 Good afternoon and welcome to today's Energy Seminar. I'm really excited about today. I think this is a great finale for our fall quarter. Today we have with us two of the main drivers of form energy, which has come up in several previous seminars this quarter from the regulators to the competitors to the complementors. So I'm really excited about this. We have here with us Eddie Baldwin, who is a Harvard undergrad in chemistry and physics, but also an EIPER joint MBA program alumni from Stanford, who has been with form since 2019, I believe, 2020. I think your biosystem. No, sorry. And then on video from Somerville Mass, working hard at headquarters, we have Scott Berger, who is an undergrad from WashU, but also has a master's degree in a PhD in engineering systems from MIT, where we've actually had several previous seminar speakers. I won't go into all that. And they are doing this exciting work at form energy, one of the hottest clean tech startups around town. So Annie, take it away. Thank you. It is a real honor to be here. As you mentioned, I went to Stanford. I just graduated about two years ago. And I went to a lot of these energy seminars. So it's really special to be here and be with you all today. We will just do a brief round of intros. So I lead battery product management here at form, which basically means that I work closely with folks like Scott and everyone else on our commercial analytics team on really understanding what the value and opportunity is for multi-day storage, how utilities think about it, what is it that they really need, and then with our technology teams making sure that we're actually building the right battery that unlocks that value. So I work at the intersection of both of those worlds. And I will let Scott introduce himself. Recording in progress. Well, so it's great to be here. I don't think that MIT has invited us to do one of these talks. So I think Stanford is kind of leading right now. So it is really great to be here. Appreciate it. I have a whole stick about what analytics is at form energy later. So I won't dig into it too much. But we're really closely with great people like Annie to understand the value of our products. Great. Well, we'd love just to share with you guys a little bit about form, what we're up to here, how we see the market opportunity. And as Scott mentioned, he'll kind of share a little bit more on the analytics side, how we go about modeling future grids. So for those of you who don't know about form, we are a company building a new class of storage assets, which we call multi-day storage. We've been at it since about 2017. Now we're about 170 folks. We're based out of both Somerville. That's where we do a lot of the cell development in R&D and engineering. And then we also have a big team out of Berkeley. That's where I work out of, where we do the product and systems development as well. We also have a manufacturing facility out in Pittsburgh. So that's where we are today. I expect if we come back here in a year, we will have grown substantially since then. So we just announced this year we raised our Series D. So now we've raised it just close to $400 million from folks who really understand kind of what it takes to build a totally new class of storage asset and really have this kind of long-term view about how to invest and how to build new, reliable assets for the grid. And just for some fun folks, so that photo up there at the top, that's from our 30-daying asset. That's where we were kind of jumping, where we got to be together after being apart from the pandemic. And then up here in the upper right is one of our full-scale cells. I'll kind of talk to you guys a little bit about what actually is in a cell and what it does. But there's just kind of a little bit of a flavor of being both kind of building a new storage asset that really builds a new grid, but also kind of building new chemistry that enables that. So when we think kind of broadly about why form started and what is the problem space that we're really trying to solve, simply it's, how do we replace the opportunity of what fossil fuel plants do today? And that even in the US alone, it's close to a terawatt of opportunity. So this particular figure on the left shows what we're projecting out, looking out through 2050 of what future grids really look like. And you'll see that there's a huge expected growth and renewables, at least a 4x growth between now and 2050. Huge growth also of capacity as well, meaning kind of the electrification demand. But there's still a lot of existing kind of legacy fossil fuel assets that kind of remain on the grid. And this is kind of our problem space of what does it really take for us to really retire that, both for coal and then natural gas. And if you think about why is it that we still expect to have some coal and natural gas on the grid, it's really a reliability problem. So you guys might have talked about this in your energy seminar, but you might hear utilities a lot talking about how do I build an affordable, clean and reliable grid. So when you think about reliability, it's really making sure that you're delivering electricity 365 days a year, but also across all these different types of weather events that could happen on the grid. So we're just showing you a sample of how utilities really think about this and some of the reliability challenges that they see. So one, and this is on the upper left hand side for the Pacific Northwest, maybe it's very hydro loaded and maybe you'll have these multi-day events where you have low hydro generation and you need a new kind of low cost energy to ride through those multi-day events. Some of you may have been familiar with the polar vortex that happened earlier this year where you have kind of the confluence of bad factors happening where you'll have low wind generation, you'll have gas assets are not operating and then you'll just have a big problem where you just cannot meet energy demand or you'll have very, very high electricity prices. So utilities even today are really thinking about how do we solve these types of problems, which today mostly gas solves today, but we wanna do this in a firm, clean, reliable way in the future. So if you think about the design space and this is actually one of my