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Tyson Lester, MBA, ChHC®, REBC®, RHU®
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Tyson Lester, MBA, ChHC®, REBC®, RHU®✓

@TysonLester

President @PolicyAdvantage | Insurance and ACA expert. Brand Dev, Strategy, AI & Tech. 3x @TheAmerCol alum— https://t.co/iD0hK60Pcj MBA w/ Distinction. Montana grown.

87.8K Following89.1K Followers18K Posts
  1. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Compliance isn’t just offering coverage, it’s about getting every detail right. How are you staying ahead of ACA requirements while avoiding costly surprises? can help you navigate complexity with clarity and strategy. 6 key insights: 1⃣🧩 Applies To Applicable Large Employers (ALEs): Only employers with 50+ full-time or equivalent employees must comply, but miscounting employees can trigger unexpected exposure. 2⃣⚖️ Two Distinct Penalties Structure: Penalties differ based on whether coverage is not offered at all or is inadequate, and they can scale quickly across employees. 3⃣💸 Affordability And Minimum Value Matter: Coverage must meet cost and value thresholds or employees may qualify for subsidies, triggering employer penalties. 4⃣📊 Reporting And Documentation Are Critical: Accurate filing (1094-C, 1095-C) and tracking are essential, as errors alone can lead to IRS penalties. 5⃣🧾 Hours Tracking Drives Eligibility Decisions: Full-time status is based on precise hour measurement (typically 30 hours/week). Inconsistent tracking of variable or seasonal staff is one of the most common compliance gaps that leads to unintended ALE exposure. 6⃣⏱️ Penalties Are Assessed Monthly, Not Annually Only: ACA penalties are calculated on a monthly basis, meaning even short periods of non-compliance can accumulate significant liability over the year. Timing errors in coverage offers or eligibility changes can quietly increase total exposure. #EmployeeBenefits #HRStrategy
    PolicyAdvantage.com @PolicyAdvantage
    The #ACA (Obamacare) "employer mandate" applies to Applicable Large Employers— an important video if you're an ALE. At we help large employers navigate these very important provisions. Connect with us online today. #HealthInsurance #HR #InsurTech
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  2. PolicyAdvantage.com@PolicyAdvantage
    The #ACA (Obamacare) "employer mandate" applies to Applicable Large Employers— an important video if you're an ALE. At we help large employers navigate these very important provisions. Connect with us online today. #HealthInsurance #HR #InsurTech
    Download
    031318.7K
  3. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    AI just turned a 120-page health insurance PDF into a one line answer— what’s the first thing you’d want to know about your own plan? 4 key insights on putting LLMs to work reading your policy: 1⃣🔄 Turning Unstructured Documents into Structured Data: Insurance policies are long, dense PDFs that people rarely read in full. LLMs can parse a 120-page coverage document and extract the details (copays, deductibles, coverage rules) into a clean, usable format. This is the core capability that makes everything else possible. 2⃣💵 Turning Policy Language into a Real Price: Once the data is structured, the answer becomes a concrete number, like “your copay is $30,” rather than legalese. LLMs bridge the gap between what the contract says and what you’ll actually pay. 3⃣🪄 Hiding the Complexity: The heavy lifting happens behind the scenes, and the customer just sees a simple answer. The best use of an LLM here is often invisible; it does the translation work so the experience feels as easy as any other consumer product. 4⃣🔍 Creating Price Transparency That Didn’t Exist Before: As the post points out, there are very few places in healthcare where you can see a price before you buy. By making policy details readable and queryable at scale, LLMs make it possible to know your costs upfront, which was previously impractical. #HealthTech #ConsumerHealth
    MTS @MTSlive
    General Medicine CEO @tjparker explains how AI can read a 120-page insurance policy and tell you exactly what you'll pay for healthcare before you buy it: "We couldn’t actually do the pricing without LLMs. We’re literally pulling down a 120-page coverage of benefits PDF from your insurance company, and we are using LLMs to turn that unstructured data into structured data so we can price these services for you." "Under the hood, that manifests as, here’s your copay, it’s $30. To the customer, it just works like everything else." "How did that happen before? It didn’t. There’s very few places you can see a price in healthcare before you buy things, which is an insane thing to say out loud." @GeneralMedicine
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  4. MTS@MTSlive
