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When an investor asks about product-market fit in MedTech, they are not asking whether doctors like the product or whether it worked in a pilot. They are asking whether the early commercial signals are specific enough to underwrite the next stage of capital, and whether they believe you can achieve the next set of critical milestones with the runway that capital provides.What Investors are Really Looking ForIn most B2B categories, revenue is treated as the clearest measure of product-market fit. Once customers are paying at a rate that supports the model, the fit is largely taken as given. MedTech does not work that way. Revenue is a lagging indicator. Multi-stakeholder buying, long sales cycles, reimbursement uncertainty, and the distance between clinical validation and budget authority all mean a company can show real clinical interest long before meaningful revenue appears. Investors know this, so they look for earlier, more specific signals of commercial progress.Stifel Venture Banking noted in mid-October 2026 that commercial readiness is now part of the financing story by Series A and often earlier. Investors want a clearer view of the buyer, the reimbursement pathway, clinical workflow, and the path to meaningful revenue alongside the clinical and regulatory story. Vikram Chaudhery, Partner at Genoa Ventures, described it this way: “The focus of an underwrite used to be technical and scientific feasibility and the regulatory roadmap. You still asked about reimbursement and go-to-market, but a rudimentary answer was good enough.” He added that questions about buyer and economics can have great answers in a conference room, but “the field is the only real litmus test. When spend is theoretical, everyone is a billionaire. When you have to part with dollars, stakeholder alignment becomes the driving force and intentions reveal themselves.” Martyn Eeles made a similar point in his May 7, 2026 HealthVC note: “Clinical value is not commercial value.” Investors are increasingly asking whether the company understands the system around the product, not only whether the product works.7 Red FlagsIn Seed and even Series A rounds, the real test is whether you can speak to a core set of risks with enough specificity to convince an investor that the market risks are surmountable and you know how to execute. Specifically:<ol><li>Economic buyer clarity. Who has budget authority, and has that person already engaged in a conversation that involves real spend or a path to it? A clinical champion who likes the product is useful, but investors treat it as incomplete until the economic conversation has started. </li><li>Paid pilots or specific LOIs. Specialist investors have grown skeptical of vanity LOIs that list a hospital or system without naming volume, price, or what converts the interest into revenue. They often call the signatory. A paid pilot under a narrow, compliant scope is stronger still because it shows willingness to pay while generating evidence. </li><li>Reimbursement Clarity. Concrete progress in at least one market, whether that is an engaged payer conversation, a coding strategy with dates, or a clear view of the pathway and the capital required to advance it. Investors do not expect the pathway to be finished. They expect the founder to know which questions matter and what it will cost to answer them. </li><li>Feasible economic model. Early willingness-to-pay signals, budget-impact thinking, or directional feedback from purchasing or value analysis teams. When real dollars enter the conversation, misaligned incentives become visible, and investors want to see that the founder has already encountered and understood them. </li><li>Conversion or expansion signals. Evidence that a first site is moving from trial to ongoing use, or that a second site is looking more like a repeat than a custom project. A pipeline full of pilots can look active. Investors want to see whether any of them are turning into paid, expanded, or embedded relationships, or at least a documented path for how that happens. </li><li>Realistic timeline assumptions. These show up in the model and in diligence questions about how long it takes to get from first conversation to decision, how much physician or operational education is required, and whether the product fits existing workflows or adds net burden. Conference-room answers are discounted. Field-tested ones are not. </li><li>Initial market clarity. Investors notice when a company presents too many markets, use cases, or buyer types at once. They are asking where the company should start, why that starting point is the strongest one, and what it proves about the larger opportunity. Breadth without a clear first investment case reads as unfinished thinking.</li></ol>Don't think about this as an ironclad checklist you have to meet before you can raise. Think about it as a test of conviction - can you speak to each with enough clarity and specificity that investors will believe you understand and know how to approach and mitigate each risk. Which risks are known, which are still open, and whether the next round of capital will fund progress against the open ones. Reference calls and data-room review often test the same points. Investors speak with customers, advisors, and other market participants to see whether the founder’s description of traction matches what the market will confirm. Gaps between the two can stop an investor conversation cold.How to pressure-test it yourselfReplay the last two or three commercial conversations you've had. For each one, ask yourself (1) do I understand the buyer map; (2) is the reimbursement or business model clear; and (3) can I map out specific next steps that will lead to a successful close? Look at whether any site is showing expansion signals and whether your assumptions on sales cycle length and implementation schedules actually match what you're seeing in the field. If you can't answer, or if the answers are weak, you won't survive the diligence process. Instead, take a step back, clearly identify the gaps in the answers and do the work to fill them before you ask investors to trust you with their money.The 7-Lever Self-Assessment is built for companies at this stage: early validation signals that still need to be converted into commercial foundations investors will fund. It walks through the buyer, economic, workflow, and evidence questions that decide whether early interest becomes a motion that supports the next round. If the results point to specific gaps you want to work through, book a strategy call, and we can talk about how to help you close those gaps.

