Insights · Product & Regulatory

Why Medical Device Prototypes Get Stuck Before Production

A detailed design can still leave a medical device team stuck before manufacturing. Ian McEachern explains how he uses simple requirements, rough prototypes and shared builds to keep the work moving.

MedTech · Stage 1: Lead Acquisition · MedTech & Innovation

Short answer

How can medical device teams move from an idea to a manufacturable product?

Ian McEachern says teams should define interfaces early, share rough prototypes on fixed dates and design for manufacturing transfer. He builds opportunities to iterate into the schedule, then works alongside the receiving manufacturing team on early systems. That approach lets product design and manufacturing documentation improve together instead of refining everything on paper first.

A medical device idea can become a detailed design without becoming something a team can build and transfer. Ian McEachern describes the churn that happens when early proof of concept remains unresolved while complexity and design controls accumulate. His approach is to make the important questions visible through clear interfaces and early physical prototypes.

Ian is founder and CEO of Nerdian, a product design firm. He spoke with host Terry Coutsolioutsos on the Zero Friction Podcast about his work in medical devices, the Maestro surgical robot and how to move from an idea toward manufacturing. His focus is on making complex engineering work easier to share, test and hand over.

How much complexity does the product actually need?

Ian describes joining a small team at Moon Surgical and bringing the Maestro system from the start of final product design to robotic surgery in the clinic in less than 16 months. He presents the system's deliberate simplicity as an important part of that story.

In his description, Maestro fits through a standard doorway, can be moved by a person and works beside the bed in an existing operating room equipped for standard surgery. He contrasts that approach with systems around which an entire operating room may be built. Those are different design choices for different situations.

He also points to compatibility with standard instruments and scopes, rather than requiring proprietary ones. Power is another constraint he says people overlook. A device that needs special electrical installation brings a different set of demands from one that runs on a standard outlet. For Ian, practical constraints belong in the engineering discussion alongside advanced features.

Which interfaces should the team define first?

When a founder arrives with an idea, Ian starts by identifying interfaces. These include the machine's relationship with the world, the operator, the manufacturer and the instruments it uses. Defining those connections helps the team decide what matters and who is responsible for what.

At first, an interface can be a high-level requirement, such as fitting through a doorway or occupying a particular space. Over time, the team works down to connections between boards and mechanical parts. Ian says this creates a shared mental model of the system.

That model supports practical decisions. If someone wants the product thinner so it can fit through tighter doors, the team can consider what else changes. The point is to understand the effect across the system, rather than treating a requested adjustment as an isolated drawing change.

When should an unfinished prototype be shared?

Ian works backward from the target date and tries to fit as many prototype cycles as possible into the available time. Each prototype has a time limit. The team shares what it has on the agreed date, rather than waiting for a particular level of completion.

We say we're going to share with people what we have on this date.

Ian McEachern

He is comfortable with rough early prototypes that remain incomplete. They may need temporary workarounds, but they can still communicate the idea and invite useful feedback. He uses large-scale 3D printing and laser cutting as examples of ways to make that early work tangible.

Ian contrasts this with refining a design extensively on paper or in a presentation before building it. A physical prototype lets more people see the same thing, add to it and identify improvements. Some early prototypes may not be fully functional or sterilizable, he says, yet can still support proof of concept and early testing work.

How do you keep speed without making transfer harder?

Ian says good engineering includes the ability to transfer the work to other people and manufacturers. Having equipment in-house can help remove a specific obstacle, but he does not treat doing everything internally as the goal.

He gives an example from his own shop: a project had ordered many parts but was missing a small number. He could make the missing pieces locally to keep the program moving, without turning the shop into the source for the entire production quantity. The product and process were still designed for eventual transfer.

That distinction is central to his approach. The team can use its own tools to avoid a delay while continuing to design something another manufacturer can make. In his account, keeping development moving and preparing the handoff are parts of the same job.

What should happen during manufacturing handoff?

Ian describes a gradual transfer through shared builds. His team builds an early system. It then builds alongside the contract manufacturer or internal manufacturing team that will receive the product line. After that, the receiving team builds while his team watches and supports it.