    General Medicine CEO @tjparker explains how AI can read a 120-page insurance policy and tell you exactly what you'll pay for healthcare before you buy it: "We couldn’t actually do the pricing without LLMs. We’re literally pulling down a 120-page coverage of benefits PDF from your insurance company, and we are using LLMs to turn that unstructured data into structured data so we can price these services for you." "Under the hood, that manifests as, here’s your copay, it’s $30. To the customer, it just works like everything else." "How did that happen before? It didn’t. There’s very few places you can see a price in healthcare before you buy things, which is an insane thing to say out loud." @GeneralMedicine
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  5. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    New. "Dallas Cowboys Cheerleaders Union: What Employers Need to Know About Pay, Benefits and Risk." The Dallas Cowboys cheerleaders already got a huge WIN this week: unionization. What could be next for their pay, benefits and risk? ✅ What Is Confirmed So Far ⚖️ A Decade of Wage Disputes Sets the Backdrop 🏷️ Employee or Contractor? Classification Drives Everything Else 🩹 Workers' Compensation: The Injury Question, and a Texas Twist 🛡️ Employment Practices Liability: Where Wage Claims and EPLI Meet 🤝 Benefits at the Bargaining Table: What It Might Look Like 📋 What Business Leaders Should Take from This 🧭 Where Advisory Support Fits #NFL #EmployeeBenefits #RiskManagement
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  6. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Scaling & reinvention through agentic AI. @PodiumHQ (via @ericwilliamrea) reached $150M in AI ARR in 2.5 years, a third of the time it took the first go-around. With 20K agents working for customers, they’ve stopped selling tools and started delivering results— what would your company deliver if agents did the work? 1⃣🔄 Disrupt Yourself Before Someone Else Does: Podium had a $100M+ software business and rebuilt around AI anyway. The second $150M took 2.5 years instead of 8. 2⃣🤖 Sell the Work, Not the Software: Podium’s 20,000 AI agents do the work for customers and have helped generate over $13B in revenue. Value is measured in outcomes, not features. 3⃣🏗️ Own the Whole Stack, From Agent to System of Record: New industry operating systems put agents on top of the data layer. Customers now run their entire business on it, which makes it far stickier than a point solution. 4⃣⚡ The Product Is Only Half the Reinvention: Podium also rethought how it builds, sells, and serves, essentially a second startup inside the first. It did all of this while staying profitable and cash-flow positive. #AgenticAI #EnterpriseAI
    Eric Rea @ericwilliamrea
    We built a $150M ARR business twice. The first time took 8 years. The second took 2.5. Today, Podium crossed $150M in AI annual recurring revenue. Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building. And we decided to start over. The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete. As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it. When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow. But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers. Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers. We massively underestimated what we'd signed up for. We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium. Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated. When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business. We effectively started a second startup inside an already successful company. And we're still at the very beginning. Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them. And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades. Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big. In the age of AI, you can either disrupt your own company or wait for somebody else to do it. I'd rather do it ourselves.
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  7. Eric Rea✓@ericwilliamrea
    We built a $150M ARR business twice. The first time took 8 years. The second took 2.5. Today, Podium crossed $150M in AI annual recurring revenue. Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building. And we decided to start over. The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete. As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it. When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow. But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers. Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers. We massively underestimated what we'd signed up for. We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium. Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated. When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business. We effectively started a second startup inside an already successful company. And we're still at the very beginning. Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them. And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades. Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big. In the age of AI, you can either disrupt your own company or wait for somebody else to do it. I'd rather do it ourselves.
