Form Energy CEO Mateo Jaramillo: Building the Largest Battery System in the World

14:17Mateo Jaramillo:Yeah, absolutely. And we anticipated the megatrend. We didn't know that AI would be present in the way that it is in the demand perspective over the last two years. But we knew the megatrends were in place, right? Electrification, broadly speaking, of industry and transportation and decarbonization in certain regions. And so that part we got right. You know, the IRA certainly was helpful in that it started to point to the fact that domestic in the U.S. manufacturing was important again. And and and storage, you know, sort of enjoys this bipartisan support sort of regardless of what your political affiliation might be.

14:53Mateo Jaramillo:We all can agree that, you know, energy storage makes a lot of sense for the grid and we should we should try and make as much of it here as as we possibly can. And so that's what we're doing. And the IRA sort of kicked off the support for for manufacturing energy storage again in the United States. And it was fully reaffirmed, to be clear, in the OBBBA, right, the reconciliation bill that came out last year under the obviously new administration in Congress. So we've been able to sort of enjoy that support. And I think it will continue.

15:23Cameron:So maybe taking a step back, I wrote a piece two summers ago called The Symbiotic Relationship Between AI, Big Tech and Energy. And I sort of predicted that with this huge boom in AI coming, there would be this interesting relationship that would develop between big tech investing huge amounts into data centers to drive AI, which would ultimately, you know, drive innovation, but also huge in energy, but also huge demand for energy. And that would ultimately be the kind of limiting input of AI. And that's, that's very much played out. We actually had Doug Bernauer, also a former Elon employee building Radiant, you know, playing into similar tailwinds with his micronuclear reactor.

15:59Cameron:um and yeah so it's quite it's kind of fascinating uh you know kind of curious what your what you see from your vantage point and whether you think ultimately this would be a net benefit for the climate or a net detractor because obviously it is driving huge innovation in energy which is fantastic but the demand that um ai is driving for energy is also kind of unseen i would say previously unseen so yeah very curious to see because you have quite a unique unique vantage

16:21Mateo Jaramillo:point yeah i i think it's there's maybe three ways that are that are you know importantly intersecting for us. One is just on the pure demand side. So you're not like, you know, this, this period of demand is really sort of unprecedented for, I mean, sure, we were growing at, you know, at the same rates, maybe 50 years ago, when the basis was much, much, much smaller. And now we have a fully built out grid that's growing at those rates again, which is kind of incredible. So just the demand signals for electricity, broadly speaking, speed to power, or how do we interconnect these loads? The other is specifically, you know, Take the case of this Google project, right?

16:55Mateo Jaramillo:They specifically wanted to do that, you know, that we would be included here. And so the hyperscaler is driving the innovation aspect of that load growth, not just sort of, you know, load growth all by itself. But, you know, what are the tools and the technologies that are maybe, you know, at that nascent stage today that can really help drive this thing going forward? And specifically, I don't find those.

17:16Cameron:And just quickly on that project for our listeners, what they've done is they've ordered a 100-hour battery for you from you, right? to power one of their data centers or to provide storage for one of their data centers.

17:27Mateo Jaramillo:Yeah. And our customer is actually Excel Energy, the utility in that case. And that utility is providing a portfolio of resources to Google. But we are the reliability asset. We're the capacity asset, right? And so in that case, showing that actually this duration, this 100 hours actually does let you compete with gas in that case. So that's the second one, specifically driving the innovation access. And then the third is, and I touched on this briefly, we are huge optimists that the model capabilities for driving material science innovation is really just getting going. And as with most things, if we aren't there already, it's coming imminently for data haves and data have nots.

18:09Mateo Jaramillo:And Form has the world's most robust data set on iron air batteries. And we've been spending the last nine years accumulating that data set. And we have tens of millions of operating hours, test data, full systems, you know, deployed systems. And now we're seeing an extremely virtuous cycle between that test data, the performance data, feeding it back into the models and getting, you know, pretty astounding directional results. run these tests, probe these variables, getting the physics-based models that we already built to be fully harmonized with the empirical data that we see. It's sort of shocking how little we actually know about electrochemistry.

18:49Mateo Jaramillo:I'll make a general statement about that. And these models are converging, the models and the empirical data in a way that we have never really seen before. So that's the third way that we see this really driving the capabilities of the technology as well, right? Using the tools themselves.

