2026 Investment Outlook and Predictions

Listen to our 2026 Annual Investment Outlook Panel with four top VCs. Get their perspective on the investment climate in 2026 and their plans to invest specifically in AI based startups. See how they did with their 2025 forecast and what their big predictions are for 2026.

Tim Porter, Managing Director, Madrona Ventures
Tim joined Madrona in 2006 and invests in B2B software companies in the Pacific Northwest. He is currently interested in intelligent applications and SaaS, cloud-native software infrastructure, the modern data stack, machine learning, DevOps, and cybersecurity. He is also a board member of numerous Madrona portfolio companies.

Sudip Chakrabarti, Partner, Pruven Capital
Sudip is a partner at Pruven Capital where he works with companies that are transforming the enterprise, cloud and infrastructure markets.  Sudip's past investments include Exabeam, Heptio, Serverless.com, Datacoral, Spotnana, Temporal, Tesorio and Polly. He had also been a board observer at Databricks, Digital Ocean, Actifio, Mesosphere and Samsara.

Kellan Carter, Founding Partner, FUSE Ventures
Kellan Carter is a founding partner of FUSE where he focuses on early-stage investments in intelligent software in both horizontal and vertical categories.  He currently sits on the Boards of Zuper, Pictory, Avante, Owl, Xemelgo and PDM Automotive.

Joaquín Gallardo, Senior Vice President, Tech Banking at Silicon Valley Bank
Joaquín is a Senior Vice President at SVB, a division of First Citizens Bank, in our Seattle/PNW market focusing on enterprise clients. In his role we helps Series A and beyond clients to scale their finance stack with venture lending alongside global treasury and liquidity solutions. Before joining SVB Seattle, he lived in San Francisco, learned to code at UC Berkeley, and helped to co-found a pre-seed company. Joaquín holds a bachelor's degree in economics from George Mason University. He lives in Ballard, Seattle with his wife and two children. In his spare time, he gets to think about how he wishes he had more spare time.

Brought to you by TiE Seattle
Hosts: Shirish Nadkarni and Gowri Shankar
Producers: Minee Verma and Eesha Jain

Brought to you by TiE Seattle
Hosts: Shirish Nadkarni and Gowri Shankar
Producers: Minee Verma and Eesha Jain
YouTube Channel: https://www.youtube.com/@fromstartuptoexitpodcast

Transcript

SPEAKER_08 0:00

The prediction for 2026 Tim.

SPEAKER_02 0:03

I think that Apple's going to have to make a big AI acquisition. And I think SpaceX will be the first of those, you know, big five to go public. Those would be my two capital markets predictions. Those are always the ones that are a little easier to measure, like it either happened or it didn't happen. So I'll I'll say those. And then I will say that the adoption of agentic AI in the enterprise will be meaningfully measurably higher across the course of the year, across all these use cases we've mentioned in more.

SPEAKER_01 0:39

Welcome to the Startup to Exit podcast, where we will bring you world-class entrepreneurs and VCs to share their hard-earned success stories and secrets. This podcast has been brought to you by Thai Seattle. Thai Seattle offers a range of programs including the Go Vertical Startup Creation Weekend, Thai Entrepreneur Institute, and the Thai Seattle Angel Network. We encourage you to become a Thai member so you can gain access to these great programs. To become a member, please visit www.seattle.tai.org.

SPEAKER_03 1:28

Hello everyone and happy new year. Hope you are off to a great start in 2026. As you may know, at the beginning of every year, we host an investment outlook panel with some of the top investors in Seattle and Bay Area to understand the major trends in VC investing. Today we are very pleased to have with us Tim Porter, who's the managing director at Moderna Ventures, a top VC firm based out of Seattle. Chudeep Chakra Bharthi, a partner at Proven Capital, which is an early stage investor in enterprise IT software from the Bay Area. Kellen Carter, a general partner at Fuse VC, a major early stage VC in the Seattle area. And Yakim Gayado, a senior VP at Silicon Valley Bank, a major venture debt lender for startups. So with that introduction, over to you, Gowri.

SPEAKER_08 2:31

Hello, everybody. Welcome to our annual investment outlook episode. Our first guest is Tim Porter from Madrona Ventures. Hello, Tim. Welcome back to our annual edition of uh investment outlook uh episode. You have now done it from the very beginning. So we look forward to hearing your views on 2025 and what to look for in 2026. First, uh right off the bat, describe uh 2025 for you. How was it? Uh was it different than 2024? How was your scorecard that you shared with us uh at the beginning of 2025? Well, how was it for uh at the end of the year?

SPEAKER_02 3:10

Yeah. Well, you'll have to score me on uh what my predictions were last year. First of all, thanks so much for having me back. It's always a lot of fun. I feel fortunate to have known you, Gary, for a long time in this tech ecosystem, and um it's always a pleasure to be able to have a chance to talk with uh you and Sharish. So so thanks for having me back. So thank you. Uh kick off with uh 2025. Look back first. Yeah, it was a busy year. We made a lot of new investments, you know. I would say, which we're excited about, you know, obviously. There's a ton, ton of innovation happening in the market. Um, you know, if anything, you know, compared to like what we thought our pace would be, like we were like we were hot. We were like on, you know, in some ways pushing the comfort level of of the number of new investments. I think we invested in um 25 uh new different companies. This doesn't, you know, count follow-on rounds, which is probably normally it would maybe be 16 to 20. We did 25, I think almost uh $100 million of new investment, you know, not counting follow-ons. And so that's a busy year. And um we saw a lot of things happening. The pace of new company formation, both in the Pacific Northwest as well as across the country and the world, is very high with very high quality. And then you have a bunch of companies that are doing really well. And so that leads to you know later stage opportunities as well. So as you think back over these last years since of the pandemic, there was a period where you know there wasn't much happening in the later stage land, but new companies kept getting created. And now this past year, you know, we've seen a period where there's lots of new company formation and a bunch of companies doing well, and a lot of capital and a lot of opportunity, uh, that brings us challenges. There's also a lot of noise and high prices and you know what's durable, right? You know, things we'll probably talk about. So it's not like it's easy, but it is exciting.

SPEAKER_08 5:00

So since the pace of uh investment went up, was it all primarily driven because now there was AI was delivering on promises that startups could really start digging into it? Because there was all this noise in 23 and 24, and people are trying to sort it out. Was 25 defining that you guys felt like we have to invest more in terms of number of transactions?

SPEAKER_02 5:25

Yeah, AI was is definitely, I mean, gosh, like what's not AI? You know, in some, you know, AI is software, and we're software investors, so it's it's almost hard to decouple. But it it wasn't 100%. You know, we I would say we made, you know, we made some investments that were in in businesses that weren't you know purely created for AI, even but even those, for instance, we invested in a company called Revive that helps e-commerce and and retailers with returns. And then how do you take those returns and sell them again or recycle them or do whatever's most efficient? And they definitely use AI to do some of those things more efficiently and to run their business operations, but it's not an AI company. So that's a massive trend that doesn't involve purely AI. But most of the businesses that we invested in were taking advantage directly of AI. It could be an AI native company in the sense of this company would have never been built if there wasn't generative AI. Uh and then there's a lot of other ones that are reimagining long-term parts of the business or parts of software where now with AI you can reimagine those workflows, do more automation, find insights more quickly. So that is definitely the bigger driver on our, you know, our later stage investments. And just to remind people, you know, we're kind of from formation stage pre-seed through series B. You know, about a 25 to 30% are like those pre-seed right at the start, about 50 to 60% are those, whatever your second round is called. And then about 15% of the deals are those kind of series B stage. That turns out to be more like 35% of the dollars, but only 15% of the deals because they're bigger checks. So those later stage ones where we're writing our initial check, those were largely companies that had grown very quickly using AI. So one of them that's in California that I'm thinking of is called GrowthX, and they help companies do lead generation and marketing automation using AI. And a big part of that is how do you use these regenerative engines, ChatGPT, et cetera, to find customers. You know, who we all do this in our life, right? You want to buy some new product, what do you do? Like you go in ChatGPT and ask it like which one should I consider and what's better and why? So that's a new place to find customers, not new in 2025, but new in the last two years. And GrowthX is a company that's gotten expert at using those AI tools to help companies do marketing automation and was growing like gangbusters. That was one of the companies that we invested in out of our acceleration fund.