How MedTech Investors Test Product-Market Fit

TL;DR: Early traction is when it is easy for MedTech teams to stop watching the thing that produced it. The first commercial wins change how the company operates. You have a few dozen live sites and a real pipeline, and the people on the team are no longer spending their week trying to figure out whether the thing works. The product, sales, clinical, and finance teams are all tracking against their KPIs.&nbsp;The question that often starts to get overlooked is whether the original PMF continues to hold.That is the shift too many teams miss. Product-market fit in MedTech is not a box you check after the first paid sites come online. It is a living condition. Clinical value, workflow fit, economic proof, and the willingness of a multi-stakeholder buyer to keep saying yes can all drift while revenue is still moving in the right direction. By the time adoption starts to feel like a harder slog, the damage has usually been accumulating for months.Why the discipline fades Early on, the constraints do the work for you. Runway is short, investors want proof that a real problem exists for a defined set of users, and the founder is in the accounts hearing the friction before it shows up in a dashboard.Once bookings appear, attention moves to the metrics the board can see every month: pipeline, close rate, headcount against plan. Fit gets treated as already solved. Teams assume that if they execute harder, with more reps, more features, and more pilots, the early resonance will persist on its own.It rarely does. In a multi-stakeholder sale, the signal gets noisier as you add sites. A handful of engaged clinical champions gave you a clean read. A few dozen hospitals, with different specialties, IT environments, and Value Analysis Committee habits, will not. Fit becomes easier to ignore until expansion stalls, cycles lengthen, or margins compress.Sean Ellis’s old test is still useful here, even if you never run the survey formally. When 40% or more of users would be “very disappointed” if the product disappeared, you have a strong signal. Below that, growth tends to be fragile. The point is not the number. The point is that fit can be measured, and it can weaken after you thought you had it.What changes when nobody owns the whole view PMF is not a departmental metric. Product can ship the roadmap and still dilute the original promise. Commercial can hit bookings by selling into a persona the workflow was never built for. Clinical can fill a journal queue that does not answer the economic questions the next committee will ask. Finance can watch unit economics after the damage is already in the cohort.Ben Horowitz named a software version of this more than a decade ago: “The only thing that will wreck a company faster than the product CEO being highly engaged in the product is the product CEO disengaging from the product.” In MedTech it happens one layer out. The live question is not only whether the product stays coherent. It is whether the original clinical, workflow, and economic fit still holds once each team is optimizing its own number.Ultimate accountability still belongs with the CEO. That does not mean the CEO runs every implementation. It means someone at the top is still looking across those local wins and asking whether the company is solving a painful enough problem for the people who have to live with it. Customer success and implementation usually see the erosion first, because they are closest to whether a first site expands or quietly stalls. If those field signals have no path into an executive conversation, they die in a ticket queue.Leading indicators of PMF erosion It rarely arrives as a single bad quarter. You notice that time to value is stretching, or that it varies wildly from site to site. The first accounts still like you and are not pulling the next ones. New opportunities need a custom evidence pack every time. The founder is still on the late-stage calls because the story only holds when the person who discovered the problem tells it, and implementation still needs heroics from the original team.None of that reads as a miss on a functional dashboard, because those dashboards measure activity. They were never built to tell you whether fit is intact.This is also where the Adoption Gap comes back, even for companies that thought they had crossed it. Crossing it once, with a small set of engaged sites, is not the same as keeping it crossed as volume and complexity rise. Growth can hide a soft landing inside the first accounts for a long time.What to keep watching You do not need a new operating system. You need a short, recurring look at leading signals instead of waiting for revenue to explain itself. Ask whether new sites are reaching useful value on a timeline the buyer will tolerate, and whether that timeline is stable as you add volume. Ask whether expansion inside existing accounts is getting easier or harder. Ask whether the core story is still true for the personas you are now selling to, or whether commercial has drifted into a neighboring use case because it was easier to close. Ask whether the evidence you are generating still matches what the next committee and the next payer will demand. Ask whether unit economics at the account level are improving as the process gets more repeatable, or whether each new site still requires the same white-glove cost.When pressure mounts, the reflex is to sell harder. Sometimes that is the right call. Sometimes the pipeline is soft because the fit has slipped and more activity will only add expensive noise. The useful pause is to separate those two problems before you staff up.A lightweight review is enough if it is real. A monthly cadence is appropriate once you have a repeatable commercial motion. Product, commercial, clinical, and whoever owns the post-sale experience should be in the same conversation, looking at the same leading indicators, with the CEO still accountable for the whole. Treat the health of fit as a visible executive metric next to pipeline and margin, not as a workshop you ran last year.A short pressure test If you have first commercial wins in the books, these questions usually tell you more than a revenue slide:<ol><li>Who at the executive level is responsible for the health of product-market fit across the company, not just inside one function?</li><li>Can someone other than the founder explain why the last three wins looked the same, and why the last stall looked different?</li><li>Is time to value getting shorter and more consistent, or longer and more variable as you add sites?</li><li>Are first accounts expanding because the workflow earned it, or sitting still while the team hunts net-new logos?</li><li>When a new committee asks for proof, how much of the package already exists versus how much has to be built from scratch?</li><li>If you stopped founder-led selling next quarter, would the motion still produce the same quality of customer?</li></ol>Honest answers here are usually enough to see whether you are protecting fit or assuming it.The companies that keep growing without spending years repairing the foundation treat this as permanent work. They do not wait for churn or a painful board meeting to discover that the early resonance did not survive the org chart. Does this strike a chord? The free 7-Lever Self-Assessment is built for this window: first commercial wins on the board, and a real question about whether the underlying fit is still strong enough to scale. It gives you a readout of where the gaps sit and what to put first. You can get it free through the form on the <a data-mce-href="https://growthplane.com" href="https://growthplane.com" target="_blank" rel="noopener">homepage</a>. If you want to walk through the results or pressure-test the next 6–12 months, I’m happy to do a focused strategy conversation. Hit the Book a Call button at the top of the page.