favorite stories about form is we weren't so much pick a technology and then find a problem that we wanted to solve, but we did it the other way around, which is if you wanna solve that reliability challenge, what is the best way or what are the types of kind of requirements on a storage basis that really solve that reliability space? So we and Scott will speak to this in much more detail, but when you model out what future grids look like with high renewable penetration, you want a new class of storage asset that's at least 10 times longer in duration and at least a 10th the cost, installed cost of lithium ion to really replace the generation of what we see for fossil fuel assets today. So on the Y axis, you'll see this is kind of an installed cost. Expect, you know, lithium ion today installed cost. So that's all in, not just the hardware cost, but you know, turnkey, everything installed cost to utility is around 300 bucks a kilowatt hour, probably bottoms out at 100 bucks a kilowatt hour on like a fundamental spaces. But if you wanna build a new kind of fundamental different type of storage asset that lasts for multiple days, so lasts for 100 hours, it has to be very, very low cost. So more on the order of about $10 a kilowatt hour. So this is kind of the design space for form is has to last for about 100 hours, has to be on the order of 10 to 30 bucks a kilowatt hour. And this is really kind of the opportunities space that we're solving within. So when form started, we kind of looked all across the possible design space. So what is it that, what are the different types of electrochemical couples that you could look at that could really get you to that very low cost? And if you look at a graph like this, there's many existing technologies today. Like I mentioned, if you were to do lithium ion just on a chemical cost basis, a dollar per kilowatt hour, you're around 60 bucks a kilowatt hour. But iron is actually been around for quite a while since like the 1970s. This technology has really been around and has the fundamentals about being a very, very cheap technology that can get you to very low cost. So it's different about form and I'll talk about this in a little bit is we can access a form of iron that's very different and kind of readily accessible from the steel supply chain today, which allows us to really get to very, very low costs on the order of a dollar per kilowatt hour. So when you think about what does an iron air battery do? How does it work? You can think about it as a reversible rest or an air breathing battery. So on discharge, the battery breeze in air. So you take your oxygen from the air, one of the cathodes or the catalyst in the cathode will react with the oxygen to form hydroxide ions and then you'll convert that iron to iron oxide. And then on charge, you're gonna reverse that process. So the battery will kind of breathe out oxygen, you'll return iron back to its metallic form and then you'll breathe out oxygen and that process repeats for thousands and thousands of cycles. So this is kind of the fundamentals of if you were to pick a very durable low cost scalable solution, iron air actually fits a lot of those boxes when you wanna kind of check, how would I actually wanna do this really well? So I spoke to this a little bit, but on an installed cost basis, we can really get to an installed cost about the 10th that of lithium ion. Safety is a big factor, right? So not only is iron kind of one of the most globally available safe molecules in the world, but actually on the components basis, which I'll talk about in a little bit, it's really just iron air and then water is kind of the fundamentals of our chemistry. There's no risk of thermal runaway and there's no heavy metals in the system. So it's very safe system, and which is something that really matters a lot for utilities. Scale is also very important, right? You wanna make sure that we can build this not just in the US, not just on individual continents, but can you access a format of iron all around the world? And you can, iron is actually made on every continent, right? So on a kind of a fundamentals basis, this really gives us to very, very low cost entitlement that can actually meet the requirements not just within the US, but kind of within the global, within the world. So on the fundamental building blocks of our system, so that you can think of the cell as kind of that fundamental chemical component, it really has all of those qualities that you want in terms of low cost, right? So the iron anode, this is a highly abundant, very low cost metal that's readily available from the steel supply chain today, with basically minimal changes that we can get to to inform the format of our system. Our air electrodes, these are all kind of commercially proven readily available electrodes. There's nothing really new or fundamentally different there. And then they're all surrounded in kind of a basic electrolyte, a high pH system that's similar to what you get in AA batteries today. So that's kind of the core building block in the chemistry side. And then on the balance of system side, which is all the auxiliary systems that you need to make the battery work. So air handling, water management, et cetera. All of these are kind of commercially off the shelf, readily available components. So there's nothing really new or fundamentally different that we're innovating on there. And that allows us to get to a very, very low overall installed cost. So when you think about what this actually looks like in the field, eventually you can imagine a system that's hundreds and hundreds of acres. And it really starts with that core chemical building block, so the cell. So that cell is that our smallest, repeatable electrochemical unit that includes the anode cathodes all surrounded in that water-based electrolyte. And then we build many of those cells in series and in parallel to build this battery module, which is kind of this DC power building block about the kilowatt sale. If you'd imagine what this would look like in a room, it's about a one by one by one meter module. So a little bit about to my shoulder height. And we really thought, we were very careful about kind of thinking about this design in a way that could really be low cost and easily