Throughout this process, both the design and the manufacturing documentation change. Ian says documenting too much too early can create material that will need to be rewritten. Developing the documentation while assembling the initial systems makes the instructions part of the actual build experience.

His emphasis is on the transition between teams, rather than a final package simply being handed over. Building together gives the receiving team experience with the product while the originating team can still make improvements and clarify how the work should be done.

Where does AI help, and what remains difficult?

Ian says AI has helped with early prototyping and proof of concept, where the immediate task is to make something work and explore a possibility. He also describes more efficient back-office work using simple AI tools.

He draws a boundary around regulated medical software. In his experience, that work has not changed as much because teams still need to meet the relevant standards and produce medically safe software. He does not suggest that faster early experimentation removes those requirements.

The thread across his examples is an engineering process that lets people see and improve the work early. Define the connections, build something that exposes the questions, and bring the manufacturing team into the build. Ian's account ties progress to shared understanding as well as to the design itself.

Where this fits: stage 1 of the revenue funnel, Lead Acquisition. Read what revenue friction is and how it is measured. See how RevRx AI works with MedTech teams.

Full episode transcriptAbout 6,000 words

From the episode captions, lightly cleaned. Speakers are not labeled, and the text may contain small errors. Time links play the episode from that moment.

0:00 Uh, it all started when I graduated school. I thought I was going to be a race car engineer, so I wanted to go to Formula One engineering school. Um, but then my then girlfriend and now wife went to graduate school at NYU, and I was living on my parents' couch, um, not not finding work back in Colorado. So, I put everything I had into my truck and drove from Colorado to New York. Well, I was hired on the spot and then I started the next day working with Dr. Robert Jarvik and been in there, um, uh, over two decades now in med tech.

What's your opinion on robotic and where does robotic space move next? Like, what's the next frontier for robotics? Knowing you spent some time at move. And that's what Maestro was is meant to address. It fits through a standard doorway. It's not insanely heavy. A one person can move it around, and you can move it up to the bedside and start doing robotic surgery in any existing OR that's equipped for standard surgery. Hey there. I'm Terry Coutsolioutsos, founder of RevRx AI. We remove friction and architect revenue for med tech and consumer health practices. Welcome to the Zero Friction Podcast.

This is Terry Coutsolioutsos. I have a remarkable guest today who has built a firm around product design. I have Ian McEachern with me today. He is the founder and CEO of Nerdian, which is really helping the have medical device companies, robotics companies take it to another level when it comes to their technology. So, Ian, great to have you on board today. Love to learn more about you, your journey in the manufacturing and design space itself and what you've done to sort of lift other companies up and then what Nerdian's doing today to kind of help companies get to that next level and get to that product design phase.

Thank you so much for having me. Awesome. So, uh, how did it all start for you, Ian? It all started when I graduated school. I thought I was going to be a race car engineer, so I wanted to go to Formula One engineering school. But then my then girlfriend and now wife went to graduate school at NYU, and I was living on my parents couch uh, not finding work back in Colorado so I put everything I had into my truck and drove from Colorado to New York and the next day went down to the public library and started looking for jobs and I came across a job with Dr. Robert Jarvik at Jarvik Heart and they were looking for a an engineer that was zero to two years out of school that had CNC machining and also jewelry making experience and my parent or my parents ran a jewelry store my dad's a master jeweler so I grew up in that trade and then also happened to have a small CNC milling machine in the back of my truck

Quite literally and so I I was hired on the spot and then I started the next day working with Dr. Robert Jarvik and I found that it was a very very rewarding and then also very wonderful area of engineering to be in and I've been in there over two decades now in MedTech. That's great and talk about like sort of manifestation and things that are supposed to happen, you know, that's pretty cool. Thank you. me about your experience at Jarvik Heart. I mean that is a one of a groundbreaking technology and you know, tell us a little bit of how that developed and and where that led you to your next phase.