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    16886816352K
  8. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    6G connectivity aims to make the physical and digital worlds indistinguishable in real time— what happens when AI is built into the network itself, not just running on top of it? 4 key insights; visit to follow along: 1⃣🧠 Networks That Learn, Not Just Carry: With AI inside the network, it can optimize, heal, and adapt itself in real time instead of waiting for engineers to configure it. The network shifts from a static pipe to a living system. 2⃣📡 Sensing Becomes Understanding: When radio signals double as sensors, AI can interpret what they reveal about movement, environments, and context, not just move data. Connectivity becomes awareness. 3⃣🌱 Intelligence Makes Efficiency Possible: AI can predict demand and power down idle capacity, so more performance doesn’t have to mean more energy. Smarter networks can also be greener ones. 4⃣🔐 Trust Has To Be Built In: If AI makes decisions inside the network, transparency and reliability become part of the infrastructure itself, not an afterthought. The more the network decides, the more trust matters. #FutureOfTech #Innovation
    6G Flagship @6Gflagship
    In 2015, many doubted there would ever be a 6G. In 2018, Oulu started the world's first 6G research programme anyway. New 6G Waves looks back at how it's turned out. Out soon! #6G #6GFlagship #6GWaves
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  9. 6G Flagship@6Gflagship
    In 2015, many doubted there would ever be a 6G. In 2018, Oulu started the world's first 6G research programme anyway. New 6G Waves looks back at how it's turned out. Out soon! #6G #6GFlagship #6GWaves
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  10. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Tyson Lester, MBA, ChHC®, REBC®, RHU®
    RT @ELOIZA19: AI is so helpful until it gives me an answer with the confidence of a man who has never been wrong
    Tyson Lester, MBA, ChHC®, REBC®, RHU® @TysonLester
    Human/AI collaboration is accelerating— but it's not the AI models with the greatest capabilities that are winning. It's the the people who know what to ask, what to doubt, and what to decide. Let's break-down the "Collaboration Gap."
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  11. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Human/AI collaboration is accelerating— but it's not the AI models with the greatest capabilities that are winning. It's the the people who know what to ask, what to doubt, and what to decide. Let's break-down the "Collaboration Gap."
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  12. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Research shows "adoption and implementation" are some of the biggest challenges working with AI— especially for small orgs. What’s been your biggest hurdle getting AI to stick? 4 key insights; full @McKinsey article: 1⃣🧩 Adoption Is Everywhere, Value Is Not: Fewer than 10% of organizations have scaled AI in any function. Layering AI onto fragmented data and manual processes just automates complexity. 2⃣🚀 Growth Champions Rewire Workflows End to End: 71% of high-growth companies raised AI investment by double digits in 2026, versus 25% of the rest. They win by redesigning core sales workflows around agentic AI, not by rolling out more tools. 3⃣🤝 Inconsistent Information Is Why Buyers Leave: Conflicting messages across teams are the number one reason B2B buyers switch suppliers. Helping every seller perform like your best one is now a competitive edge. 4⃣💸 Budget $3 Of Change Management Per $1 Of AI: Most companies flip that ratio, and it shows. Value only appears when AI changes what sellers do every day, so adoption has to be designed in from day one. #EnterpriseAI #DigitalTransformation
    McKinsey & Company @McKinsey
    Most B2B companies are experimenting with AI. Growth leaders are redesigning the commercial playbook around it. The result: better opportunities, smarter decisions, and stronger customer outcomes.
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  13. McKinsey & Company@McKinsey
    Most B2B companies are experimenting with AI. Growth leaders are redesigning the commercial playbook around it. The result: better opportunities, smarter decisions, and stronger customer outcomes.
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    825849.3K
  16. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Tyson Lester, MBA, ChHC®, REBC®, RHU®
    RT @Eli_Krumova: Thank you for flagging that, @TysonLester. Keeping function intact while watermarking binders is a practical necessity as design tools become easier to use. #AI #LLMs #Robotics
    Tyson Lester, MBA, ChHC®, REBC®, RHU® @TysonLester
    @Eli_Krumova @GoogleDeepMind @dinisguarda 📈 Function-preserving watermarks on binders is exactly the kind of tooling the field needs as design tools get easier to use— appreciate the mention, @Eli_Krumova!