SPEAKER_08 7:50

Right. So since uh uh Madrona as a fund invests at every stage, you're stage agnostic, but you're uh, you know, uh yeah, you are more founder-centric, if I could use that word, right? Has the valuations uh shifted in 2025 because this AI layer got there, people can build faster or maybe show growth quicker? There was a catalyst that was not just capital. Capital was a huge driver of growth. Looks like you could grow before even you take meaningful capital. Therefore, is value are founders coming with different valuation expectations at any stage?

SPEAKER_02 8:31

Yeah, I'd say valuations are running hot. But it it uh I'll I'll give some nuance to that. So at the very earliest stages, you know, new new companies, there are certainly deals that I would say with good founders in good spaces using AI, you know, where the initial you know pre-seed round is, you know, 13, 15, 18, 20, 25, you know, which it's I mean, you and I remember days when those deals got done in, you know, single digit, you know, pre-money, but you know, in any in that 15 to 25 million dollar range, you know, that doesn't feel overheated, you know, for good founders, um, you know, in a good category. But then there's other ones who, because of the track record, the case case, whatever, where you see somebody right out of the box, you know, raising $50, $60 million at, you know, $300 million. Um, yeah, you know, you got to really believe that that's gonna be a big outcome to like consistently, you know, make good returns for your for your shareholders, you know, when initial money is going in at hundreds of millions. And so that dynamic of seeing like initial rounds, I thought, I think somebody I saw article called it a instead of a seed round, a coconut round, you know, because of the size of the you know, the size of the check. Um, you know, I think that's a sign of the times. And it uh part of it is that once these companies take start growing, a lot of them are growing really, really fast. So the old were days of like if you triple, triple, double, double, double, go public, you know, now it's like, you know, one to ten, you know, instead of you know, one to four or something like that. And so if you don't get in soon, it gets even more expensive. Um and you sometimes can truly justify, you know, a higher price based on if this company grow keeps growing this quickly, we'll grow into it, you know, in in you know, one to whatever number of years. But then there's also a lot of FOMO and there's they're continue, you alluded to it, there's just a lot of money and a lot of firms chasing, you know, these deals. And, you know, when you have companies like certainly OpenAI and Anthropic on the far outlier end, you know, of success that are reaching, you know, hundreds of billions of dollars of valuation, you know, you can justify like, well, this might seem expensive, but guess what? This could be a $30 billion, $50 billion, $200 billion outcome. You can justify a lot of things. So I and I think in this market, you are absolutely gonna see more winners like that created. Historic companies that couldn't have been created before, but then there's gonna be tons of losers. Like it's always the story of venture forever. It's a power law where you have a you know a smaller number of winners and a larger number of losers, but it feels like in this market it's all it's amplified. That power law is amplified where you're gonna have even bigger winners that everybody chases, and you're gonna potentially have even more losers just because of the sheer number of companies and the amount of capital that's going into them.

SPEAKER_08 11:14

You alluded to IPOs, right? You just said you know, usually people went down the path of exit, right? As part of there's an investor exit, not company exit. Investor exit. We've not had much in the way of big IPOs for a while. A few years, right? There's some signs that it could come back. Is your belief the economy macroeconomic conditions are ripe for it, or maybe it's regulatory? Could you talk a little bit about is this twenty twenty's time when you predict IPOs could make a comeback? And also your views on the macroeconomic conditions to make any of it possible, whether it is whether it is exit because of IPO or is it five days could happen more. Both of those were quiet for a bit, if you if I may.

SPEAKER_02 12:01

Yeah. I mean, we we really have had a four or plus year drought in uh tech IPOs. You know, there have been a few, but not many. And so I I do think this is the year that that dam likely breaks. And you know, there's five mega companies that everybody's watching. OpenAI, Anthropics, Stripe, Databricks, uh, and SpaceX. I think it's it's highly likely that at least, you know, two, maybe more of those go public this year. These are all, you know, more than $100 billion, and in some cases, more than trillion dollar potential market caps. I think those will be, you know, just massive bellwethers for the overall market. You know, if those go and go well and and start to, you know, one after the other, I think you'll see even a lot more. I'm hearing from my my banker friends that the the backlog and the activity, the private file and people getting ready is like that activity is really picked up in a in a bunch of names of companies that are far along that aren't, you know, one of those five mega names. So I do think we're gonna see a big uptick in IPOs this year. We'll see. I, you know, I would have to, if I had to pick, you I would say, you know, probably SpaceX or Stripe would be the first, you know, of those to go, but the ones that'll be most watched, well, they'll all be highly watched. But OpenAI is kind of the one that's the the biggest one. I also see so NA is always harder to tell. I would say just within my own portfolio, my drones on portfolio, there's more activity for sure, including some of more size than the then you know, the small MA kind of never goes away. You know, a few different things. I think you see bigger companies who want to buy, you know, businesses, products, talent in AI. You see the AI companies, you know, voraciously buying. You know, we sold StatSig to OpenAI last fall. That was a you know a big transaction that was really meaningful for both sides. And so I think you're gonna see more activity kind of across the board. The the other one is I think you'll see more of these private to private, you know, mergers, you know, where you have private companies that are of reasonable meaning, reasonably meaningful scale, perhaps could have been public companies in years gone by, where now the bar for kind of size plus growth rate plus profitability means that some companies will need to combine, which is always easier said than done. There's lots of pitfalls into doing that successfully in order to create, you know, a big enough asset with good enough margins, take advantage of the synergies, et cetera. So I think that's another thing you'll see more of this year.

SPEAKER_08 14:29

What about the economy in general? I know that that's not a driver for investments, but but you generally watch it because at the minimum it's um something that everybody takes into account from an emotion perspective. So as that um is it better now? Because it it's there's a lot of change happening.

SPEAKER_02 14:50

Man, I know we don't have a crystal ball. Like as you alluded, you know, we think about we're gonna invest, we're gonna have eight, ten, twelve plus year time horizons on our investments, and you're gonna have up cycles and down cycles and to be successful, and you can't just try to time what's happening in the macro. But up to your point, of course, it all trickles down, it all matters. Um, I would say, you know, so think back beginning last year. I think we had a position, I probably said it on this podcast, you know, that it was gonna be a more aggressive risk-on environment. And then the first quarter plus was a very much like, oh my gosh, there's so much volatility, everyone was sort of frozen. But then as you got to mid-year in the second half of the year, you saw a lot more of this aggressive risk-on, you know, investments that we talked about, MAs starting, et cetera. I think where you are now is it continues to be an aggressive risk-on environment. You know, there's uh there's capital flowing uh on the investment side, you know, enterprises are spending money. There's these super exciting, you know, new AI services. I think that that's all happening in a weird backdrop where it's just like there's so much geopolitical, you know, in my opinion, kind of awfulness, you know, happening out there that it feels weird sometimes. You're sort of this tech, you know, you're operating in this like ripping market, but yet there's so much uncertainties. Like we're just putting our head down and and working. Um, and you know, if we start to see the you know, budgets shut or economy change or something, we need to be able to be nimble. In the meantime, we just think there's a lot of opportunity to keep driving towards. And then I think this whole question of like, is there AI ROI is another interesting one. So, like, set aside the geopolitics is like this AI stuff really work. And I think we're kind of in the natural part of the adoption cycle where people realize like it's easy to demo this stuff, it's hard in production, there's lots of things you have to get right, and that's gonna cause some use cases and some implementations to not be, you know, a panacea, you know, on day one. But I think we're already seeing a bunch of use cases and places that you do get incredible ROI. And so we're long-term believers in that and that you're gonna see amazing ROI from AI broadly, even if specific use cases and implementations and things in the enterprise, you know, there's a crawl, walk, run aspect of it. Uh, and we could talk more about some of the places that we're seeing a lot of, you know, obvious ROI and some of the places where it's probably still early.

SPEAKER_08 17:12

Let's kind of look at, you know, you're gonna make, let's assume you you make the same number of investments this year in the early stages, 25 or so. Is this then the year the agentic takes root? Because you as a as a venture fund have really been on the intelligent application thesis for a long time. This is even pre this AI uh run, right? You you guys have always believed in uh intelligent applications and and of course founder fit. These two have been cornerstones of your investment. But uh, as a gentic is taking root, and therefore your intelligent application thesis uh now really blossoms into exactly what um what AI's promise might be from an investor perspective.