3:01 Yeah, Jarvik Heart was pretty amazing. It was a fully vertically integrated R&D and manufacturing facility in Midtown Manhattan. So they had CNC machines on the 15th floor of an old press of old printing press building in in Midtown and then we did R&D on the seventh floor and then the scenes the machine shop was on the 15th and we also had a clean room and we would quite literally have titanium come in one end and LVADs come out the other end and during my time there not only were the R&D engineers responsible for the R&D of the new child and infant size LVADs for the pump and program we were also responsible for the day-to-day manufacturing operations of the Jarvik 2000 LVAD. So every LVAD that went out the door during my time there myself or my partner were someone were the last people to touch it before the surgeons did and so we had quite a lot of responsibility, but also got to learn basically everything about the manufacturing process of an LVAD from

Machining all the way to final assembly and packaging. That's pretty cool. And what a great, you know, sort of mission to wake up for every day to go and deliver. So, there's Jarvik, and then what was the next step after Jarvik? And then after Jarvik, we wanted to move back to Colorado, and I ended up at a company called Evergreen Research, which was a spin-off of Cobe. So, Cobe Laboratories really pioneered what we now refer to as hemodialysis, and uh the story was at at the time, this is many, many years ago, Cobe was trying to develop a new blood pump and had difficulty doing so in-house, and so they spun off a little R&D group. That R&D group delivered on their promise within 16 months or 2 years, and then after that, they didn't want to shut it down, so they kept it alive as a medical device manufacturing contract R&D firm, and that firm became Evergreen Research, and so I worked at Evergreen Research to

Architect and design the Tablo kidney dialysis machine, and so Outset at the time it was called uh Home Dialysis Plus, but now the company's called Outset Medical. They had contracted with Evergreen Research to architect their Outset Medical Tablo dialysis machine. And what does a Tablo dialysis machine do? It's pretty amazing. So, first of all, it does dialysis, which in and of itself is quite an amazing process, but the other home dialysis products on the market and other just dialysis the products that you do in a in a clinic, you need dozens and dozens of liters of what they call dialysate, which is a diluted acid or base mix that they mix to go on the other side of the dialyzer and pull whatever things they need to pull out of the blood. And so, that in and of itself is very difficult because even if you have a portable machine, you still need these big bags of fluid for every treatment. And so, one of the

5:43 Amazing things about the Tablo system is it has an RO water filtration system built into the base. So, you plug it into the tap water just like any spigot like you would a portable washing machine and it takes it'll take any EPA certified drinkable tap water and turn it into injectable grade ultra pure water that can be mixed with dialysate concentrates. So, that it in the end you have a small machine now the size of a small like a dorm refrigerator and then you have two jugs like 1-gallon jugs of the concentrate and then all the rest of the fluid is taken from the the water supply. And so, it really makes it so that you can have not only portable dialysis at home, on the go, but you can also do dialysis in in a clinical setting without building a whole RO water treatment facility to support a bunch of dialysis machines.

So, it really enables a lot of like um places that wouldn't normally be able to do dialysis to be able to do dialysis. You know, and and so you move from there and I know you had an extensive experience with with Moon in the robotic business. So, which is really exciting. So, talk to me a little bit about that and then then I really want to talk about Nerdian and then then what you're really looking to solve from a product design perspective with with your clients. But, tell us about Moon because I think that's a really unique story in itself and especially when it comes to you know, helping companies compete with Intuitive which really sort of owns that whole robotic surgical marketplace and what you what they're developing what you helped them develop to actually sort of counterattack in a different angle.

Absolutely, I'm happy to. So, over time my wife and I made it out here to California and like a lot of people I got sucked into the surgical robotics ecosystem. I've done a lot of automation and robotics design in addition to the med tech stuff. So, that's why my experience was attractive to them, but I worked initially at Verb and then over time at Auris and built a very large team for J&J's robotics and digital solutions program for the Ottava robot. And then after that I left and I joined a very small team at Moon Surgical. And with a very small team, we brought to market the Maestro system in less than 16 months from beginning of of product design on the final product through to actually doing robotic surgery in the clinic on humans. And the amazing thing with the the Maestro system is the Maestro system is in a lot of ways deliberately simple. In a lot of ways ways the da Vinci system and Ottava and

These other competitors to it are are extremely extremely complex. And that works very well for a lot of the the more difficult surgeries, for a lot of the situations where you can build an entire OR around a very large robot. But that leaves a lot of the opportunity to improve care on the table. And that's what Maestro is is meant to address. It fits through a standard doorway. It's not insanely heavy. One person can move it around. And you can move it up to the bedside and start doing robotic surgery in any existing OR that's equipped for standard surgery. And so the Maestro was really built to to democratize access to robotic surgery. And it doesn't do It only has two arms. It doesn't do a lot of the more advanced features that these other assistants do. But a lot of the the selling points and a lot of the value of the system is in its simplicity. And so in not doing a lot of those complex things, you can do things