Protecting Product-Market Fit

Diverse healthcare team collaborating around conference table reviewing financial reports and performance metrics on screen

Tell me if this sounds familiar - you feel like you've had a successful pilot, the champion is happy and the clinical data looks strong. Someone on the hospital side says the next step is value analysis, and the room gets quiet. Everyone nods like that is a paperwork step. It is not.In my experience, that is the moment a lot of companies discover that, while they have strong clinical interest, they're completely unprepared to navigate the Value Analysis Committee. The pilot proved the product can work in one setting with one motivated user. The committee is being asked to approve spend, workflow change, and risk for the institution. Those are different jobs.This is the Adoption Gap in its most concrete form. Product-market fit in MedTech is not the same as in B2B SaaS. A hospital can like the product and still refuse to buy it. If the committee will not approve it, you do not have fit yet, no matter how strong the early cases look.What the committee is actually doingValue Analysis is a formal, multi-disciplinary review. The group is usually some mix of supply chain, finance, clinicians, quality, and operations, sometimes with IT or clinical engineering in the room. They are conservative by design. They care about total cost of care, not only unit price. They want clinical evidence, safety, real-world outcomes, and a clear argument for why this is better than what they already have, including the cost of switching.The process often takes three to nine months, sometimes longer. Requests for more data are normal. A no is common, and it can be sticky. You do not get unlimited retries with the same thin package.That is why clinical enthusiasm from the pilot champion is such a poor predictor of approval. The champion is answering “does this help me do the case?” The committee is answering “can we defend this purchase, this workflow change, and this ongoing cost?” If you only prepared for the first question, you will feel the second one as delay.The path is shorter if you pick the right first siteThe mistake I see most often is treating the first VAC submission as a volume play. Teams pick the biggest logo, or the system that would look good on a slide, and then invent the package under deadline.I would start somewhere more manageable. Use the account where you already have a real clinical relationship and honest access to how that hospital buys. Before you write anything, ask the champion who else has to say yes, what the last similar product had to submit, how long review usually takes, and what killed the last request that looked a lot like yours. You can learn more in two of those conversations than in another month of polishing slides.You also need a map of the buying group, not just the user. The end user cares about performance and workflow. Supply chain and finance care about budget impact, contract terms, and total cost. IT and operations care about integration, training load, and disruption. An executive sponsor cares whether this lines up with quality goals or service-line priorities. Department managers can slow you down even when they cannot sign. If you only stay close to the person who ran the pilot, you will meet the rest of them for the first time inside the review.Build the package from the pilots you already haveMost teams do not lack data. They lack the right data, organized for a buyer who is not the investigator.During the pilot you probably captured clinical performance. What usually never got written down is the operational and economic residue: minutes added or removed from a case, extra staff required, length of stay, complication or rework rates, wasted consumables, time to get a new user productive. Those numbers do not need to be a published health-economic model on the first pass. They do need sources, a baseline, and an honest statement of what you measured versus what you inferred.Before you chase a new study, separate three piles:<ol><li>What you can pull from current sites if you go back and collect it properly.