installed and easily managed in the field. So something that could easily be shipped to a project site, easily movable with a forklift. And then to get an actual power block, which is what a utility would really need. They want something that's fully connected to the grid at the medium or high voltage system. You want not just many of those power modules, you'd actually have maybe thousands of those modules all surrounding around a utility grade inverter on the order of a megawatt scale. And then to get to the many hundreds of megawatt or even gigawatt scale, which is what you would really want to be kind of similar to what you get for gas plants today, you can imagine a hundred megawatt system would be about a 10 gigawatt hour installed battery, right? So it's a lot of capacity that you get. And this is where we really think is the opportunity in space of how you could really replace gas and coal plants. So just to give you guys a picture of what this looks like, you might appreciate this from being in an academic environment all the way up to product space. So just in early 2018, this really just started with an iron anode, right? Just one small pellet and just proving out that that could really work. And then we've scaled up since then, both kind of at the subscale to subscale cell level, building out to that full height cell. So that kind of gets to my shoulder height that gets you to that one meter depth. And then we've scaled out since then, both on width and then also on the module basis as well. So kind of building out what that first proof point looks like in terms of what an actual embodied electrochemical system looks like. So it's a big scale if you were to actually imagine this on a order of magnitude basis, on a power basis from the iron anode to a full module. That's, I think it's 300,000 X. That's quite big that we've been able to do in the last few years, which is really exciting. So we have a first pilot project, which is really exciting when you think about the opportunity and demand. So we're working with Great River Energy. They are a small co-op in Cambridge, Minnesota. And we will be deploying a one and a half megawatt, 100 megawatt hour system that will be coming online in 2023. And I think one thing that's particularly exciting about this is it's easy to think of multi-day or long duration storage as kind of a fall out problem or a solution that you wouldn't really want now. But in this particular utility, there's a lot of drivers that really drove them to be very excited about form, even kind of starting from two years ago. They have a coal plant in their area that's retiring and they have a lot of wind assets and they're just really craving a new form of firm clean capacity that they can use to replace what that coal plant used to provide. And that's where they got really excited by form. And we're excited to bring this onto the grid in the next two years. So with that, I will transition it over to Scott and talk a little bit more about the modeling side. Thank you, Annie. Well, that was a great tee-up for the company. I think if you wanna go to the next slide, just a bit about what analytics does it form energy. I think Annie touched on this earlier, but we really try to be a, I mean, just across the board, obviously a quantitatively driven company, we wanna make all of our decisions, informed by the best possible analysis. That includes at the very technical level. So we have, I have the next slide talks about this, but we have a lot of folks that do things that could be considered analytics at form, really with the analytics team within the broader business development and analytics group at form does, is kind of quantitative modeling of markets. So anything that touches the kind of economic or project or system value of our asset, and that is, that requires essentially beyond an Excel model to analyze, that is what the analytics team focuses on. So largely we're really kind of driven by the desire to understand the future trends of the power sector and how that will impact the economics of different assets, including our own. So we wanna be very unbiased, but then obviously we wanna inform forms, kind of product and strategy and policy decisions based on that. So we do this kind of unbiased or what we think of as unbiased assessment of market fundamentals and system economics and then use that to help form build projects. So we work really closely with our commercial operations team to really educate our customers. The reality is most utilities have not seen a 100 hour battery before. Some are still think that four hour lithium ion batteries are nascent technology. So this is a 100 hour battery, sounds very strange to them. So we do a lot of customer education and help them understand what the business case could be. We then, we also realize that this is not, form is playing really a 30 year game. This is not a kind of an effort to get into a market and get out quickly. This is, we see this as a multi-decade effort. We're all motivated by the desire to decarbonize. And so what we are trying to do is educate the market on what we think are the right mechanisms to decarbonize cost effectively. And then we obviously wanna do that by providing our unique view. So when we think about things from the multi-day energy storage perspective, that's the kind of unique perspective that we can bring. And then obviously we partner with internal teams to help them do their thing. So either informing the policy and regulatory affairs team or the product management team that any runs, as well as any other kind of teams internally, including the tech team, work with them to provide assessments of how our batteries should be expected to operate and things like that. This goes back really to the very founding days of FORM. FORM's, one of FORM's five co-founders was Marco Ferrara who led business development and analytics. Analytics being one of the core teams from the very beginning. And FORM's actually the first kind of experience using analytics at FORM was the company was actually founded around the idea of maybe building a 1,000 hour battery. And then we went and we looked at the different, as Annie mentioned, the different chemistries that could maybe deliver on what we thought was necessary or