SPEAKER_02 17:58

I think so. And uh I think to my earlier point, it it's a continuum, and so it's not in all use cases and categories simultaneously. But I mean, take a few examples, right? So in cogen and for in developer tools, I mean, it's incredible adoption and incredible efficiency and incredible ROI. You know, the the growth of companies like Cursor, um, I think you are seeing what I would call, you know, truly intelligent agents, you know, things like Devon, you know, from from cognition. Now, even this is complicated because the difference between writing you know more lines of code faster doesn't mean you know you're necessarily shipping quality working things faster to customers, and that's the only thing that matters at the end of the day. So, but I think you know, we've seen lots of examples of just things being built in time frames and in ways that they wouldn't have been never possible before. So I think that's a an area of clear deep adoption and and benefit. External customer support, you know, areas where, you know, historically there were things like IVRs that like everyone hates, like, you know, AI voice agents way better, right? And you can sort of language what you want, you know, take you to the right place, answer your question if it's available in the database, it's actually a better experience. And and companies save money. So you have, you know, cut companies like you know, Decagon, you know, growing really, really quickly. That's that's not one of our investments. But there's a there's a set of companies in that space um that have done you know extremely well. I think AI for legal, you know, that you're seeing a lot of adoption in law firms and now in internal legal departments where redlining and contracting and workflow, you know, I think there's a lot of adoption in ROI there. Some of the areas we invested in that I think are coming and internal support. So internal service management. We invested in a company called Ravenna here in Seattle that helps automate creation and tracking of tickets, answering questions for employees. And I think that's neat because that model that IT's used for a long time, like you've got a question, we log a ticket, we resolve it, we track how many we resolved, how long it takes. That's kind of how all of us work. Like you need a question from sales, yes, sales, you need a question from legal, HR, but it's more ad hoc. I think AI provides sort of a system of both record and action. And a company like Ravenna AI is providing that for all types of internal service management and support. I think, you know, autonomous GTM is another interesting area around sales. I think you could argue that this whole, you know, there was a lot of adoption, for instance, on things that was like AI SDRs, like, hey, I don't, you know, I don't need a person anymore. My AI is gonna send all these emails and convert and all that. And and while that is kind of true, there was also a lot of like, whoa, that was a lot of spammy email that didn't really help. So that, you know, I I'm not sure that on the other hand, you know, broadly around there's too many tools and sales, it's not automated enough. How do you bring those things together? Giving, I mean, one of a company that we invested in, I work on Clarify AI, autonomous CRM that's all in one across your call recording, outreach sequences, data enrichment, et cetera. So that is a big theme on like how do you make it easier for enterprise adoption? And it's an interesting time because you have this wave of LLMs. You did have some, you had a bunch of companies that were pre-LM. You've got some companies that were super early in LLM, and now in some of these categories, you're companies that are starting right now, where it's like, okay, now the tech is really ready and you can build the product exactly and meet customers where they are to create this magic. And so you see a little bit this fast follower, and some of those now are the ones that are really taking off.

SPEAKER_08 21:25

So talk a little bit about founders, right? Because you guys have really made that the cornerstone of your investment, right? Of any investments that you make. Founders today need to not only have good engineering or technology capabilities, but looks like they need to understand go to market much, much earlier than they ever would have in the past. Because there you kind of made strides, worked on it. Now you're scaling. You got to figure this out quickly, otherwise somebody else has figured it out. Do you see GTM as becoming a moat in it? itself than just pure technology? Or is this accelerated GTM that's getting there that founders now need to have that skill on day one? It's not like a we can hire somebody, we'll learn this, you know, we'll get a b build a good product. From a from an investment perspective, how has that come into play for you guys, both looking back and looking forward?

SPEAKER_02 22:23

Carol, you broke a up a little bit in the middle of that question. So if my answer doesn't hit it exactly, we can edit edit back here. But I'll I'll jump in. So I think you're right, you know, that we're at the end of the day, AI automation, it's still about the founder. It's still about people and while AI can create a lot of efficiency, it doesn't create true intel it's it's another tool to go to go faster, to be more efficient. It's not going to make you successful on its own. Specifically in the area around go to market, it has, you know, I think it has evolved. I think you you need to as a founder understand how you and you can adopt some of these tools to find initial leads. The way that you can do founder selling, I think in some ways can scale a little farther and be more efficient before, for instance, you have to hire your first salespeople or expend some of the traditional marketing budgets. So I think you know being smart about how do you leverage AI in all parts of your business, probably particularly go to market, given many founders that we back are are technical product people, right? And that's we'd love to basically have the idea of the problem, you know, how to build a beautiful solution, the selling, you know, part of it is often the okay, now how do we go either learn that or augment that, you know, et cetera so I think um I think that leaning into how you're using AI across every function, particularly go to market, particularly in the early days is absolutely a critical success factor. But it's also one that we feel like we can help founders, you know, and that you can you can come up to speed.

SPEAKER_08 23:54

So this leads to the other important question, right? Is the Motes changing? Meaning you now need to have many things. You can't just be you need to understand the vertical, you need to understand the workflow, you need to understand, you need to build the technology, you need to have go to market. Seems like now the founders have to assemble different kinds of teams than they might have in the past. Where the first the past could be I'm going to hire 10 engineers, right? Raise capital to hire 10 engineers. Looks like you got to hire a mix even on day one because design, UI, all of this is becoming important because my assumption is that the coding is now less compared to in the past where you had a code like ours, you code much less how does how is that changing or what is your opinion if A is it changing? B, are you looking for that change as an investor?

SPEAKER_02 24:47

Yeah. So interesting time kind of moat and how do you create like durable competitive advantage and then also how does that imply you build your team which I think they are definitely related to your point but they're also somewhat there there's also some separate considerations. So you know we have this uh AI conference in the fall and the founder from a company called Neon that was bought by Databricks for a lot of money um this question came about moats and his point which I think is interesting and largely true is in this world of AI the only mode is speed. The only the only mode is execution and how you are constantly making whatever's the latest innovations in AI work for you. And and without chasing shiny objects, right? That's the challenge. It's like if you just sort of jump on whatever the new thing is this week, you could chase your tail but if you ignore you know the new things this month, then you're gonna fall behind. And so I think that's what the best founders need to do. And so I do think fast execution is paramount and that comes to what's the team you build around you to to accomplish that fast execution. I I would also say I'll and I'll come back to the team on Moat, you know, you can still create data flywheels in your business that create a moat that um either you take advantage of a data set that your customer has to then create more data that makes your service better, et cetera, et cetera. So I I do think that that's a a real thing. There's the there are classic advantages around you know building brands and building community network effect kind of moats. And occasionally, you know, there are technical motes. I think there's always been this like there's no real technical moat because Google or Microsoft can build anything you know if they decided that they wanted to do that. I do think that notion is probably even more so that way that anyone can build anything. But the but we also are still seeing founders who are doing things we think in in novel ways or in some of the businesses that are more deep tech you know type things. On the makeup of the team I think it's true. Like it's like the sheer number of engineered bodies you need to do X is probably less. Or it might the end might be similar but what they're doing is different. You know, this idea of you know more architect thinking you know more versus sort of just like go write the code I think there is a little bit more of a shift you know to that side of things people who are smart about how you review the code not just write the code but on the other hand you know depending on your category still getting some critical mass of people that are just really deep in that area of technology whether it's search or whether it's you know healthcare or whether you know whatever your domain is I think still matters a ton. And so you know I'd still hiring engineers is probably the you know the hard one one of the hardest and most competitive things that founders have to do and it still you know it still matters a ton. You know, and getting that right mix of you know when you hire the right on go to market side without hiring too many and right ways to compliment it's it's just as just as tricky as it was when you were when you were building uh your first company Gary.

SPEAKER_08 27:42

Yeah the hiring engineers is tougher I think because the you know they're employed at you know say the Mag 7 or even the Mag 20 I mean the next 20 of them the value of their of their options or their overall value of those companies is so big at this point you got to really think and and now I feel like these companies are hiring like like NBA athletes or NFL athletes. I mean you hear numbers I mean Sam Darnold is getting the same deal as AI engineer like that's that's just uh incredible and I mean as an investor you got to sit back and say wow this is a whole different ballgame isn't it? For sure.