</li><li>What you can only get from the next implementation if you instrument it now.</li><li>What you will not have in time for this committee and should not pretend you have.</li></ol>I would rather see a short, sourced package with clear gaps than a long deck that treats directional estimates as proof. Committees notice the difference. So do the people inside the hospital who have to defend you after you leave the room.What belongs in the first formal packageThere is no universal template. Hospitals vary. The first package still needs to answer the same handful of questions in language a non-specialist can follow.<ul><li>Regulatory status and labeled use, bounded tightly. If the committee’s intended use sits outside what you can claim, say so early.</li><li>Clinical evidence matched to the use they would actually buy, not every study you have ever run.</li><li>Outcomes from real use that touch cost and operations, even if the sample is small, with methods visible.</li><li>Implementation burden: training, IT, sterile processing, storage, support, who owns what after go-live.</li><li>A comparison to the current alternative that includes switching cost, not only device price.</li><li>A two-page briefing for people who will not read the appendix. If finance and supply chain cannot repeat your argument without you in the room, the package is not done.</li><li>Treat that first submission as a learning cycle. Capture every question they asked, every document they requested, and every place they stalled. The goal of package one is not a perfect win rate. It is to stop building the argument from scratch on the next account.</li></ul>Where teams get stuckA few patterns show up so often I now look for them.<ul><li>Evidence collection stayed almost entirely clinical. The team has sensitivity and specificity, or a case series, and almost nothing on time, labor, or avoided cost.</li><li>Every new opportunity restarts the research. Nobody owns a reusable set of claims, sources, and exhibits.</li><li>VAC work lives in hallway conversations. There is no named owner, no date for a first formal package, and no list of what that hospital actually requires.</li><li>The economic story is still a clinical story with a price slide attached.</li><li>The process looks interesting but delayed for months. That delay is usually an unresolved issue in budget, authority, workflow, or evidence, not a scheduling problem.</li></ul>When I see several of those at once, I tell teams to pause the hunt for the next logo and finish one complete package against a real committee calendar. Adding pilots on top of an empty commercial file makes the Adoption Gap wider.How to tell you are actually movingYou do not need widespread approvals before you can say the path is working. A few signals are enough.<ul><li>You can describe the typical review process, timeline, and decision-makers at your priority accounts without guessing.</li><li>You have written health-economic language for the committee, not only for clinicians.</li><li>You have one formal package assembled for a hospital where the clinical relationship is real.</li><li>You know which evidence gaps matter for the next twelve to eighteen months, and you are collecting against that list on live sites.</li><li>Someone other than the founder can explain the economic case without inventing it in the meeting.</li></ul>If those are missing, more pipeline will not fix it. The committee will keep asking for the same things you did not build.A successful pilot is still an invitation. The commercial event is whether a hospital can approve the product, install it without heroics, and defend the spend. That is the work sitting between the last case and the first real purchase order.If you want a structured read on where the gaps are before you assemble that first package, the free 7-Lever Self-Assessment is the starting point we use with teams in this exact spot. It will not write the submission for you. It will show you which parts of the commercial foundation are still missing. If you want to walk through the results and the first-account plan with us, click the Book a Call button to schedule a 30-minute strategy conversation.