what we thought was gonna be important and said, okay, how would these things actually work out economically in the market? And then kind of moved that goal down to actually, let's focus on maybe 175 or 200 hours. And that was all informed by a project level economic modeling. And then actually when Annie joined, she kind of led another effort that we worked on together to say, actually what do we think is the right thing that clears in the market and then ended up going to 100 hours. So it's, I guess all of that is to say that one, this is started from very early on in the company's history. And two, it's had real impact on, how we think about the product that we're building and the thing that we're trying to go to do. Annie, if you wanna go to the next slide. This is maybe just another rephrasing of what I just said, but long story short at FORM Analytics is really or at least the analytics team is anything that touches energy markets of project economics and that is too big to excel. So primarily we're using Python-based power system models. We're leveraging cloud infrastructure to run those models because a key, I guess differentiating feature for what we're trying to do is model things in a scalable fashion and really represent the system with a lot of granularity, both in terms of how the system is operating from moment to moment in time, but also with respect to space. So we wanna be representing the details of the grid with the maximum level possible. And we're doing that informed by both existing system data, historical data and kind of forward-looking data. If you wanna go to the next slide, Annie. Part of, a big part of what motivates our work at FORM is a desire to understand the value of our product and just kind of how the system is, the power system will evolve in general. And a major driver of what we do is a belief that the best way to understand system economics is with optimization-based production costs and capacity expansion models or capacity expansion unit commitment and economic dispatch models. We confront this very often either utilities or IPPs or policymakers trying to assess the relative value of different technologies using first, a levelized cost of storage metric. We think that this is a pretty flawed way to do things in part because one is only an assessment of cost and it does not assess value. And even its assessment of cost is actually very imperfect because you have to make an assumption about what is the cost of the energy that you are charging the battery with. And more often than not, in almost every case that we've seen an LCOS or a levelized cost of storage model, they assume some flat value. So you're paying, I don't know, $20 per megawatt hour to charge energy. But of course, in the real power systems, the cost of energy varies over time and it really depends, are you charging from energy that would either be curtailed or go into the battery or are you co-located with a wind farm that has some kind of negative correlation with pricing. So when the wind is blowing very strongly, energy prices tend to be lower and so maybe you're charging with energy that is less than average price, et cetera. So really LCOS, it only assesses cost and even that it does a pretty bad job at. So we really don't like that kind of modeling. The next thing that we tend to see when people are baby being a little bit more sophisticated than traditional LCOS modeling is some kind of price taker dispatched modeling. So you'll say, okay, I'm going to take some prices that I see on the market, usually historical prices, although sometimes forward-looking prices that you get from some kind of vendor or some kind of futures market. And you say, what is the economics or what is the kind of value of dispatching this battery against those prices? This does a little bit better job of capturing costs because you may be capturing more realistic or a more realistic view when the system is charging or discharging. And at least it begins to capture value. So it begins to capture kind of what is the system going to produce in terms of returns and things like that. How is it going to benefit the system? It does that by representing different market products that are in the market. So maybe you're dispatching against, you're providing energy arbitrage, so you're dispatching against energy signals. Maybe you're providing some ancillary services, meaning very quick changes in the state of charge of the battery in order to kind of balance the grid over time. Maybe you're providing capacities. You're kind of reserving some amount of energy in the tank in order to be available during periods of grid stress. So you have some representation of market products. I have this kind of not filled in all the way because in practice, you're not really capturing the dynamics of those systems. So in reality, if I choose to charge or discharge an hour, that can actually impact the value of that service and you tend not to get that in these price taker models. So it's maybe not perfect. You're definitely not capturing how these assets are interacting with each other, meaning if I'm discharging now, is that preventing some other asset from discharging, et cetera? Maybe you're capturing a little bit about how the asset mix in the grid is changing and maybe a little bit about how that's changing associated with policy and regulatory constraints, but at the end of the day, that's kind of relying on an assumption that's happening outside the model, meaning you need to kind of assume that these changes are happening in the grid and that as a result, the prices that you see in your model reflect those changes, but ultimately it's imperfect and they're really not capturing, they're not great at capturing any kind of transmission detail or anything like that. That brings us to production costs and capacity expansion models. These are the tools that we tend to rely on most heavily because they capture the combination of these two things really captures everything that we think is really critical to understand the value of long duration storage. So together they can capture what market products are actually being offered in the system. They capture how this technology can interact with other technologies, meaning if I install this technology, does