SPEAKER_02 28:26

And again it's like um it's a it's a real power law like some of these top AI researchers like yes the numbers are just absolutely staggering. You know they're what would have been like a you know career making acquisition you know number you know IO number for an entire company could be for you know one top AI engineer. But then you know there's other parts of the market where there where there where there's a lot more folks available and then you have things like you know Amazon and Microsoft keep shedding you know in in meta they keep shedding engineers and so it's weird because sometimes you talk to folks who are like I'm having a hard time and other times a hard time like finding the thing. It depends on your field and and your expertise but certainly if you think you're going to go pull people out of OpenAI or anthropic or in one like good good luck with that. You got to find some more creative way to do it. Outside of the people who you know are mission driven and you know getting in early it's more risk but you can also make an amount an amazing life changing amount of money if as you believe in the mission and are willing to dive in.

SPEAKER_08 29:23

Great. So now we are on to the all-important prediction the prediction for 2026 Tim uh you can make any number you want but we get we need a lead one from you first one the first prediction that you will make for 2026.

SPEAKER_02 29:36

You know this I think that Apple's gonna have to make a big AI acquisition and I think SpaceX will be the first of those you know big five to go public. Those would be my two capital markets predictions. Those are always the ones that are a little easier to measure like it either happened or it didn't happen. So I'll I'll say those and then I will say that the adoption of agentic AI in the enterprise will be meaningfully measurably higher across the course of the year um across all these use cases we've mentioned in more with that Tim thank you very much again for coming on board and we'll have you on next year I'm but I'm sure that we will run into each other at many of the events uh during the year.

SPEAKER_08 30:18

Thank you very much for your time.

SPEAKER_02 30:19

Thanks Kari really enjoyed it a lot of fun one second Hi there.

SPEAKER_08 30:29

Thanks for the support make sure to subscribe on your favorite app. Just search from startup to exit to stay updated. Now back to the show. Well we have uh Kellen Carter for our uh annual investment outlook podcast episode Kellen thank you for doing this this is third year in a row our audience is always excited to listen to your predictions and then see how much of them came true the next year. So with that this is the hottest year of AI that you've been predicting this for two straight years. Let's start with uh looking back first right what was 2025 like from an uh investment perspective compared to the year before that you know 2024 versus 2025.

SPEAKER_06 31:15

Yeah so first of all thanks for having me on again I always always love doing this this podcast with you an honor that you continue to invite me on. You know I start to call it internally the annual put my foot in my mouth podcast because you know if I had a crystal ball maybe I would start a company instead of being an investor. But if I I look back and reflect on 2025, the thing that is hard to imagine every single year is that the pace of innovation continues to accelerate. Well you had the first wave of ChatGPT and then the next generation of AI research labs and it was always hard to fathom, okay, things could change even that much faster. And the pace of innovation and the pace of change is only accelerating. And you know I I look back during the SaaS era and Uber's a great example where they wanted to start building self-driving cars because they viewed that as an existential threat to their ride sharing business. And that timeframe was really 10 to 15 year timeframe of of when they had to think about the the the next act that would be disruptive to their business. Now this is happening in years and even months sometimes and so the speed of how companies need to evolve is only accelerating and it's hard to keep up the thesis was AI the primary focus of your investment thesis in 2025 or did you have other thesis in addition to AI? Yes primarily AI solutions mainly vertical AI solutions and what I mean by that is is things not in the direct roadmap of OpenAI, Anthropic, Gemini, et cetera and so we like verticals that are completely getting reinvented with with AI at its core because new business value can be delivered things in insurance things in freight and logistics even healthcare and delivery where there's just a lot of workflow and FUD and process and documents that AI could help clean up a little bit and make the delivery of value that much better. Interestingly enough we've we've taken an interest in space over the last couple of years and now have a couple companies in space one that helps manage satellites in space one that's putting data centers in space and we made this investment before Elon started talking about it. And so we're we're proud of that and really excited about the StarCloud company. And we also have a defense company in space called Portal Systems which helps satellites maneuver versus being static on their orbit. And so we've taken an interest in space and I think Seattle is a really interesting hub for space innovation because Boeing was an original anchor tenant of of major companies here.

SPEAKER_08 33:49

Overall how do you see valuations compared to 2024 and 2025 were they impacted is capital plenty therefore the valuations were high, low, same?

SPEAKER_06 34:01

The valuation market has been probably one of the most unpredictable markets in my 13 years of doing venture honestly if I look back into the era of SaaS if you you know hit a number you could kind of plus or minus 10% of what the likely applied valuation would be. Now in this world of AI, you see companies you know getting priced in billions with no revenue you have other companies growing from one to five million at ARR and struggle to get a term sheet. And so there's really no formula for how valuations are ascribed to companies. The tale of the two cities that we are seeing is a massive disconnect between experienced founders that have made VC's money and getting these massive premium valuations and companies and founders that have not yet. And you could still you know really play an important role here if you haven't been a return founder, but you're just seeing a huge disconnect in terms of the valuation described and and how I think about that is the ground underneath our feet is shifting so fast that venture investors are therefore applying a premium on founders that have been there, done that before, have talent coattails that they can bring in faster, have an existing customer network and can move a little bit quicker as a result, thereby taking the lead in a category that emerges.

SPEAKER_08 35:22

And so that's just the major uh disconnect that we're seeing there's a lot happening or has happened with the macroeconomic uh you know situation has that affected either the investment or the valuation what's uh your take on everything that's happening in the economy because it seems like if there is an impact of how startups are getting funded.

SPEAKER_06 35:45

Yeah I the U.S. economy has probably never been more dynamic than it is right now. And there's your running for office word right there, I guess, right? Dynamic. It's such an ambiguous word. But I I'd argue it's much healthier than most people think the layoffs have been lower the inflation's below 3% GDP prints are north of 4.5%. The impact tariffs have actually been way more muted than I think most people predicted especially back in March. And so I think that the U.S. economy is probably the most attractive place to have not only domestic but also international investment in the world right now. And I think with all the AI build out that's happening, you know, with data centers, with chips, with the infrastructure that will need to exist to unlock the new set of applications that's all getting done and driving tons of construction jobs, lots of of investment and lots of innovation.

SPEAKER_08 36:35

Right.

SPEAKER_06 36:36

You talked about vertical applications that you're focused on are there specific verticals or is it that somebody comes with a vertical solution and qualifies with all these return founder talent pool aggregated how are you formulating it taking all this into consideration your economy vertical outlook vertical application and the founder return founders versus new founders yeah there's uh a a couple ways that we're thinking about this so if you take a step back and see where AI is making a profound impact it's software development right it's putting software developers and turning them into 10x producers content development whether it be text to speech video PowerPoint etc and then the third where we really like to play is in the workflow game where there's just a lot of documents and a lot of text. And so if you look at you know in our funds we have a company in insurance automation that helps process claims for carriers well what do you do when a claim comes in you have to detect whether or not it's fraudulent or if it's legitimate and if it's fraudulent you put it into a different workflow where you go prove out that it's fraudulent and go recover the capital. And it's it's really easy to commit insurance fraud. But on the flip side if it's legitimate there's lots of health records, lots of data that you need to aggregate and then adjudicate how much do you pay and when do you pay out that claim. And it's a job that is very repetitive for a claims agent in an insurance company and where there's just lots and lots of bodies well with software in this company called OWL that we're involved in, the AI can do much of that data aggregation, document annotation, and then help a claims agent decide exactly how much should be paid out and when. And so it just puts these business processes and brings them to be way more efficient and even way more accurate. And so you're just starting to see the tip of the iceberg of enterprise applications get adopted twofold is one, the security and compliance is becoming much more clear from procurement, et cetera, how you treat the data. Two, the LLMs are much more accurate now where the accuracy actually usually exceeds a human, but the human is still required to make sure that these things are producing the right way. And then three, the trust element people are becoming way more comfortable adopting AI solutions as part of their everyday consumer life, which brings them into the comfort level of their work life as well. And so I think if we're looking out to 2026, you know we're starting to see the rise of enterprise applications get built.