19:05Cameron:Well, energy scarcity is often defined civilization. Do you think we're approaching a period where, you know, the cost of energy is going to trend towards zero and with storage and renewables, we're essentially going to have close to free and abundant energy. Do you think that's possible?

19:19Mateo Jaramillo:I think it's possible. You know, we're pretty good at putting up roadblocks to achieve. But it's, you know, probably, and we already see this happening, right? Right. Regions that are able to build capacity are going to benefit from from this boom right now. And, you know, what we should be doing is thinking about how to unlock the existing resources that are already built to make them as highly utilized as possible. And we should be building more things again. I think, you know, certainly the position in the states is, you know, unfortunately calcified to how do you stop building things, you know, for a lot, especially coming from sort of the left side of things, you know, to now again, we'd have to build.

19:57Mateo Jaramillo:and we should be building, right, for the benefit of all of us. And, you know, this notion of abundance, being able to tap into sort of that mindset again is important for us going forward. So I think if we're able to, you know, lower the bar a little bit for sort of how we go build big things, I think that's possible, certainly, as long as we kind of don't get in our own way on that one.

20:20Cameron:And how do you think about geothermal and nuclear? Some people think that this is the future and potentially, you know, renewables and storage will be leapfrogged by some of these new technologies that create energy at more scale, more cheaply. How do you see the landscape and the more fitting in together with what you do?

20:35Mateo Jaramillo:Well, I mean, the market is so massive that it's never going to be a zero-sum game. There's not going to be a single technology that dominates because of cost, because of local dynamics, because of local resource availability. it's almost impossible to conceive that there's going to be a single tech that dominates here. And in the end, you know, given the way that we operate, that we know how to operate a low cost, highly reliable grid overall, you want asset diversity, right? You want geothermal, you want wind, you want solar, you want hydro, you want, you know, nuclear of whatever kind is cost effective, So I think we're going to see that continue to be the case.

21:17Mateo Jaramillo:You know, we are very good at balancing a complex grid today. And there's no reason to sort of back away from that and have, you know, a single shot approach, which, you know, suffers from other potential failure modes that we don't want.

21:31Cameron:Incredible. We're going to shift gears now and talk about your time at Tesla. um you've worked with you know on paper the most successful entrepreneur of all time in terms of value creation what are some key lessons from working with elon musk uh there are so many uh

21:48Mateo Jaramillo:you know one of it is and one that i directly took into founding form is um why not go after the most ambitious hardest to solve problem i like to work hard anyway i might as well work on something that is like that really has a huge payoff and and the other the upshot to that is um all the great people want to work on meaningful problems right that no phenomenal person like technical person market whatever it is wants to work on a marginal problem really and uh and the talent density at tesla was just incredible um and it was you know particularly destructive to me that the deals so that that we did with daimler and toyota uh that was my day job at Tesla for the first five years.

22:34Mateo Jaramillo:In background, literally my nights and weekend job was starting what became the energy effort. But primarily, I was responsible for the powertrain business for the first few years there. And so Tesla did these deals with Daimler and Toyota and they were, you know, Tesla was developing the electric powertrain that would go into either, let's say, a Daimler B-Class or the RAV4 for Toyota. And it was like shining a light in a cave and like these people inside of these massive companies like found their way to work on this project. They were compelled to work on this innovative, you know, bleeding frontier project.

23:06Mateo Jaramillo:And dare I say, they were the best people in those companies. Right. They like they just they had to find a way to come work on this amazing stuff. And and, you know, so that the lesson for me was like shine the right light and you attract the right people, you know, for the for the right kind of really hard problem. Like it's a little counterintuitive, but the harder the problem, the better the people you can attract.

23:24Cameron:The hardest problems attract the best people.

23:26Mateo Jaramillo:Yeah. Yeah, exactly. And, you know, you have to phrase it right, of course, and you've got to like, you know, make sure that you can distill it down to a nice, clean narrative for why any of this matters. But, you know, the mission is what drives people and the hard mission drives the best people, I think. And so, you know, from the beginning of forum saying we're going to solve a problem people think is not possible to solve, i.e. come up with a battery cheap enough that the duration is so long that you can compete with fossil fuels in the market and solve this intermittent issue. That's highly motivating to phenomenal people.

24:02Mateo Jaramillo:And so that's a very deeply imbued lesson that I saw at Tesla day in, day out. It was the quality of the people that let the company whistle past the graveyard half a dozen times that we did, the stories that don't get told there. But you need that kind of commitment and quality out of folks to go through these really hard pathways.

24:23Cameron:Anything you would not emulate? Oh, man.