9:00 Like it's compatible with a lot of off-the-shelf instruments and endoscopes. You don't have to have proprietary instruments and endoscopes that are disposable for the robot. You can use kind of your standard lap instruments and standard scopes with Maestro. And it really enables a lot of people that wouldn't otherwise have access to surgical robotic systems to have access to them and really improve the standard of care. Got it. So, and I'm guessing footprint helps, too. Like that that Moon Surgical robot probably it makes it more competitive in that way, too. Since simplicity, footprint, the ability to move it around is all all very strong attribute, I guess. It is. And one of the things that people will often miss, and this was a challenge with Outset Medical as well, is power. Anything above like a standard 20 amp, 15 amp, 110's outlet requires special installation. And so, a lot of these systems, like Maestro, like the e-table system, run on a standard outlet, and that's not easy.

Got it. Well, let's pivot. Let's pivot to your current customer base today and running Nerdian. And so, when you go to market, like, who is typically the the customers that are coming to you with, you know, what are they medical device, are they robotics, are they across the board? Typically, from a product design perspective, where do you really tend to find yourself? We end up helping out quite often with different difficult engineering challenges. And so, it it really runs the gamut, and I'll I'll give you an example. So, uh for example, we have some clients that are very early stage. Maybe it's a group of of research professors or doctors that have a new medical device that they want to bring to market, and they really need advice on the architecture, how to architect the whole system, how to walk the line between what's disposable, what's capital, what the reimbursement codes do you go after, and then what standards do you need to apply to, and just help them really architect the

System around what's possible to actually bring to market and manufacture. And then, on the other end of the spectrum, we work quite a bit with a lot of, like, for example, very large, established, publicly traded companies that just need a lot of engineering expertise. And and so, for example, another recent product like that is they're a very mature company, very mature product line. They're coming out with a new product, but there are some really advanced new features focused on injection molding, ultrasonic welding that they needed to incorporate, and their in-house team didn't have that kind of experience. And so, we were able to walk with the in-house team, help guide them, help introduce them to our partners to be able to manufacture and prototype these things. And then, we have a lot of in-house equipment here that they also leverage to allow them to kind of do that new new difficult engineering challenge that they haven't done in the medical space before, even though they have a team, they have the

11:39 Infrastructure in place, and they don't need us to architect the whole product. So, it sounds like you you can be like a little speedboat for your your customers in a lot of ways. Exactly. Exactly. And in in that way, we're really embodying the Evergreen Research mantra and a lot of the things that I learned in working there. Exactly. So, tell me about, you know, the speedboat process. Tell me what that looks like and, you know, cuz I can I've experienced many things in my career where as a large manufacturer of medical technology, many times big companies get in the way of innovation just because they're big and sluggish and slow and lots of processes and and sometimes innovation doesn't really get the agility that it needs inside of a bigger company. Are those some of the problems that you end up solving for as well for some big bigger companies?

Exactly. And quite often, and my best example of that is by the time when I started at J&J, it was I could pull a part number, make a drawing in 20 minutes, and by the time I left it took a week because you had to go through all these different processes and different people. And that's exactly what we do at Nerdian. And a lot of times we have all the equipment here to be able to do everything that we need to do, but we deliberately don't do it all, and we and that part of good engineering design is to be able to transfer that to other people and transfer that to other manufacturers. Many hands make light work. But in a pinch, we need that one part to unblock the the program, we have the equipment here to be able to do that. And so, a great example of that a little later today, I'm going to laser cut a couple parts, and we ordered hundreds and hundreds of parts, and we

Just we're just missing two, so I'm going to make those two here. I'm not going to make several hundred here, but we deliberately make the process and the product designed early on so that it can be manufactured, so that it can be transferred to a CM and transferred. But through that process, we don't let it slow us down. So, when they come to engage you, what you know, and we're kind of like, let's focus in on a new startup company. So, let's let's create a scenario, right? Cuz I think this is probably an area where you can really add some value to these startup technologies, these startup companies that haven't had rounds and rounds and rounds of development over over cycles.