SPEAKER_08 39:20

Does that extend to the agentic applications part or agentic being the core way of delivering these solutions businesses buy value.

SPEAKER_06 39:34

They don't necessarily care if it's SaaS or if it's an agentic outcome the way a customer thinks is I need to buy value to a problem that I have to a business process that I have. And that solution is always going to consist of some parts human, some parts agentic solutions. But the core root of it is what is the value that I'm building and over time these AI solutions whether it be agentic or agentic plus human will evolve to arrive at the best method of delivering the business value.

SPEAKER_08 40:05

Right, right. So that sort of opens up this question right so you you talked a lot about application layer but on the other hand you guys are also going into space that looks like it's from the outside infrastructure are there other infrastructures in the AI stack that you're looking at leaving out the LLM that being cornered by a few is there other parts of the AI stack that are just core but just may not be immediate applications are you guys also looking at that as an investment possibility or is that an investment thesis at all?

SPEAKER_06 40:39

Yes so majority of what we've done has been in the applications area and even primarily in vertical at least most recently but there's a whole suite of enabling technologies that need to exist for the AI economy to thrive. And so we've we're we're in a company that helps with monetization agents essentially building the plumbing for how an AI agent company will price to the business value that it delivers, demonstrate the attribution, bill and collect payments, all while doing this with a clear understanding of the gross margin, which are highly variable in the AI economy as we all see but it's essentially building the stripe or the visa of the AI plumbing for monetization. And this company was founded by Manny Medina who built outreach in Seattle a company that we're really excited about, but it's a layer that needs to exist. And so we're looking at at the preconditions that would would be required for the AI apps to actually work. We are not doing the AI research labs the the highest most sophisticated AI researchers their first round of funding is sometimes bigger than our fund size and so that's not the game that we're playing we we've done some interesting things and inference optimization funded by some brilliant technical folks where we see them going after you know enterprise scenarios where you want to lower your cost of compute compute and delivering value with AI without having to buy a whole army of you know Nvidia chips. And so you'll see more interesting innovation happening there because you know Nvidia is clearly a powerhouse but you know customers can only bear so much brunt with how how how expensive it is.

SPEAKER_08 42:24

Right. So that leads to the next obvious question which is these things are building but there's no good talk about IPO in the AI market anthropic that's been well documented that they could go IPO and they seem to be making moves around it. Do you see the IPO market in itself opening up what's your prediction and take on the IPO market because that's a path to exit which is at the moment seems like either get funded or get acquired. Those are the only paths that are available.

SPEAKER_06 43:02

Yes I think this year will be the year of the IPOs especially back half you know interest rates are now at a moment where equities are more attractive um you know I it seems like the current administration is is more IPO friendly and forward um and also MA forward. But there's just a you know the reality is is venture firms are on a clock and by clock I mean 10, 10 year funds plus two year extensions where you got to start to get liquidity in your underlying companies and you know we're at a tipping point for many of the 20 early 2010 funds where you got to essentially find liquidity for the companies and that means you know do you sell it or do you sell in the second do you sell your shares in the secondary or do you start to finally push the companies to get public and and really it's you know the the the the companies they got high watermarked in the 2021 that are now finally growing into those valuations that that um you know are important Important for a founder psyche to go public. And so I think the macroeconomic environment will be helpful. The timelines that companies and funds are on is a little bit of a forcing function, and that companies have matured beyond the 2021 high watermark where they can get out at the last price or close to it.

SPEAKER_08 44:20

Got it. So what uh what's what are companies that you are watching that might go IPO? It may not be your portfolio, but it can be anything that could go IPO that have postponed it in that definition of from 2021. There's been some movement to get there, but something or the other hasn't worked out.

SPEAKER_06 44:42

Well, I can't comment specifically on a company that's near and dear to me in Seattle from my uh ignition days, but that's a company that you know think super, super highly of the iService folks. And, you know, then they've executed phenomenally well, and we'll see what their path is over the next kind of 24 months. You know, I think the company that everyone wants to benchmark as the AI comp is anthropic right now. They seem to have won the B2B side of things, plus the software development side, whereas Gemini, Grok, and OpenAI are duking it out for consumers. But everyone wants the comp of what is really under the hood of these companies as as how I should think about the other private investments. Because right now, you know, you get the gross margin ambiguity, you get all the capex ambiguity, you get the state private ambiguity, and everyone wants a little bit of certainty of what what how do I make sense of this new market, given there's so many variables at play. And so I think everyone's all eyes on anthropic by the end of this year. Got it.

SPEAKER_08 45:45

Um so this sort of goes back to this other question, right? Which is you brought up this, they have clearly got productivity under their sites, anthropic, I mean, right? You you just mentioned they they seem to know they seem to do extremely well with developers, enterprises, etc. That's a shift in your mind when founders come and talk to you saying, you know, they want to raise X let's for the sake of they want to raise some money. And then when you look at use of funds, seems like now the use of funds is how you're going to distribute rather than how you're going to build, right? Because it used to be 85% went into engineering efforts. Now theoretically cloud could do it, I don't know, fast, at least definitely faster, maybe less less expensive compared to that. Does that change how how a founder listening to you would come and say, hey, this is my use of funds. What's my what's the way I will gain traction?

SPEAKER_06 46:47

Yes. A simple framework that that worth thinking about, or at least I'm thinking about it, is IP can now be in distribution, not necessarily in software development. So what is your IP that is in distribution if you're a founder? Because to your point, if anthropic and and these other software generation tools exist, that means the barriers to entry have just calmed down. You know, it's more inexpensive to build a V1 product. You know, you don't have to be as technical to get you know a V1 product. So it happens faster and it invites more competition. So what is your IP that's in distribution? And that's what needs to exist to actually win a category today.

SPEAKER_08 47:29

Right, right. It's a very interesting approach, right? Because then founding teams need that as a core talent within their within their initial outlook. It used to be you could get together a couple of great engineers and build something and then add the sales talent, et cetera, later. But this like this is almost the reverse now what's happening. You've got to get the sales talent in first, or go to market talent. I don't mean sales in general. Go to market talent in first. Yeah.

SPEAKER_06 48:01

Yeah, yeah. And I, you know, I think there's just a lot of co-marketing, product-led growth. You know, we're seeing a lot of designers, you know, founding designers hired earlier on to deliver, you know, just really a best in class first touch experience with AI because the the switching costs for a lot of these apps are net next to nothing, which is always concerning. And so you see founding designers to make sure that the product experience uh and usability is world, world class day one. That is a new shift versus the SaaS era.

SPEAKER_08 48:33

So the moment of truth now, Kellen Carter's prediction for 2026. First, why don't you look back at your 2025? You had predicted that the open AI Microsoft relationship will frail. What do you think has happened in reality?

SPEAKER_06 48:49

I think in reality, the the relationship is clearly important, but did fray, but they're a little bit dependent on each other. I think Microsoft was a little bit behind on much of their AI solutioning and their copilot, and they need OpenAI to keep them relevant on that side of things. But I also think that they see such a big prize that they're so committed to figuring it out and working with other vendors to make sure they don't miss out on that prize. Meanwhile, OpenAI has developed partnerships and relationships with essentially every other cloud vendor out there. And so they've had to diversify away from Microsoft, probably to make sure, one, they have the compute capacity, but two, that they're they're not solely dependent on Microsoft's distribution uh and and and that Microsoft might emerge as a realistic competitive threat from an AI standpoint. So both of them are playing like, you know, my the what is it, the the enemy of my enemy is my friend. That's what it sort of feels like right now.

SPEAKER_08 49:45

So it's taking longer for them to separate. It's easier for them to be together. That's your that's your take.

SPEAKER_06 49:51

Yes, yes, exactly. We have to coexist, but we're gonna compete. Yeah. So with that said, what's your 2026 prediction? Back half of 2026 will be the best year for IPOs in the last decade. Maybe except for 2021. But that's when I think that um LPs, founders, VCs, it will be one of the best years for exits in the last decade.

SPEAKER_08 50:17

Great, Callan. Thanks a lot for uh your time. And as always, we always look forward to recording with you beginning of the year so that our audience can enjoy your predictions. Thank you very much.

SPEAKER_04 50:30

Thank you.

