-codes, fills CRMs and insurance claims, triages patients, classifies accounting transactions or mimicks human interaction. The wow effect disappears when you start using these capabilities intensively as part of your job. It is somewhat helpful, but not a dramatical improvement to your productivity, lest of all a replacement for a single human. For companies, productivity gains will be either wasted in longer coffee breaks (as has been the case with most software efficiencies in the past 20 years) or obtained via AI-disguised offshoring. 2. The intrinsic limitations of its foundations will make it hard to be really impactful in our lives AI is a set of algorithms involving statistical classification of data and prediction/generation based on available datasets. You should instinctively mistrust anyone pronouncing the "agentic" word. AI does not really "learn" or "think". No Colossus data center and smartly coded software running on it can ever get close to emulating the 86 billion neurons and 100 trillion synapses the human brain has. A self-adjusting or recursive algorithm can be described in metaphorical terms to make it more understandable and marketable, but a metaphor is not an identity. There will be improved, more efficient and adaptive AI algorithms for sure. We all have seen the improvement in AI videos in the past few years. But they will still be algorithms and unable to create, strategize, or read real-life scenarios and nuances. 3. It is not feasible to get rid of AI's dirty secret, the third-world training workers One million people work as AI trainers, tagging images, providing voiceovers and interacting with chatbots, making $1-10 / hour. This is not a transitory task that will be completed once all models are fully trained. As datasets evolve and models are expected to produce new outputs, further human training is necessary. AI cannot train AI without spiraling into poor human-grade outputs. I asked our chatbot friend Claude to run some math for me. Turns out 2 billion hours per year in productivity gains are directly offset by an equivalent number of annotator/trainer hours. 4. The real cake that core AI companies are chasing: the Internet itself i.e. marketing and content If all of the above is true, why are VCs pouring billions into core AI companies? It is a high stakes game, actually. Google has a near monopoly on search, with a market cap of $3.8 trillion and $400bn in revenue (of which 75% content/advertising). MarTech is $1tn in revenue. Social networks is $400bn. All of these can be won with AI. Content generation, search, advertising. Attracting search users to use chatbots instead. A $100bn investment in OpenAI would surely be a homerun if it fundamentally changes the world, but it's also ok if it only changes the Internet.

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Too many startups assume: 𝙩𝙝𝙚𝙧𝙚’𝙨 𝙖 𝘾𝙋𝙏 𝙘𝙤𝙙𝙚 → 𝙩𝙝𝙚𝙧𝙚𝙛𝙤𝙧𝙚 𝙩𝙝𝙚𝙧𝙚’𝙨 𝙖 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨. Reality is rarely that linear. Viability tends to unfold in fits and starts, shaped by payer coverage, provider workflows, and the real operational burden behind reliable billing. ⚙️📉 Inspired by Matt Kamen's excellent post on CPT adoption curves & the recent ACCESS discussion, we’re sharing our internal framework: 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 𝐀𝐬𝐤 𝐁𝐞𝐟𝐨𝐫𝐞 𝐁𝐞𝐭𝐭𝐢𝐧𝐠 𝐨𝐧 𝐚 𝐍𝐞𝐰 𝐁𝐢𝐥𝐥𝐢𝐧𝐠 𝐂𝐨𝐝𝐞 It goes deeper than payment policy — covering clinical and documentation requirements, enrollment and service mechanics, operational readiness, and the maturity of the CPT pathway. 🧠📋 If you’re evaluating a CPT-driven business model — or working with someone who is — comment “𝘾𝙋𝙏” below + DM me & I’ll share the document. 📄➡️ #startups #HealthcarePolicy #HealthTech #CMMI #ACCESSModel #Medicare #DigitalHealth

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Every operator, consultant, and banker with a network is realizing the same thing. Why advise on deals when you can lead them? Smart professionals are launching funds at record pace. The pattern is obvious. Healthcare executives launching biotech funds. Former operators starting B2B software funds. Industry veterans are tired of watching generalist VCs fumble deals in their space. Specialization beats generalization. Experience beats connections. Your track record speaks louder than your pedigree. Your network matters more than your alma mater. The old barriers to fund formation are dissolving. Technology platforms handle back office operations. Limited partners are diversifying beyond traditional institutional investors. The smart money is following the smart people. The result: A new generation of fund managers who actually understand the businesses they invest in. The question is not whether this trend continues. The question is whether you join it or watch from the sidelines.