And so, you have a doctor who comes to you with an idea that, you know, he's a cardiologist, they have a, you know, a novel problem that they think that there's an opportunity in the market for a new piece of technology. How do you What does that design and engineering and architecture and concept How does that all go down from, you know, a drawing on a napkin into like a like what does that process look like to actually get a prototype and get something moving? One of the kind of secret sauces of what we do and and I quite honestly, I learned this from reading and researching about the Apollo program.

14:20 And it it's the interfaces. So, early on, we really try to focus in on what are the interfaces. Interfaces between the machine and the world, the machine and the operator, the the manufacturer and the machine, the and the instrument and the machine. And so, we really start to define what those in what those interfaces are. And those really can help you help us just laser focus on what are the actual requirements, what are important, who owes who what in what way. And we really define those very early on. And those can be very high level. So, what we were talking about, oh, it needs to fit in this space or go through this size door. And then over time, those get worked down until it's an interface between this board and that board and this mechanical bit and that mechanical bit. And it once we really hone in on those interfaces, not only does that give us, okay, what do we need to pick, but it also gives us, how does

It affect everything else? And so, over time, what we're building is a mental model that we all share that allows us to say, hey, if we want to make it go a little bit thinner, so it can go in tighter doors, how does that affect the rest of the system? And we can have real answers for those kinds of what if questions very quickly. And so Does that Is that like take an inventory and discover design and then is are there iteration components that you build into the process like you know how like this sounds just trying to understand like how do you get to the end? Like you know Yeah. I deliberately build in as many iteration possible opportunities as possible. So typically we'll we'll look at the end date and say, "Hey, we want to be done by the end of the year." And then we say it takes us x amount of days to build a prototype and we try to get

As many prototypes within that amount of time as possible. And each prototype is is time boxed. So rather than say a certain prototype needs to meet a certain level of done-ness before we share with people, we say we're going to share with people what we have on this date. And then even though it's incomplete, even though it may have some hand waving and and some duct tape and some bubble gum, it still gets the point and it still allows everybody to share in the same mental model of what we're building and provide feedback to it and then also add to it. And so really we focus on like very rough early prototypes. We do a lot of like very large scale 3D printing, a lot of this really you know laser cutting, stuff like that. And then over time the improvements become self-obvious and it's a lot easier to share the work and for everybody to see what's going on if you have a rough early prototype rather

Than really refining things on a on a piece of paper or in a PowerPoint presentation and then building something very very refined. So that's really a lot of the value we provide is is we can design and deliver very complex early prototypes that maybe aren't full functional, maybe aren't sterilizable, maybe aren't those but you can still do a lot of the early testing work and a lot of the early proof of concept work. And and a lot of times that's where the churn happens. If you just If you can't get through that phase and on to the next and you start adding more and more complexity and design controls and all that before you're out of that phase, it becomes very difficult. So, all those things kind of come in into play.

17:28 Um you have a prototype. What's the next phase after prototype? Do you work with manufacturers? Do you tie it all together? Like, you know, or do you actually do the manufacturing process, too? We uh a little bit of both. So, usually there's a lot of clinical work at that phase. So, typically we'll do very early prototype, do some very you know, maybe not animal work, but bench work, and then it'll there'll be some animal work or some other clinical work that we need to do. And typically we support that. So, like at Maestro, I personally ordered and purchased the first five systems worth of parts, and all the boxes came to me and built those up. And then we used those those early systems to do that transfer. So, the first system would probably would be be built by me and my team. The second system would be built usually with with either the contract manufacturer or the in-house manufacturing team that's going to be absorbing that information and absorbing

That product line. And we build it with them, and then and then after that, they build it, and then we watch them and support them. And that whole time we're iterating on both the product design and the and the uh manufacturing documentation in order to make the the thing just go together a lot better, and then also have a really clean, nice documentation package. And we find that if you if you do that too much of that documentation too early, you end up changing most of it anyway. So, really doing it in that way where you're collaboratively putting that together as you're putting those initial prototypes together is really, really efficient, and then it ends up with a better product.