it avoid the need for other technologies, maybe avoiding the need for transmission or avoiding the need for other more expensive forms of generation? It obviously can capture the impact of policy and regulatory constraints. So we wanna decarbonize over time. So we look forward and we say, okay, what's the best resource mix to do that? To a degree, we can capture uncertainty and things like that. So this is a very long winded way of saying at the end of the day, what we think is really critical to understand the economics of these systems is very detailed kind of optimization based modeling and that informs a lot of our strategy and both around the product design but also our market interactions and our business development. So this is the approach that we take if you wanna go to the next slide, Annie. The tool, I'm gonna talk about one tool that we tend to use, it's a tool called formware, which is essentially a least cost capacity expansion model. What capacity expansion means in the power system context is essentially it's telling you what resources you should build and how you should operate those resources in order to meet whatever objectives you have within realistic constraints. And so when I say whatever objectives I have, I mean, if I'm a utility, I'm making some forecast of my demand out into the future and I'm saying I want to meet some fraction of that demand with clean energy or maybe specifically renewables and maybe there's some other constraints on my system. I have transmission representation, things like that and I need to be balancing supply and demand. Maybe I can buy energy from a market or sell energy to a market. You can kind of capture all of these things and then say, based on all of those constraints, what is the best set of resources for me to go invest in and how should I operate those resources? That is what we do with formware and that's a tool that we've built up in-house over the last four and a half years and we use it like I said to inform all of these different decisions. I'm gonna highlight a couple of projects or a couple of kind of outcomes that we've seen and just talk about how we tend, essentially show some examples of how we use formware to inform some of the decisions that we make. Annie, if you want to go to the next slide. Oh, well, this is, so I actually forgot about the slide, but long story short, this is just a reiteration of kind of all the different ways that we use analytics to form, really kind of marketing analytics to form everything from kind of business development, kind of commercial support all the way through, supporting our policy teams and our product management teams. So this is one of the kind of case studies that I wanted to highlight and just, I think it's useful because it underscores, it underscores really the value piece that I was trying to describe earlier, meaning how, using these capacity expansion models to understand the value that NASA can provide in the system. This is a case study that we built for kind of a least cost representation or essentially a representation of MISO, which is, I don't know the power systems background of this group, so I'll explain it briefly, but MISO stands for the Mid-Continent Independent System Operator. It is an entity that kind of spans much of the middle of the U.S. that operates the U.S. power grid in that region, meaning it essentially tells power plants when to turn on and turn off in order to meet demand at every different location in the system. And MISO as an independent system operator doesn't really tell the grid which resources to go by or which resources to go invest in, but it does do some kind of forward-looking planning because the system operator in order to maintain reliability, it's tasked with maintaining reliability, it needs to kind of know what assets it should expect to be online at any given point in time. A lot of the utilities within the Midwest are thinking about decarbonizing, and this case study was really a lot more relevant when the Clean Energy Performance Plan was being considered as part of the reconciliation package within the Biden administration, but so within that time one of the potential outcomes of the CEPP was that all of the states and utilities within MISO would have been incentivized to move towards 80% Clean Energy by 2030 on a path to 100% by 2035. That policy no longer exists, but the case study is still relevant because it kind of again points us to how can long-variation storage or multi-day storage provide value in a decarbonizing power system? And the long story short, essentially, the way we think about value is you say, okay, what's the least cost pathway to providing 80% decarbonization in MISO without multi-day storage? And that's kind of the middle bar. And then what's the least cost portfolio providing 80% decarbonization with multi-day storage? And what we tend to see is, without multi-day storage, we build a lot of renewables. Actually, we do that in really either case. We actually end up building a really substantial amount of lithium ion. And then we end up building a little bit of natural gas vine cycle plants with carbon capture and sequestration. That should say CCS, not natural gas CC. So we end up building quite a bit of renewables and then overbuilding or building a substantially the larger amount of lithium ion as well as carbon capture and sequestration systems to provide firm capacity. With multi-day storage, we end up building a little bit less renewables. We end up with a very similar quantity of storage, but we have to rely a little bit less on wind. And the impact there that's not shown on this slide is largely due to an increasing utilization of those assets. So we really reduce curtailment on that system and end up with essentially about a 40% reduction in curtailment. We replace a substantial amount of lithium ion. It's not a perfect substitute because these really are different assets and that provide different services. And I'll talk about that in a moment. But we replace a substantial amount of that and then obviate the need for kind of more expensive forms of firm capacity like carbon capture and sequestration. So what this shows is not only essentially how the system changes with the ability to invest in these kinds of