From a good pilot to a Value Analysis package

<h3>Why Seed Stage MedTech Companies Stall After Their First Pilots</h3>I keep seeing the same pattern.A seed or small Series A MedTech company lands two or three solid pilots. The clinical feedback is positive. A couple of sites are using the product. The team feels momentum. They start talking about early traction and begin hiring or raising with that story.Then the next six to nine months feel strangely flat. Pipeline conversations stretch. Value Analysis Committee discussions stall or request more data that doesn’t exist in usable form. The two happy sites stay happy but don’t turn into references that open doors elsewhere. Founder-led sales still carry almost every deal. Revenue stays lumpy or nonexistent.This is the Adoption Gap in action.Early pilot success proves that something can work under controlled conditions with engaged users. It does not prove that the solution will clear a Value Analysis Committee, integrate cleanly into existing workflows without constant hand-holding, generate measurable economic or operational outcomes that the hospital cares about, or create references who will actively advocate for you with peers. That distance between clinical proof and repeatable multi-stakeholder adoption is the gap most teams underestimate.<h3>What pilot success actually buys you </h3>A successful pilot is real progress. It is also incomplete progress. Most teams treat it as the main signal that product-market fit is arriving. In practice it is only the starting point for the commercial and operational work that has to come next.You still need reusable evidence that speaks to the questions budget holders and VACs actually ask. You need a value story stable enough that someone other than the founder can deliver it. You need a small set of reference customers willing to speak about measurable results. You need clearer mapping of the full set of people who can slow or stop adoption inside a hospital. Without those pieces, every new opportunity starts from near zero.When companies keep running more pilots instead of building these foundations, the pattern becomes familiar: more data requests, longer cycles, and little movement toward predictable revenue.<h3>Where the stall usually shows up</h3>I see the same weak spots surface again and again.Evidence stays too clinical. Teams collect outcome data that impresses clinicians but does not address the economic or operational questions that determine whether a hospital will actually buy. Every new opportunity requires building evidence from scratch. There is no reusable package and no clear view of what will be needed over the next 12 to 18 months.The core promise is still unstable. Messaging shifts depending on who is in the room. The team has not pressure-tested a clear value story with prospects outside the earliest relationships. Sales conversations stay founder-dependent and hard to hand off.Referenceability is thin. Two or three sites may be using the product, but none are yet willing or positioned to speak credibly to outcomes with peers. Without those references, every new conversation starts from zero.Workflow and multi-stakeholder understanding remain shallow. The solution works in the pilot setting, but the team has not proven it fits day-to-day workflows without heavy customization or support, and has not mapped the full set of stakeholders who can block progress.These gaps are normal right after the first pilots. They become expensive when they persist.<h3>Why this period matters so much</h3>The companies that treat the post-pilot period as a deliberate bridge do something different. They use the early sites to generate the specific evidence and references that later buyers will demand. They harden the value story. They start building a small network of clinical champions who can open doors. They get clearer on the documentation and outcomes VACs will require. They stop treating every new opportunity as a custom science project.None of this is glamorous. It is the work that determines whether early clinical validation turns into something durable.Teams that skip it often look busy. More pilots, more conference presentations, more “interesting” conversations. The underlying conversion mechanics stay weak.<h3>A practical way to pressure-test where you stand</h3>If you are in this window, a few diagnostic questions are useful:<ol><li>Can you point to a simple evidence roadmap that covers the clinical, operational, and economic outcomes needed for the next set of VAC discussions?</li><li>Do you have at least two or three reference customers who are actively willing to speak about measurable results?</li><li>Is the core value message stable enough that someone other than the founder can deliver it consistently?</li><li>When a new opportunity appears, how much of the supporting material already exists versus how much has to be built from scratch?</li><li>Are you seeing real movement toward decisions and implementation, or mostly polite interest that never converts?</li></ol> Honest answers to those questions usually reveal whether the company is still inside the Adoption Gap or starting to cross it.<h3>Closing the gap is a choice </h3>The Adoption Gap trap is common because pilot success feels like progress. It is progress. It is just not the kind that automatically produces repeatable adoption. The teams that avoid long stalls treat the period after the first pilots as the time to build the commercial and evidence infrastructure that later growth will require. They do not wait for the next pilot or the next funding conversation to force the issue.If you are running a seed or small Series A MedTech company and the early clinical signals look good but the commercial path still feels unclear, this is the moment to diagnose the gap rather than simply run more pilots.The free 7-Lever Self-Assessment is designed for exactly this stage of the journey. It walks through the specific foundations that matter after early clinical validation and gives a clear readout of where the biggest gaps sit. You can get it through the form on the <a data-mce-href="https://growthplane.com" href="https://growthplane.com" target="_blank" rel="noopener">homepage</a>. If you want to walk through the results or pressure-test the next 6–12 months of work, I’m happy to do a focused strategy conversation; just hit the Book a Call button at the top of the page.&nbsp;&nbsp;