24:28Mateo Jaramillo:Certainly.

24:32Mateo Jaramillo:I think we've taken a slightly different approach to deadlines. I mean, Elon loves to sort of put just insane deadlines out there for the team. And I think, you know, under his management style, it works. but there's also sort of an acceptance that he's doing that intentionally and people know that he knows, that they know, that that's not... There's always like a convergence.

24:56Cameron:The boy who cries wolf at some point, yeah.

24:58Mateo Jaramillo:Yeah, exactly. And Tess has been able to pull off phenomenal things and almost always later than what Elon originally said. And part of it is just like, I'm not, never aspired to be, He never thought that it was Elon, so I should not manage the way that he does. And so I try and pick a slightly different tact on the deadlines, which is to say, pick aggressive but achievable, that the team believes is grounded in reality timelines. We don't pick timelines at form that are easy to hit, to be clear. And we have missed deadlines because we've been too optimistic and too aggressive up front. But but nevertheless, there shouldn't be sort of like a, you know, knowing acceptance that that that are quite, you know, unsaid acceptance that the team knows that my deadlines are unrealistic, that they're going to pretend to hit.

25:53Mateo Jaramillo:And I pretend to believe that they're going to pretend to hit, you know, like that. You sort of reduce the wearout factor around that a bit. You know, Tessa does have a very high turnover rate. And, you know, maybe we can reduce that a little bit by sort of reducing the turn a little bit there. So that's one stylistic difference. But on the other hand, there is no style like Elon's. Very fair.

26:16Cameron:And you've hired a thousand people now at the company. Have you developed your own rubric for trying to identify A-plus talent or people who are a good fit for the culture?

26:25Mateo Jaramillo:Yeah. There's nothing like demonstrated success. I mean, people can interview phenomenally well and have all the right answers, of course. Show us known good work product. That's sort of the thing that we're looking for. And then talking to people who've worked with them before. I don't know that there's, certainly there is no perfect approach, but the old saying is true, right? A's hire A's and B's hire C's and C's hire T's. And you just have to keep the talent as high as possible.

26:55Cameron:And do you give people a long time to ramp or are you pretty explicit on, you know, you have a fairly short time to prove value?

27:02Mateo Jaramillo:I would say we've evolved on that. But the company has gone through pretty distinct phases over the nine years. And you might even say that we've been three distinct companies along there. We were an R &D company, to be clear, for the first few years. Super heavy on scientists and PhDs. And the mindset and the methodologies that works for that phase does not work for the engineering phase. You actually have to design a product and it has to be able to be manufacturable. And we were that for a couple of years. And we were that in the absence of also being a manufacturing company. And it turns out the manufacturing mindsets and time horizons that matter for success are very, very different.

27:40Mateo Jaramillo:And so whereas early on, I think there was a lot more latitude given to folks for timelines and execution just because that's what scientists require. It really doesn't work in the manufacturing space. And so I would say now we do operate on a much more sort of clinical time-based assessment for whether or not somebody's working out in a way that we just didn't the first two-thirds of the life of the company. And during that early period, were you working closely with Professor Yet Ming, who introduced us and is one of the few people to have been involved in co-founding multiple Climate Unicorns at this point?

28:12Cameron:So, yeah, it would be great to hear a bit about how you two collaborated together.

28:15Mateo Jaramillo:Yeah, Yet is sort of the founder glue between all five of us co-founders. And Yet's just a phenomenal material scientist and person. Lovely person.

28:26Cameron:Yeah.

28:27Mateo Jaramillo:He's just an amazing guy. It's been such a professional pleasure to get to work so closely with him for nine years. And, you know, talk about talent. Like, he attracts absolute top-level talent. And our CTO is a former, he did his PhD with YET at MIT in material science. And Billy, his name, Billy Woodford, has just been, you know, phenomenal technical leader for the company over the nine years. And, you know, he's a PhD. So we've brought on, you know, subsequently folks who are, you know, amazing engineers, design engineers, manufacturing engineers, that kind of thing. But yeah, yet and the science team and, you know, that ecosystem has just been, you know, critical to the success of the company throughout.

29:12Mateo Jaramillo:And even as, let's say, we sort of transitioned into engineering and engineering to manufacturing, what never slowed down was the core science advancement. You know, I mentioned that we had these new learnings on iron. You know, the team is just continuing to drive the fundamental knowledge and performance of that, just the base electrochemistry. And we now have a very good sense for what we see in the lab today, knowing that it's going to show up in a product in two to three years. And so we have a tremendous amount of confidence in the product roadmap because that cycle now feels very, very mature for us as a company.