assets, but also where the value emerges from and emerges from kind of improving that utilization and changing the asset mix in a way that reduces overall asset needs. You wanna go to the next slide, Amy? This is kind of another cut at that same story in a different region. This is for a utility in the Western United States, which is WECC stands for essentially the entity responsible for maintaining reliability in the Western US. And I think without going into too much to Jill on this slide, because it's really not necessary. The point I'm trying to make is that you can really use this kind of framework to understand both the system level value as well as the asset level value and saying for a particular project in a particular system, what is the total value that we provide in a decarbonizing portfolio? And if you wanna go to the next slide. One of the things that I mentioned that kind of comes out of this style of modeling is not only which assets should we invest in but how should those assets operate? What this shows is the operational profile of a multi-day storage system represented by the state of energy or state of charge essentially. So 100% state of charge or state of energy as the battery is completely full, 0% is completely empty. And what this shows is the profile on the next slide I have a direct comparison but the profile of how a multi-day storage system would operate and it's very different than lithium ion or other types of resources. What we tend to see is some combination of intraday battery cycling. So that's represented by these kind of purple bars on the right where you see essentially some charging and some discharging within a single day period. Maybe eight to 12 hour bursts over a period of maybe high demand or low removal energy production. Moving to the left we tend to see also, so we see that kind of intraday behavior overlaid with some kind of seasonal behavior. So in this case we're kind of charging up the battery or kind of net charging the battery over about a one month period in the spring where we tend to have high renewable generation and low demand followed by a multi-month discharge of the battery between late June or early July and the end of August when the summer demand months pick up. And then finally the last kind of operational behavior we tend to see is multi-day discharging or or charging of the battery to kind of stop gap the system during low renewable energy events. So this is the kind of behavior that we tend to see and it's one of the outcomes of this modeling and it helps us think about again where is our system creating value? And then also what do we need to go test? You know, how do we need to go design the system to operate or essentially how do we need to test the system? How do we expect it to operate? What kind of test should we run against the batteries and all of these kinds of things? And then the last slide that I have is really just comparing, you know how a multi-day storage system, this is from a snapshot from some work we're doing in California. How a multi-day storage system would operate compared to, for example, hydrogen which is providing more seasonal storage and lithium ion which is providing that intraday cycling. And again, this kind of analysis and this kind of representation can just help us understand how this asset is unique relative to other types of resources. With lithium ion, the kind of light purple here, we see a lot of basically charging and discharging every single day, in particular during the months, the kind of spring and into fall months. You know, it's essentially solid purple which means the batteries every single day charging and discharging, charging and discharging. With multi-day storage, we see that which is represented by the orange. We see that complimentary intraday and multi-day and monthly cycling. And then with something like hydrogen, we see much more of kind of a seasonal story where it's really charging all the way from late winter all the way through the fall and then kind of discharging throughout the winter, early winter into, I guess, still early winter. But I think what the other kind of key takeaway here is how these resources can be very complimentary in the system and this kind of modeling can help us understand how we expect these assets to perform and how we expect them to support other resources and providing kind of a clean firm portfolio. And I think that is the last slide. I don't know, Annie, if you wanted to say anything here. Oh, yes, just a shameless plug that we're hiring. Maybe just putting a little bit of color on that. When I joined Form last year, we were about 60 folks. Now we're about 170. We're hiring all across the gamut, both on kind of the software engineering side, on the analytics side on Scott's team, as well as on the kind of product development engineering side all across the gamut. So definitely encourage folks who are close to graduating time. Definitely check out our careers page. I will say just kind of personally, I think Form is at a very unique space where we're really thinking ahead about how we really build a new class of assets that can enable this fully decarbonized grid in a way that's really near term, right? I think a lot of people think about this in a 2050 time, a really far away timeframe, but what we're showing with our technology is that it's really possible in the near term. So yeah, feel free to ask us any questions about Form, technology, analytics. Yeah, we'll take it from there. Okay, thank you. Hi, thank you so much for a very interesting talk. My question might be a bit silly, but I was wondering what product management or product design looks in the context of these kind of businesses? You mean what did the teams do or what does the actual product look like? Maybe both, like what do the teams do and why are the teams important for the kinds of products that you guys are working on? Yeah, so that's a really good question. It's kind of what are the teams doing in a way that's kind of unique to product development in a utility space? Many, I think maybe I'll just speak a little bit to the product management side of things and then can speak a little bit towards the other engineering teams. On the product management side, we think a lot about what exactly