Let me pivot to AI a little bit and robotics. I think that's a How's that changed your business? Quite a bit. It There's a lot of For the longest time in robotics, software was a big part of the bottleneck. Like, we could design a robot with 10 arms, and it could do all these crazy things, but it would take 6 years to write the software that does all and and so in a lot of ways it's changed. What's interesting and I I see this a lot in the medical space with regulated software, it it hasn't changed a whole lot because you you still need to to get it through the the standards and write medically safe software per per that definition and AI really hasn't been able to do that. I don't know that it will be without changes to the rules.

But I think that a lot of the early prototyping stuff, a lot of the just make it work, figure out a proof of concept stuff has really been enabled by just being able to do these more complex things faster. And then there's a lot of other aspects to AI that I that have affected my business in the back end as well. Just a lot of like the back office stuff is a lot more efficient now. Just with simple AI tools. Got it. So but AI is definitely creating some efficiency in the space, you know, shortening time frames, all those types of things, right?

20:14 Absolutely. Yeah. What are what's what's the biggest problems that your customers come to you presenting with? Like what's the what are their biggest pain points? A lot of times what I say that I've done for the last 20 years in the last 15 years here in the Bay Area Silicon Valley is teach software people how to make hardware and so I have an old school mechanical engineering education. I view myself as kind of an old school mechanical engineer that would be just as comfortable designing a flyball governor or a steam engine as what I do today and I happen to design medical devices and that's a lot of what I learned from Dr. Jarvik. He was a very good machinist. He employed very good machinist and it was very first principles focused on good mechanical engineering and a lot of what we do is that. So a great example is one thing we've done many times now for companies is surgical navigation companies. They have a set of bone taps, bone drills, things

Like that that they need to sell with their system, and not all engineers are comfortable doing all the detailed design work to design the bone tap and the features and the engineering behind that. And we we do that kind of stuff all day. Mechanism design, optimization of like membranes, blood contact surfaces, a lot of just really really difficult, hard-won engineering, mechanical engineering, systems engineering, electrical engineering knowledge and background as it pertains to medical devices is is really a lot of the value that we provide. Cool. What's next for Nerdian?

More more of the same. My my goal has always been to design and deliver to market as many medical devices in my career as possible. And so the way that I do that is find great partners to work with and people to help. And so really hopefully more of the same, just faster, and um more of them making it to market. That's great. And what do you do about like how do you go do people find you? Do you find them? Like what how do you how do you connect with with innovators and founders of of technology?

A little bit of both. So um any more there's quite a bit of folks just recommending us and and for different projects here and there. We have uh quite a bit of traction in the investment community um recommending us for for their companies. And then also we there's also just a lot of things I've been a part of my whole life like LVADs, blood pumps, and I go to a lot of those trade shows and just know know people in the space. And so we naturally end up working together through those kinds of relationships.

That's pretty cool. The digital world, right? You know? And you're right there in a and kind of a one of the hotbeds in America. Like you're in the Bay Area, you know, whether it's the Bay Area, Santa Clara, you know, the Valley. It's all kind of connected with that medical device world. And you've seen all these things kind of grow. What what what's your opinion on robotics, and where does robotics space move next? Like what's the next frontier for robotics knowing you spent some time at Moon?

22:53 Yeah. I I think the next frontier ro for robotics are a lot people have been saying this for a long time, but but robots that interact with the the general public more often. And it's been a difficult challenge. A lot of times we call them cobots, but that's one of the really wonderful things about Maestro is Maestro, when you want it to move, you just grab the arm and move it. And And so, it really is a very collaborative robot. And then it You can also enable auto following, and it'll just follow the tool tip naturally for you, and still allow you to move it naturally.

And so, I think it's more robots like that that interact with average people, general public. And maybe they're not doing the most elaborate of difficult, challenging tasks, like has been popular in the past. In the past, it's always been the dirty, dollar, dangerous jobs, right? The The nuclear reactor cleanup and things like that. I think that Of course, those robots still have a place, but I think that more and more we're going to start to see robots just in our everyday lives doing simple tasks. So, you've worked in some really remarkable spaces. Jarvik Heart, you Evergreen Research, Moon Surgical. What can you say like was a consistent thread through those experiences that had led you to where you are today?