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  18. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    October 2026 report via @Peterson_HTI: "Driving Adoption of High-Value AI in Healthcare" courtesy @chrissyfarr. Why does the same technology help in one part of healthcare and backfire in another? 4 key insights below; full report: 1⃣🔁 AI Amplifies Existing Incentives: Today’s system rewards billing and documentation, so administrative AI is mostly adding activity and cost. AI scribes and prior authorization tools are spreading fastest, but there’s no evidence yet that they lower cost per claim. 2⃣🩺 Clinical AI Should Target Care Gaps First: Hypertension and mental health are the best early targets because care is hard to get and outcomes are measurable. AI can monitor patients between visits, and clear endpoints make it possible to track safety and performance. 3⃣💸 Fee-for-Service Doesn’t Fit Clinical AI: AI scales at near-zero marginal cost, so paying per use invites runaway volume. Outcome-based payment, like CMS’s ACCESS model launched in July 2026, is the best starting point, with rates that adjust as evidence and scale grow. 4⃣🧭 Payment Is Only the Start: Lasting change also needs better evidence, updated licensure and liability rules, smarter purchasing, and redesigned care delivery. These four domains have to move together, or AI just gets layered onto broken workflows. #HealthcareAI #HealthTech
    Christina Farr @chrissyfarr
    Health plans should: Publish machine-readable medical policies and escalation pathways to allow providers (and AI tools) to identify requirements before submission. And share clear, published rationales! Agree so strongly!
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  19. Christina Farr✓@chrissyfarr
    Health plans should: Publish machine-readable medical policies and escalation pathways to allow providers (and AI tools) to identify requirements before submission. And share clear, published rationales! Agree so strongly!
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  20. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    🔵 "We help individuals and families find coverage that protects what matters, at prices that makes sense." -Marketplace Health Plans -Family Coverage -Dental & Vision -Homeowners, Condo, & Renters -Landlord -Auto, Marine, & RV -Pets And more. #Insurance
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  21. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    Signs of time times. Economists are winning Nobel Prizes for effective management of global economic volatility. Geopolitics, climate, inflation, pandemics, business disruption, and more— it's a "risk on" world. How are you mitigating volatility? 1⃣📉 Economic Volatility Can Be Managed: Better economic models help policymakers understand and moderate the peaks and troughs of economic cycles. 2⃣🛒 Household Behavior Matters: Robert Hall’s work on consumption decisions helped economists better understand how people make spending choices over time. 3⃣🏢 Pricing Decisions Shape the Economy: Michael Woodford’s research on how businesses set prices helped strengthen the framework for understanding inflation and monetary policy. 4⃣🧭 Credible Policy Requires Communication: Economic policy isn't just about pulling levers. Explaining decisions and shaping expectations can influence how households and businesses respond. #Macroeconomics #EconomicPolicy
    The Economist @TheEconomist
    The Nobel prize committee credited the two winners with rebuilding macroeconomics on “microfoundations”. We explain why this was an intellectual break from the past Photo: Reuters
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  22. The Economist✓@TheEconomist
    The Nobel prize committee credited the two winners with rebuilding macroeconomics on “microfoundations”. We explain why this was an intellectual break from the past Photo: Reuters
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    6187031.2K
  23. Tyson Lester, MBA, ChHC®, REBC®, RHU®✓@TysonLester
    AI is moving from insurance’s edges to its core engine— which part of the value chain will it change most? 4 key insights below, full @FGraillot article: 1⃣🤖 AI Is Spreading Across Insurance: Incumbents like AXA and MAIF are rebuilding their roadmaps around AI, and nearly every week another insurer launches an offer on ChatGPT. 2⃣📈 30% Of InsurTech Deals Are AI-First: Since January, almost a third of all European InsurTech deals went to startups with AI at the core of their value proposition. 3⃣🧮 AI Is Moving Toward The Core Of Insurance: After claims and distribution, startups now build AI for actuaries, underwriting, product design, risk modeling and prevention. As the ecosystem matures, it gets closer to the engine of insurance. 4⃣🚀 AI-First Insurers Are Coming: In the US, new insurers, brokers and MGAs built on AI infrastructure already compete head-on with incumbents. If the US is a proxy for what’s next, Europe should see them soon. #Fintech #VentureCapital
    Florian Graillot @FGraillot
    AI is spreading across every section of the insurance value chain. >>
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  24. Florian Graillot@FGraillot
    AI is spreading across every section of the insurance value chain. >>
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