is it that utilities really require in terms of the requirements of a storage system? And I think in product management, in particular, it's all about trade-offs, right? What's the right cost efficiency trade-off? What's a degradation cost trade-off? So the things that we think about in our team are given the landscape that Scott and his team put together with what utilities really need. How do we actually make sure that we're helping the technology team make those right trade-offs, right? And how do we make sure that we're asking the right question in a way that can prioritize their efforts? So that's what my team does. In terms of the other engineering teams, I think it's kind of similar to what you'd expect in another battery company, right? You'll have kind of product development, R&D, cell development, a lot of that's kind of making sure that the actual chemistry of our system works really well. So we've got a lot of folks on the cell development side. On the product and systems development, it's how do we really build this in a way that's very reliable across all types of kind of weather or extreme weather events that you have to manage towards the utility timeframe. And then there's also kind of the manufacturing level that as well, which is how do I not only build something to blast in the field, but how do I also build it in a way that can be manufactured easily and can be manufactured reliably? So we've got a lot of folks on the engineering and systems development. So those are the folks who are based out in West Berkeley and the cell R&D and development teams are based in Somerville. I'd also add that in the utility space, and I think this is generally true of hardware broadly, but I think it's particularly true of utility scale, bulk power applications, where the things that you're building, the unit sizes are very big. They are kind of costly just from an aggregate dollar perspective. It's very different than software. You can't afford to kind of release a product and do A.B. testing and see judge consumer reaction. You really have to kind of predict where you expect, what you expect demand to look like three to five years out or maybe in certain cases like a decade out and say, that's the product that we're gonna go build. And that kind of decision making where you're saying, knowing what we know today or what is the kind of best risk informed decision that we can make about what to go build that we think will meet customer needs, knowing that we're locking in decisions today about product design that are gonna last three to five years on a development cycle. So I think that is something that is kind of uniquely true of hardware and in particular hardware in that kind of utility scale energy space. What's the biggest product or market assumption that form energy still needs to validate? You wanna start, Scott? If I understood the question correctly, is what is the biggest assumption that a market or product assumption that we think about? Is that? If you guys don't need to validate or have a lot of questions about it. Still needs validation. Yeah, so I mean, there's a lot, quite frankly. I mean, I think there's two related things. I mean, one of the biggest things that drives value for our system, we hope to be the least cost form of clean firm capacity. You want to provide kind of reliable capacity to utilities in a zero carbon fashion and we wanna be the cheapest resource to do that. That kind of assumes that utilities want clean, firm capacity. Clean being a differentiator than just firm capacity. So I think that is validated by both the kind of investment decisions that utilities are making and obviously the broader focus on decarbonization in the United States. But we are kind of skating to where we think the puck will be. We think that that trend is going to continue and that the nature of what firm capacity or clean firm capacity looks like is going to continue to require longer and longer duration assets. And I think that the kind of related piece there is we are assuming to a degree that utilities are not going to want to, or maybe policymakers and really customers are not going to want to continue to rely on natural gas to provide that firm capacity resource that we're gonna start to demand clean alternatives to providing firm capacity. So I think that is a big assumption that we continue to advocate for showing that there are alternatives to natural gas to provide firm capacity and that those alternatives are better in many ways. But that is kind of an assumption that ultimately drives how we think about where the right market opportunities are for us. Yeah, I guess I'll add on to Scott's point, which is it's an assumption that utilities will choose to not build new gas assets, but it's also like they, a lot of the excuse that they may use is that there aren't good affordable options today. So it's a little bit of a chicken and egg. If we had a solution like ours that lasts for 100 hours that is cost-effective and affordable, then could you retire gas plants? So that is the premise that we are going out with, but still something that we actively engage with customers all the time, right? And that's where the value of kind of this modeling piece comes in is showing you how you actually deliver on that reliable piece without other gas assets. Yeah, it's a great question about like, how do you validate your assumptions? So it's actually unique to form where we have a very close relationship with a lot of these utilities. Cause when we take the perspective of we wanna help you build towards your goals, right? Depending on what's unique to your grid, what's out there, how do we actually make you enable that future and how can we do that cost effectively? So by kind of taking those data sets and kind of working very closely, hand in hand with them, here's your grid, here's how we see it. This is where multi-day storage could provide value in that system. Then that, then through that close interaction we're kind of validating that particular assumption. Yeah. Super cool to see what forms up to you. Thanks guys. Just one question. It seems like a big part of the value of forms battery is sort of its capacity value for meeting peak events. Capacity markets can be very flawed throughout the