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Today, I'm incredibly excited to announce the launch of our VOICE AI Platform from Beyond Physician, a patent-pending tech that uses deep audio analysis of physician expert interviews to understand their decision-making habits, which will impact the pharma, biotech, medical device, and overall healthcare industry. I was surprised when I first learned about the data-collection standards in healthcare, specifically that many companies relied on multiple-choice surveys. The responses are limited: A, B, C, or D... How can you reduce decades worth of a physician's knowledge to one of four answers? It was also shocking to hear the physician's perspective as well: despite surveys being "an easy way to make a quick buck," many physicians passed on them, not for the money, but because they felt cold and impersonal. Our early case studies yielded substantially richer contextual data, and the physicians literally stated they "loved this experience" of having the opportunity to share their perspective. Physicians aren't necessarily looking for a payday; they are looking for respect and confirmation that their opinions are actually making an impact. After repeatedly hearing that physicians were passing up paid surveys, despite the billions of dollars spent annually on this data collection, we started working on a solution that became our VOICE platform. I'll save the deep tech dive for another post, but I really enjoyed the opportunity to leverage my audio engineering background, which actually spans over 20 years, with my (brief) time in college as an Audio Engineering major, and even my time with Soundstr. This tech is strong, the analysis is extremely thorough, and the AI is real, not just a top layer on an existing LLM, which is why we have filed a patent, another exciting moment for our company. I look forward to creating a real, meaningful impact in healthcare with our new technology. Full press release below. Big thanks to our incredible team: Navin Goyal MD Marshall Kuremsky Christine Wallace Buffy Alegria Aaron Boggs and all of our other amazing advisors, partners, investors, and supporters. https://lnkd.in/gtnustVE

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The Signal Every Investor Should Pay Attention To When leading Silicon Valley investors like Vijay Pande (formerly of a16z Bio + Health) and Zack Werner launch a new firm—VZVC—focused exclusively on AI in healthcare, it’s not a coincidence. It’s a signal. A signal that elite capital is doubling down on healthcare AI in 2025, that the market sees real scalability at the intersection of automation, intelligence, and patient impact, and that the next generation of value creation in healthcare will come from AI-enabled efficiency and insight. Mission 3A HealthTech sits precisely at this intersection — where technical innovation meets real-world execution. We believe there is no better investment opportunity than healthcare AI. The sector combines long-term demand stability with massive efficiency gaps — and AI is finally capable of bridging them. As investors chase the next wave, we’re already ahead of it: identifying, validating and investing in these cutting edge companies. We are partnering with surgeons and health systems, and commercializing solutions that drive measurable impact. #HealthcareAI #VentureCapital #Mission3A #DigitalHealth #AI #MedTech #Startups #HealthcareAI #DigitalHealth #MedTech #Mission3A #VentureCapital #AIHealthTech #HealthTechInvesting #ArtificialIntelligence #StartupFunding #FutureOfHealthcare Tempus AI insitro Freenome Stryker PathAI Apple Butterfly Network, Inc. Lyten Medtronic Orthofix Treace Medical Concepts, Inc. Forma.ai Smith+Nephew Vizai Engineering OWKIN Kevin Cordell Trey M. Matt Hostetler Greg Berlet Patrick Fisher https://lnkd.in/eSmCCf_E

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Utah just became the first state to let AI renew prescriptions. No doctor visit. Four dollars. Done in minutes. A year ago, this would have seemed like a regulatory pipe dream. Now it's live. Here's what most people miss about this news: It's not about replacing physicians. It's about returning them to medicine. Physicians today spend 33% of their time on administrative tasks. Five-plus hours a week wrestling with insurance paperwork alone. Routine prescription renewals stack on top of that. Every minute spent on tasks AI can handle is a minute stolen from patients who need real clinical judgment. Utah's pilot signals something bigger. Regulators are starting to recognize that AI efficiency isn't a threat to care quality. It's a prerequisite for it. The future of healthcare isn't AI versus physicians. It's AI enabling physicians to be physicians again. https://lnkd.in/gJADnhai #HealthcareAI #FutureOfHealthcare #DigitalHealth #PhysicianBurnout

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