29:49Mateo Jaramillo:and that engine that in that like core scientific engine has never slowed down and so we feel now that we've sort of been able to land the engineering and now the manufacturing piece of things uh we feel really good about sort of the pathway for the product and the innovation sort of um inertia that we have it seems it seems like sitting slightly outside it but uh one of the

30:07Cameron:things you guys have managed to do it seems essential to success is having the scientific engine you know which kind of stemmed out of you know mit and yet ming having someone like you build the market, make sure that there is commercial demand for it. And then over time, ensuring you can actually scale up and manufacture it. I think for a successful hard tech startup to succeed it, I think you really need all three.

30:28Mateo Jaramillo:Yeah. And, and, and, and having the balance between those two things, as I mentioned along the way, and, and I should note, you know, part of the reason why we were able to do that is because of, it was all grounded in, in deep analytics by my other co-founder, Mark, Marco Ferrara, who also has a PhD in MIT as it happens, in his case, in nuclear fusion of all things. But he built these very complex co-optimization models that let us understand that sort of solution space for what battery to go produce in the first place, right? 100 hours is like, that's not just a finger in the air exercise. There's a lot of very deep quantitative work behind it.

31:06Mateo Jaramillo:And that let us go engage the utilities and the buyers years before we had technology that we could point to. and sort of start that clock on getting those markets running, that engagement with Excel, it's five, six years. Deep engagements and they wouldn't do that if they didn't believe that the math fundamentally supported the value of what we were talking about. And we only could do that because of these what we call capacity expansion modeling tools that Marco built.

31:35Cameron:It's a nice round number, 100, too.

31:37Mateo Jaramillo:Yeah, exactly. Exactly.

31:39Cameron:What do you believe about the future of energy that very few people agree with you on? Oh, well, I'm happy to say I think people are starting to agree with me.

31:50Mateo Jaramillo:It's becoming consensus. It's becoming consensus. I think there's a lot of dismissal, a lot of incremental thinking in the market. Now we'll go two hours, now four hours lithium ion, now six, what about eight hours? You may remember the eight-minute abs thing. And, you know, it's like, what about seven minute abs? No, no, six minute abs, right? And, you know, we sort of blew up that notion of incremental thinking. And I think that's what this Google project does. But I also think that we are, back to my point about the frontier of electrochemistry, we really are just scratching the capabilities of energy storage, broadly speaking.

32:28Mateo Jaramillo:And what I mean by that is, you know, we generally think about storage as a secondary device. You discharge and you charge, right? sort of rechargeable battery. But we increasingly are taking primary approaches. In other words, you only discharge. So think about it as two separate processes. You use electricity to charge something, and then you discharge that thing to create electricity somewhere. But they don't have to exist in the same device in the same place, right? And so once you sort of take those apart a little bit and say, well, I have primary charge and I have primary discharge, but I can complete sort of a system level view of that.

33:05Mateo Jaramillo:Now you open up these possibilities that we really don't think about. And we have a grant from the U S department of energy for iron processing that takes half of that. So you take, you take essentially iron ore, right? The oxidized, the discharge state of iron, and you add electricity and you create a metallic iron. And that's, that's one way to do it. And that's for steelmaking. So how do you decarbonize steelmaking and do it in a cost-efficient way and scalable way? And the other half of that is you take metallic iron and you discharge it. So now you have a metal fuel that you can sort of move around as you need to.

33:44Mateo Jaramillo:You can recharge in one place and discharge in another. And think of that as like a standby generator, right? Very, very low cost, extremely reliable, and extremely scalable.

33:56Cameron:And in that case, you could have 2 ,000 hours of fuel on hand if you wanted to, right?

34:00Mateo Jaramillo:it really just depending on sort of the metal that's there. So I think, you know, that kind of thinking about what energy storage is and how it fits into the market, we haven't really talked about people don't know. So maybe it's not, maybe it's so unknown that people don't disagree with me about it. But, but I am convinced that that that sort of is the next frontier for the way that we think about storage on the grid.

34:20Cameron:Thank you so much for joining us on Giant Ideas again, Mateo, and sharing these wonderful snippets of your life. Very excited about Form Energy and its future and it's been so great chatting with you.

34:30Mateo Jaramillo:Amazing to be here. Thanks for the chat. Super fun.