US. I'm curious how much you guys think current electricity markets need to change in order to fairly incentivize products like forms? Or do you think that their current form is sufficient for you guys? Yeah, that's a really great question. I would say that I think we pretty strongly believe that markets will need to change pretty dramatically to encourage decarbonization. Markets are, this is a really complex topic, of course, but by and large markets are very good at kind of coordinating or current electricity markets in the US are very good at coordinating existing assets to ensure the system operates reliably and cost effectively given the resource mix that exists today. They are, they have not proven to be particularly effective at driving the kinds of investments we need to maintain system, even putting aside the decarbonization objectives, they have not proven to be particularly effective at driving investment decisions in a way that is kind of least cost and effective in that sense. And that's been demonstrated, again, putting aside the decarbonization goals that's been demonstrated for existing technology. So by and large, our markets have been shown to kind of operate really well, but not necessarily kind of ensure that we have the right resource mix moving forward. And then once you start to layer on the complexities of decarbonization and what that means and in particular, the need to drive kind of innovation. And so you're not just thinking about static efficiency, but you're thinking about dynamic efficiency, meaning the efficiency of the power system over time, our markets are really not great at optimizing for that alone. So one really simple example that I give often and you kind of touched on with respect to capacity markets, capacity markets are designed assuming that the kind of reserve product, meaning the thing that will get built at the end of the day is a natural gas combustion turbine. And that kind of sets the maximum clearing price in technical terms, it's called like the cost of new entry is always based on a natural gas combustion turbine burning natural gas. That is not a zero carbon solution. So if you're kind of benchmarking the reserve price in your market against a carbon emitting solution, that's obviously gonna skew the types of resources that you tend to see in the market. So that's just one really simple example, but we could really go on all day. I mean, I think our markets are designed really about meeting short-term peaks and are not really kind of starting to think about multi-day renewable energy roles and energy sufficiency over these multi-day periods and all different kinds of things. So I would say our markets are both a marvel of kind of engineering and economics. They're really incredible and they ensure that the system, which is the largest machine ever built operates effectively, but they have their limits and will need to evolve as we push towards decarbonization. So I had one, I may follow up to that question and that is in your work, either one of you or both, do you think the way forward in this regard is educating the regulators? Because we've heard a lot from the regulators here or kind of complimentary, I don't even know who these are, but I expect they are complimentary entrepreneurs that are doing other things that would in a sense work around the status quo ante. I wouldn't even blame that on regulators. It could be other public acceptance, blah, blah, blah. Do you spend a lot of time on that? The other model could be, we leave that up to our innovative utilities to handle all that stuff. So how do you do all that? We are engaging directly with regulators and market operators. So that, again, we're playing a multi-decade game. We wanna be building the markets for the long haul. So we are working with those folks. I would also say we're working directly with entities that maybe want to move faster than the market more broadly. So either, there are very progressive forward thinking vertically integrated utilities, vertically integrated utilities are maligned frequently for maybe being conservative or slow moving or something like that, but there are many that are looking to the future and saying, we see the writing on the wall, we see the need to decarbonize, we wanna get out of ahead of this issue and start, we recognize, we've done the modeling, we recognize the kind of resource gaps and that we're gonna need something else. And so we wanna start buying in today on solutions that we think can support us in decarbonization. So there are those kind of entities and then there's also the municipalities and commercial and industrial customers that also wanna move faster than the broader grid. And so they're saying, okay, we're gonna try and push this issue forward. So there are, I think there's the customers that'll kind of move quickly and we work really closely with those customers. And then I do think there's room for entrepreneurs that can create new ways of operating markets or new financial incentives and things like that that can allow customers to understand the carbon emissions impacts of their decisions. So depending on where you are in the grid and how you're operating, what the emissions impacts are and things like that. So I think there's definitely room for regulators, customers and entrepreneurs across the board. Very exciting. Sarah conveniently arranged the talks. We had the biggest CCA in California speak last week. So I can see those as other people you could reach out to because they are similarly minded, it seems to me. That's pretty terrific. With that said, I'd like to, before I thank these guys, thank Sarah and Marlies for a terrific quarter and all of you for being here. We'll look forward to reading your final essays. If you have any questions or comments, I know I owe a couple of people feedback on some of their interests, but feel free to do so. So with that said, we'll move on to the of close and personal student session with Annie and thank very much for actually doing a great job of not only creating a crescendo at the end of the quarter but tying a lot of themes that we've had exposed here together in a very creative and entrepreneurial way. So thank you, Annie and thank you, Scott, for a great, great talk. Thank you. Thank you.