The people I've worked with. Every one of these places, the people I've worked with have been remarkable to me. And it's been remarkable to me that they are my coworker because of their path, where what they did to get there, and a lot of times their education, and what they were able to teach me. And I can quite literally say that I've I've worked with people with degrees from the top technical universities all around the world, and they have all been deeply humbling, but also deeply just good, regular people to work with. And that rubbed off on me, and has had a huge impact. And now, when I work on a lot of these projects, I have people to work for me that have advanced degrees from some of the most famous and prestigious universities in the world. And it's very strange to me that they're working for me, but we have that same kind of interaction, that same kind of passion for the work. And a lot of times, like one of my friends said

During engineering school, you have to really want to be an engineer to get through engineering school. And and a lot of these folks just really really passionately want to do what they've been trained to do and are very good at it and it's just a real blessing to be surrounded with that every day creating new greater medical devices. You know, and that's great and you have so many talented people with you. How do you Did you build like an ecosystem? Do you have an operating system? Do you have something that sort of allows all this individuality from an engineering side of things and creative side of things and a designer side of things? Do you have a system that you work within that sort of keeps it and pulls it all together? Yes, absolutely. So we have a robust system and a lot of it is is processes I've learned from Evergreen Research where we're able to to kick off a new project, do all the infrastructure pieces that we need and firewall that

25:47 Project if we need for other projects, and then bring people in specifically only to that project. Um we're able to do that very quickly and efficiently. And one of the great things that because of the size and breadth of the network that we have a lot of the things that we do are typically things we've done in the past. So when we bring somebody in that's something that they've designed a similar product in the past that was very successful and so that helps make projects go a lot smoother because you really have a lot of horsepower you can bring to bear without having to have everybody come up to speed.

Pretty cool. And and pulling all that together is no small feat and I'm sure there's a balance between creativity and consistency and processes and there's that's a constant balance for you in the product design space I'm sure, right? Like where you want you want people to reach and think beyond, right? You want people to think what if, you know, so that you can make that medical technology that advancement that, you know, nobody thought was humanly possible and come up with that brilliant idea, that brilliant new spec, that brilliant new material that changes the whole landscape of how it performs.

Let's be honest. And working this way allows that freedom for us. And that's a lot of the what I say a lot of the value I provide like on a project where I might not be doing a lot of the design heavy lifting. I I really provide a lot of that guidance and and I say okay, let's let's take this risk and let's do that thing cuz we know it'll be better before our next meeting and we'll and and then you can walk into your next meeting like a hero and and and having those little bits of not not only freedom to do that work to do that, but also the experience and the creative confidence to take advantage of that freedom. Pretty cool. So, Ian, I have one more question for you and it's more of a from a personal perspective. So, you've had great experiences. I mean, listen, you've worked on some of the most amazing technologies and and medical industry.

Jarvik Heart, which is a huge technology. Evergreen, Moon Surgical Robotics. What would be the one piece of advice that current day Ian, if you had a chance to go back and talk to 22-year-old Ian when he was sleeping on his mom's and dad's couch before he moved to New York City. And what would be the one piece of advice that current day Ian would go back and provide you know, 22-year-old Ian um and provide the best benefit because of what you've learned over the past years.

The my advice I would be give is it will go on. Early on I was very worried that what am I going to like I my first job was at Jarvik Heart working with Dr. Robert Jarvik and then I left and it's like, what am I going to do now? Like how can I possibly top this, right? And and I had a lot of just angst about that. And so it will go on. There will be other things to design and build is what I would tell us.

28:33 That's pretty cool. It will go on. I love that. I'm going to write that down. So, folks see you out there. Uh Ian McEachern, CEO founder of Nerdian, which is a product design firm that is helping early stage, mid stage, late stage companies get to the next level from a medical device perspective and thank you so much for being here today. Thank you so much for having me. It's been a pleasure. All right, Ian. Have a great weekend. Thank you, you too. So, let's connect. Let's find where your revenue is getting stuck, book a call at revrx.ai and build your revenue engine.

This article summarizes views shared on the Zero Friction Podcast. Statements are the guest’s own and are not medical, legal or regulatory advice.

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