The Adoption Gap Trap

round mirror with reflection of man standing on the ground

Author and Columbia professor Halle Tecco recently shared a thought provoking <a data-mce-href="https://www.linkedin.com/posts/halletecco_i-recently-spoke-with-a-hospital-cmio-who-activity-7453043817009676288-1O3Z?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAADleoBbUgcAt8rZFR-egBkNo3efiATkhg" href="https://www.linkedin.com/posts/halletecco_i-recently-spoke-with-a-hospital-cmio-who-activity-7453043817009676288-1O3Z?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAADleoBbUgcAt8rZFR-egBkNo3efiATkhg" target="_blank" rel="noopener">post</a> on the power that Epic exerts on the healthcare industry, and on healthcare startups and innovation in particular.&nbsp; Here's the text of the post:"I recently spoke with a hospital CMIO who told me they were switching AI vendors. They were moving from a well-funded AI scribe startup to Epic's native AI ambient scribe, even though he genuinely liked the startup's product better.&nbsp;It came down to money: Epic was $100K a year compared to the startup’s annual cost of $1M.That story is playing out across the industry. SaaS is struggling broadly; software stocks lost over $1 trillion in early 2026, in part because it's easier to build things in-house now.&nbsp;But in healthcare, we also have the disadvantage of having an incumbent like Epic that squeezes out competitors. In Robert Wachter's words: "Epic’s stranglehold on the healthcare system AI market is likely to stifle investment and innovation".&nbsp;I do think the “SaaSpocalypse,” as some people call it, is an overcorrection. But if your entire pitch is a workflow automation layer on top of someone else's data, you're in a tough spot."This is spot on,&nbsp; but while I'm skeptical about the SaaSpocolypse, as I've written before, I would say it's more dire for SaaS &amp; AI startups in healthcare vs. any other vertical because of the stranglehold Epic has on the industry.Healthcare by its nature (necessity?) is massively risk averse, and the explosion in ransomware attacks in the late teens &amp; early 20's have only hardened that mentality relative to technology adoption.To echo what the CMIO told Halle, I've personally heard the following from CIO's, CISO's and CMO's for both regional systems and large IDN's (paraphrasing from memory):<ul><li>- "If I know something is on Epic's roadmap, I'm either not buying from another vendor, or will only sign short term deals so I can switch when Epic is ready"</li><li>"I want to buy platforms, I'm not interested in point products anymore"</li><li>"My CEO won't question my decision to buy from Epic/Oracle" (twist on the old-school Silicon Valley truism that "nobody ever got fired for buying Cisco...")</li></ul>Over $1.5 billion-with-a-B of capital has gone into ambient listening startups in the last couple years, and 2 months ago Epic released AI Charting. I wonder what the return prospects are now for those investors?The advice I'm giving to founders is if you think Epic can build a competitor to you, pivot. Doesn't matter how much better you believe your tech is, healthcare doesn't buy cutting edge or disruption. Plus, you will always be at a price disadvantage. Instead, focus on how you can build a moat that Epic can't or would choose not to try to bridge.&nbsp;In many (most?) cases that's easier said than done, but to build sustainable adoption, that's the only choice unless &amp; until Epic's stranglehold loosens.