SPEAKER_08 50:31

Always so fun. Thanks, Karen. Hi there. Thanks for the support. Make sure to subscribe on your favorite app. Just search from Startup to Exit to stay updated. Now back to the show. Hello, everybody. Uh, we have Shudeep uh joining us for our annual investment outlook episode. This is the third in annual series that we are doing. Shudeep, thank you very much for coming back on the podcast and doing this every year for us.

SPEAKER_04 51:05

Yeah, it's always a pleasure. Thank you so much for having me.

SPEAKER_08 51:10

So let's kind of uh start with uh the uh 2025 year in review. What was 2025 like from an investment perspective compared to the say the previous year? What was your focus of uh 2025?

SPEAKER_09 51:27

Yeah, I mean it it definitely was busy, but I would say that probably it was less frothy than 23 and 24 in particular for a couple of reasons. So one was that I think we are entering that phase of the whole uh AI space where people are actually getting to a point where they are uh asking uh to show the money um to the companies that are selling to them. So what I mean by that is uh, for example, we work with uh many, many large enterprises. And I think in 25 in particular, particularly in the second half of 25, they started really asking the hard question of uh ROI of all the you know 50 or 100 you know POCs they were running with AI companies. So they really started asking the money question, the ROI question. That in turn has started separating the wheat from the chaff, so to speak, meaning if you are just selling a story uh but don't really not really delivering value of the ROI to the um to your customers, think you are uh you are basically uh like it there was less space to hide in AI. So investors naturally started gravitating towards companies that were bringing that ROI, bringing that real value to the table, uh, as far as their customers were concerned. So in 2025, you saw, you probably saw this data already. The deals actually started getting concentrated. So, what I mean by that it was uh like bigger checks in a smaller number of companies. And um, I think you will probably continue to see the pattern because you you're seeing some of the winners pull away from the rest of the space because they are able to deliver the real benefit, real ROI to their customers. So that was 2025 uh for sure from a deal activity standpoint. From a focus standpoint, you know, for us at Proven Capital, we invest in two areas. One is enterprise IT. So anything in the infrastructure, cybersecurity, data, developer tools that kind of falls in that bucket. The second one is uh applications. So essentially we invest in two buckets that uh large enterprises buy. I think um in 25 in particular, we actually started um um seeing some of these companies grow up in both of those buckets. Our focus really hasn't changed much in 25. We continue to focus on companies that are delivering real value. I think whether they are real AI companies or driven by AI is kind of a secondary thing for us. It's more like they're actually providing some real value to our enterprise customers. That's really that has been our lens. So our investment focus wasn't all the different from 2025.

SPEAKER_08 54:20

But was it uh extremely focused uh in terms of AI? Without AI, there was no consideration, or did you have other considerations?

SPEAKER_09 54:31

So we have a slightly different lens. Our lens is more like problem-oriented, meaning like, are you really solving a meaningful problem? Are you really automating a workflow that actually delivers real value to your enterprise? I think naturally the companies that we ended up investing, uh, we ended up uh engaging, they are more or less all driven by AI in some respect. Yes, they all were more or less AI-driven companies, but we stay away from investing in areas like we don't invest in companies that are building foundation models, for example. You still see those. Yes, I mean, obviously there are big um 800-pound gorillas in the space, but we saw a number of companies that are trying to build foundation models for specific verticals like healthcare and you know, radiologic nouses and things like that. We stay away from those because at the end of the day, we are very much focused on are you the are you solving a real problem? Are you delivering a real solution for a use case that an enterprise will pay for? So, yes, I mean all of our investments were AI driven in some ways, but they were not quote-unquote AI companies, as in building foundation models or frontier labs.

SPEAKER_08 55:41

So building on um that that what you just said, which is you saw separation between companies, ones with real and ones that were not quite there yet, did it have impact on valuations compared to the previous years? Go up, go down, especially you mentioned concentration. A lot of money chasing few too few deals. How did it affect valuations?

SPEAKER_09 56:09

Yeah, uh definitely the valuations were at premium at a premium for companies that have started showing real momentum, real ROI, uh to your point. Uh valuations for companies that were in the previous B, C, uh, D stages where they had real momentum, real ERR growth. And frankly, you know, some of this, you know, some of the old playbooks of ERR growth have gone out of the window for some of these next new generation companies. What used to be like, okay, you grow 3x, 3x, and then 2x, 2x, which was very uh, I would say top decile, very good for SaaS companies, have gone out of the window because some of these companies are growing like 1 to 10, 10 to you know, I don't know, 70 or 100 in some cases, right? So for those companies, evaluations have definitely uh like gone through the roof. I think on the seed, uh at the seed stage, um, I would say yes, you always you know read about some headline deal where, you know, oh raising you know X hundred million dollars at you know X billion dollars. But those are like very few and far between far in between, particularly in 2025. I think I would say on the seed side, things were a little more rational uh than 23-24. People were not just jacking up valuations just because it was in a great team, but only had a PowerPoint deck. So the market was a little more rational on the seed, even in CDs A at CDSA stage. But like I said, for more like the growth stage companies, particularly if you are the winner in that space, you could command virtually any valuation that you want.

SPEAKER_08 57:54

I see. So that leads to the question of uh overall economy and the health of it, or your opinions on the economy looking forward compared to what the years that that just went past, because there was a lot of impact on macro factors on everything that we did in our lives.

SPEAKER_09 58:15

So I'm actually, I would say, cautiously optimistic about the economy in 2026. I think uh you read the market data, you see the market data, you see, I mean you track the interest rate, you track inflation. I think you know, I'm cautiously optimistic. I think probably at this time last year, I think there was uh probably, in my mind, at least a bigger uh fear of uh some form of recession, less in that camp right now, 2026. I think the one question that I think everybody is pondering, not just me, is the sustainability of this whole AI space, right? Meaning, like if you really look at it, a lot of the activity is driven by big, big investments in the AI space. Large data centers getting built, which is fuelling demand for you know chips, which is fuelling obviously in a lot of the stock prices we are seeing. And we have all seen this. I mean, there's a little bit of like um that's a circular economy among some of the large AI companies. So I think how I mean that sustainability of that you know through 26, 27, I think is a question because I think if if there's any hiccup in that, that might have a certain impact to the tech side of the economy for sure. So that's one thing I think we all kind of worry about. But when it comes to like an early stage investor such as us, our time horizon is much longer, right? It's like five to ten years probably for any investment we are making those companies to really grow up and have a you know meaningful business that gets impacted by economy, it's probably too far off. So we do not, for our own investments, we we we are not making decisions thinking there would be some kind of hiccup in the economy in 2026. But of course, we are watching because we are part of the overall venture market. I think the bigger question is the IPO market open up this year even more meaningfully. Um I think that a good IPO market could dramatically obviously help um the economic outlook.

SPEAKER_08 1:00:30

So expand on that, right? Do you expect the IPO market to open up in 2026 uh more than the last two, three years?

SPEAKER_09 1:00:40

I actually do. I think the IPO market is probably already more open than it was during 22, 23 uh drought at the time. You could hard you hardly saw any company go out. Frankly, a number of companies pulled their uh S1s in the 21-22 timeframe. I think you know there is there are some really good companies in the IPO pipeline. You take companies like Databricks and uh Evaluate and Cohes D and you know, like so and a bunch of these companies that uh I think you know in previous IPO cycles probably would have gone out already and are remaining private only by choice right now. So I do expect um, again, I'm a huge fan of a company like Databricks. I hope, and I do expect they go out sometime this year, right? I think once you have one of those marquee companies go out, I think you'll see a string of companies follow because the markets um obviously sentiment, you know, a lot more positive, the reception is a lot more positive. So I think you need one or two of those um marquee iconic companies to get out. And hope this is the year that Databricks decides, because that will help uh for other companies.

SPEAKER_08 1:01:57

But there's a lot of um chatter around anthropic might go on in 2026. So would that set a bar or a comp for others? Because this would be no real numbers, right, when they do go public.

SPEAKER_09 1:02:14

Yeah, so anthropic, I'm glad you brought it up. Yes, I think you know we all are reading the rumors of them, you know, going out from H1 and could be giants, you know, IPO, right? You know, a trillion dollar IPO or something. We have never seen. Yes, it does up the bar, but I would say in general, even in the IPO market, I think the bar is already moving up. So what I mean by that is I think you're seeing the charts and the chatter about the multiples for pure SaaS companies getting compressed already. And and I think that's the direction the market is going to move, which is if you are if you're just um let's call it a database with some heuristics, with an you know, kind of an UI built on top, which is most SaaS companies, and solving a vertical problem, I think your long-term moat is at risk, and the market is already accounting for that. And so my point is even if like without with or without anthropic, you'll probably see the bar moving up for sure. I think one question there, and this is not specifically about anthropic, there's more like the pure AI application company. I think I think one vector is growth, the other vector is margin. So gross margin. So I think that's gross margin story, is a little bit of a TBD. Like we don't really have enough data to know if you're growing from one to ten to 100 million in ERR, what's happening on the gross margin side? Are you mostly like passing that on to one of the foundation models? Or are you capturing a meaningful part of that? I think we will see that as some of these companies go out, you know, we'll have a better sense. But I think you also need to have a good, strong story around your gross margin. So that's another vector I think people will have to factor in as they evaluate some of this, you know, uh newly public companies.

SPEAKER_08 1:04:15

So with that said, with application companies gaining momentum, is this truly 2026 the truly the year of Agentec then? Because we talked a lot about it. There's not much to show for in terms of you know, but is this the year do you see that shifting or is it still in a you know?

SPEAKER_09 1:04:37

So it is still in a curve. I mean, I I would say one thing though, this we are actually hearing this quite a bit from the corporates we work with. Multiple of them have told us, and this coming from the CTO chief architects who are responsible for putting these agent thick applications in production. I think the code is more like 2026 is going to be the year of agents for. The focus will not be okay, the agents will come back in and replace whole departments of employees overnight. I think that's a very far-fetched dream at this point. Still, I think what you will see is very focused workflows and use cases getting automated by agents with the humans in the loop. So that's sort of like if 2025 was a bit of a oh, my entire team doing X could be replaced by a bunch of AI agents which work 24-7 and you know never complain about their comp they were their comp. Uh, I think that is probably uh still we are very far away if uh if we ever get there at all. But enterprises are looking at more narrowly scoped workflows and use cases, and definitely uh they are putting in agent take automations there with human in the loop. The other area where we are Seeing um, I would say agents taking or gaining more traction is what I would call um service use cases. So if you talk to any Fortune thousand, Fortune 2000 enterprise, normally they spend in any given year, they spend somewhere between 500 million to 1.5 billion on all of these service providers. Definitely are seeing a lot more receptivity from them in terms of, okay, if I'm sending $50 million to a service provider who have offshore human talent to do my X, whatever that might be, some kind of business process. I think the enterprises are definitely a lot more open to a new generation company coming in and saying, hey, we are still your service provider. We still, our interface is still humans, but under the hood, instead of having 100 humans doing your business process X, we probably have 10 humans, and then the remaining 90% is some kind of agent tech automation helping those humans. And as a result, we can offer you much better quality, price. I think in those kind of scenarios, we are taking, we are seeing agent tech automations getting faster fraction for the simple reason that for enterprises who are consumers of those services, it is actually much easier to point their business process from service provider X to a new generation agent tech service provider. It is much harder for them to really adopt a tool because they need to set up a team, train them on that new tool, and so on. So that's why they are much more open to replacing their service provider with some kind of whatever would not call agent tick service provider. Somebody m said this to me, I'm still like, it's a little corny, but somebody said agent share is the new accenture. Um I mean it's a corny code, but uh I think there is definitely a lot of truth in there.

SPEAKER_08 1:08:05

So this leads to the other question, right? There's been a lot of, at least a lot of success reported in uh knowledge workers being replaced, like coding, for example, right? Vibe coding, the whole clot really moving into the enterprise has been well documented, right? Now you talked about massive shifts in terms of productivity as agents move in, whether it's replacement or increase in volume or things like that. But look looking at it from an entrepreneur perspective, right? When they come to you for early stage funding, you have a set of things you evaluate on the problem they're solving, is it real, is it repeatable, all that said. But it seems to me that that one of the things that looks like you may be evaluating is how do they reach the customer, right? The go-to-market seems to have, based on what you're saying, seems to have moved even into seed stage of as a very, you know, early. You almost need a go-to-market plan before you even write a line of code, yeah, kind of a thing. Because the code can be written by Clark. I'm being physician, you know what I mean, right? Right. Is that something as a trend you are seeing? And are you guys evaluating the ability to execute a go-to-market?

SPEAKER_09 1:09:25

I would say is like um uh it's almost like it has always been the, I mean, that it's not as different from the past cycles. Meaning it's almost like the old is always the new kind of thing, and there's something in some kind of quote like that. My point is I think gone are the days when you'd invest in a company and expect that team to take two to three years to build their you know, MVP of their product, right? I think, and then think about go to market. I think uh those days are gone for multiple reasons. One is just like you said, you can get so much more done with um so little this days. Like I was actually talking to a founder recently, he had a pretty successful exit selling his previous company to uh Fortune 50 and did very well. And he had built a company over four or five years. And first two, three years of that was building the product, and then the remaining two, three years was obviously figuring out go-to market, tweaking the product based on what he was saying in the market. He was telling me in like a in a five, six weeks time frame, because he is still thinking in that same space, and he was saying, like, you know, in a matter of weeks, he alone was able to replicate virtually the product that he had built in his previous company over like a period of you know several years. And that is mind-boggling, right? Um and I think you'll see that, I mean you're already seeing that, you know, in every um uh aspect of uh in uh startup, right? So I think that is uh that mindset. If the founder already does not have that mindset, I think it is going to be very hard for that founder to succeed. Forget about even raising money. I would say the reason go to market is so important, by the way. I mean, I I I would always think like even in uh five years ago, go to market was still as important to think about when you were building the product. But it is more important now because a lot of the success of your product depends on it getting better based on the data you're collecting from your users. So if you don't have a flywheel of users using your product, sending you first party data that you can use to fine-tune, retrain whatever, you know, your core AI, then your product is not going to get better over time, right? And then you run the risk of some other platform company coming and completely wiping you out in a couple of years. So I think that's why go to market is so much more important. It's not just to you know show dollars, but also to really enhance and improve your product continuously. Because that is the mode that you are building at the end of the day. So that's why I think go to market, like thinking about it or actually acting on it from day one is so important or more important. Because always important, by the way. I mean, don't get me wrong, but I think it's even more important because now your product success, your moat critically depends on you getting in front of your users.

SPEAKER_08 1:12:42

Yeah, understood. So it's almost like you need uh you need the distribution to be built in even into your first business plan that you're thinking about. Seems like that. Without that, there's no no chance of you getting there.

SPEAKER_09 1:12:59

Yes, 100%. And that's your moat. Um, and I think you know, in this world, probably the single biggest concern is the moat. Like, what do you have today that cannot be wiped out by just you know the models getting better? Like we all are, you know, kind of uh thinking about this long context windows, right? So for example, let's say today you are a completely like an AI-driven solution. Let's say you are taking on marketing, right? You're automating some of the workflows in a marketing team, right? So you have built almost like a middle layer on top of whatever foundation model you're using that is very marketing specific. You are collecting your data as people are using and so on. I think the question, real question is in five years' time, will the underlying foundation model be able to do all of that without your middle layer?

SPEAKER_04 1:14:03

Very, very good question.

SPEAKER_09 1:14:04

So you completely putting your company at risk.

SPEAKER_04 1:14:07

Yes.

SPEAKER_09 1:14:08

And I think that's a real question you have to ask because this space is moving so fast that you have to think about okay, in five years, how do I compete against the foundation model being so much better than what they are now? I don't know the answer to that. I think in the SaaS cycle previous in uh decades, I think this was not a question people really thought about because at the end of the day, it was all of uh, okay, if I have more users, if I, you know, get them, uh get their workflows in my SaaS tool, I have created my mode because I'm I have their data. I mean, think about you know Salesforce, right? I mean it's like David is one thing that prevents people from moving away from Salesforce, no matter how much you like their UI and UX and so on. But I think in the new generation, in the coming days, I think a lot of like you'll have to think about the threat from the foundation model. Also, you cannot rely on being a system of record. Because I think that mode is disappearing or at least getting very blurry. Um earlier it used to be like you had a system of record system of record and that's your moat. I don't think you can rely on that anymore.