The Epic Threat to Innovation in Healthcare

I just read Pete Flint's piece, <a data-mce-href="https://www.nfx.com/post/infinite-game" href="https://www.nfx.com/post/infinite-game" target="_blank" rel="noopener">The Infinite Game: What Artists Know That Founders Don’t,</a> and it got me thinking...again.&nbsp;Pete's thesis: Software is having its daguerreotype moment (yes, I had to look that up too) thanks to AI. When photography first appeared in 1839, painters thought it was the end. Who needs painted portraits when a machine can capture IRL perfectly? But in reality, photography freed artists from spending time on literal reproduction/documentation and instead allowed them to focus on creative expression...the 'art' of painting. At the same time, photography itself exploded through photojournalism, artisitic photography, instant Polaroids. The world of visual expression didn't contract. It expanded in directions no one predicted, creating new professions, markets, and industry segments.<figure id="figure-wy5axfvqpmonjqoak"data-full-width><img id="wy5axfvqpmonjqoak" src="https://cdn.durable.co/covers/30SoRpiPpkaRMGC3SRHV4bEy9rLTyo7S9y43lUkekEb0qvnyD2mHEuaoRerrEX3b.jpg" alt="" title="" class="object-cover bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionX="undefined" data-positionY="undefined" data-fullWidth="true"/></figure>I believe we are at an identical inflection point with AI. The doomsayers focus on what's being commoditized - basic coding, rote tasks, operational patterns - but that's not destruction, it's liberation. AI handles the execution layer, which frees up cycles for humans to exercise creativity and tackle more opportunities.&nbsp;Interestingly, the speed of adoption in healthcare has so far been mind-boggling given the industry's historical aversion to deploying new innovation. IMHO, that's mainly due to existential threats to the industry that threaten its financial viability (posts for another day) and ability to provide the services our society needs.Take AI scribes. They've very quickly gone from 'what's ambient listening?' to standard-of-care level tools because the data very quickly showed them to be effective in countering one the most significant existential threats - provider burnout. A study published in JAMA Oct-25 titled <a data-mce-href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2839542" href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2839542" target="_blank" rel="noopener">Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout</a> found that after just 30 days of use, providers experiencing burnout dropped from 51.9% to 38.8% because AI scribes drive meaningful drops in after-hours charting and cognitive load, and ultimately free clinicians to focus on patients instead of paperwork. I have even heard from C-level execs from the largest hospital systems that even though AI scribes are a net-loss, they invest in them anyway because it's the only way to recruit and RETAIN the best physicians. Significant statement in an industry with low single digit net margins.And it's not just about provider admin automation. There is massive innovation happening in diagnostics, drug development, personalized medicine, and all over the back-office.&nbsp;I'll go out on a limb - 10 years from now, there will be more people in healthcare than there are today, but they will be focused on clinical tasks that actually improve patient outcomes, instead of EMR charting, compliance, coding or other 'AI-able' admin tasks. In retrospect, EMRs will be the daguerreotype of the healthcare stack.Read Pete's piece and come back &amp; tell me what you think.

Software's Daguerrotype Moment?

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