SPEAKER_08 1:15:26

Because the interactions with whatever systems is also changing. They're they're coming at from humans and agents maybe in the future. You're right. And multiple systems.

SPEAKER_09 1:15:36

Multiple systems.

SPEAKER_08 1:15:37

That's right. That's right. That's right.

SPEAKER_09 1:15:39

Um because it is like I think we built SaaS tools almost like in silos, so humans could use them. I think we are getting into a world where we are going to be workflow-focused, and hence the power of the underlying system of record is going to be greatly diminished.

SPEAKER_08 1:15:59

So now the uh the one thing that we've been waiting for for the whole interview, your predictions for 2026.

SPEAKER_09 1:16:08

Yeah, uh, I'll probably say a couple of things, not just one. I I would say you asked me a little bit about you know kind of the broader market IPOs. So let me uh share one thought there. I think uh, and there's a prediction, I think uh at the end of 2026, if you really look at the IPO market, probably the best performing tech IPO will be c will be a company that is that uses AI deeply, but is not perceived as a pure AI company. And my thought behind that is I think 2026 will be that inflection year where AI as a category will start to almost like disappear and in favor of almost like AI as a baseline capability. So think back 20 years, right? Pure internet companies, you know, kind of disappeared as a category and internet just becomes the underlying engine, right? So I think you'll start seeing in 2026 um that being reflected in the tech IPO market. Like one prediction I definitely have. The second one, I think um I'm still um hopeful, but I think you will um I I'm I don't have a firm timeline whether it will be definitely by the end of 2026 or not, but I think you will see AI coming to the edge or getting to the edge a lot more. And um again, internally, somebody said to me the other day, which was in 2026, gets edgy. That was kind of the cut. Um, and I think I think there's a lot of truth behind that because I think the use cases are getting there where there's a lot of market pull because of you know, user latency, user experience, data privacy, all of that reason. And frankly, even the infrastructure, underlying infrastructure actually getting there where you can run pretty high capability, you know, much, much, much smaller models on the edge. And edge doesn't only mean phones and stuff like that. It could be in a lot of other things. It could be your cars, it could be in a like edge data centers, you know, whatever, like your parking meters and whatnot. But I think you'll see in a fair number of edge use cases, you know, uh coming up. So we are seeing that on the infrastructure side where you know people are actually working on you know, kind of pushing AI to the edge from an infrastructure layer standpoint. And I think you will see some of the applications evolving or um emerging in 2026, at least 2026. So I'm hopeful of that. And we are obviously very much focused on those some of those use cases because I think that's where a lot of the growth could come uh in 27, 28 when AI gets to the edge.

SPEAKER_08 1:19:00

Well, Shadeep, awesome, as always. So we will track those predictions through the year, and when we come back, we will discuss more about that, see how it all worked out. So thank you for taking the time to be on it and uh spending uh your morning with us uh to uh be on this annual episode of uh Investment Outlook. Appreciate it.

SPEAKER_09 1:19:22

It's always a pleasure, Gori. Thank you so much. It was fun. Have a great day. Bye-bye.

SPEAKER_08 1:19:32

I hope you're enjoying our investment outlook episode. This year, we invited a new guest, Joaquim, from Silicon Valley Bank. We really enjoyed his insights when we met with him, and we wanted him to share the data that he has about the economy and about startups with you. Thank you, Joaquim, and thank you, Silicon Valley Bank. Hello, everybody. We have Joaquin Gallard from SVB for our annual investment outlook episode. This is uh both uh Joaquin's first and SVB's first participation in our podcast. Thank you, Joaquin, for being part of this episode. And uh also thank you for uh bringing some unique points of view to our audience. Why don't you introduce yourself and uh SVB to our audience?

SPEAKER_05 1:20:27

Yeah, well, I should clarify it's Galardo. Typo this is uh this is my typo here. But yeah, it's great to be here. Thank you for having me, Gauri. Again, my name is Joaquin Gayardo. I'm with Silicon Valley Bank, our division of First Citizens Bank. We've been around, just a quick introduction to who I am and what we do. Silicon Valley Bank has been around for 40 years. We invented the category of tech banking, and we've been banking with the best tech companies ever since, all the way from just an idea and just incorporated, all the way through post-IPM. So that's the niche that that we service, which is very unique, especially when it comes to the world out there, uh, venture-backed technology companies in the innovation economy. It's a very small sliver of the big economic pie. So from there we have very unique services, lots of white glove. And on top of that, just it comes with a lot of you know expertise that comes along with it, with experience and having been in it. I've been through um started my career in Washington, DC, worked my way through uh San Francisco, had a failed startup, taught myself to code, became a full stack developer, have a code sense, which is fine. Now I have tools that do that for me. So it's been a fun awesome.

SPEAKER_04 1:21:50

Thanks for that intro.

SPEAKER_08 1:21:52

So uh let me start with this, right? Most entrepreneurs, most founders don't wake up thinking about their banking relationship. They they have some personally, or they may have some, they may have had some at their employer, and then just say, Oh, yeah, yeah, we just start with that. But you guys uniquely focus on startups that go from seed stage all the way to IPO and past. What is it that is so important for a founder to consider when they need, like they're starting up their company, they're thinking of people, products, etc. They're going to build and acquire. This relationship is also important. Can you elaborate a little bit on how that is very important for founders to consider at very early stage and how you are a partner to them?

SPEAKER_05 1:22:42

Absolutely. So we're we're relationship banking, we're relationship driven, relationship coming from the investors all the way down to the founders themselves. So, in course of everything that we do, that's the core of it. And to us, what that means is we increase the probability of success for our founders. So we we love getting to know companies, what they do, work with them personally. You need a face, not just a faceless interface. You need to talk to a human being that understands what they're building and how they're building and what they're doing, who they need to talk to. And then we roll up our sleeves and try to help everyone can, which is introductions, it's inviting them to events, to dinners, a programming to help them along the journey. It can be it's lonely, it's a lonely journey when you're a founder. And so we try to add light to that and help and provide resources along the way, which is unique to the founder journey and venture and adventure back company. So, you know, from that perspective, we we truly are unique and we've built out that model. And then from the product perspective, we understand companies that by definition are gonna run out of money unless they raise again. And we know how to lend to them, we know how to have credit cards um that help advance that in terms of getting into some nuance there, but uh, don't need to do that. But if your company is getting and it's going really well, you're gonna still burning, so your balances are coming down. So that's when you least need or want your ability to use your credit card to go down. And that's something unique that that SVP knows how to, you know, with. And that's just one example of many. It goes across the board the different ways that you can help that we understand as an institution through our products, how to work with um venture back startups.

SPEAKER_08 1:24:37

So let's kind of go into the outlook for 2026, right? What does your institution see from a macroeconomic perspective uh 2026 will look like for founders? I mean, the let you know, our audience is a good mix of founders and investors. So from a founder perspective, what as an institution you guys are looking at and forecasting and saying, hey, this is what 2026 is going to look like. And these are the categories that might be of importance.

SPEAKER_05 1:25:10

Yeah. So there's the superficial view, and then there's what's happening under the hood. And what's happening under is messy. There's a lot of things changing in the ecosystem through and through. Right now we're entering one of the periods of time when it's been most, from an investor fundraising perspective, unequal. You can have Andreessen raising $15 billion, which is phenomenal. But then the bottom 50, it's wrong to say bottom, but the funds that are so much smaller, that have a different focus, they are not getting as much funding. It's uh it's sucking the oxygen out in a way from the LPs as they um as the LPs themselves are figuring out their allocations and also looking for a return. So it it's the IPO window has been a little a little open. And actually, we were kind of surprised it was much more open in 25 than we thought it was going to be at the beginning of 25. So that's gonna lead to a lot more capital recycling through the system and funding more more venture capital as well. All that to say that in 26 we're expecting we're expecting more funds to close. We are expecting that to go up. We expecting um slightly more in terms of what we're forecasting for you know series eight venture deals. 25, we saw um we saw about six. And we're expecting you know 1500 to 1600. So about the same equal in terms of series eight venture deals, and there's how much and what valuations and how that's shifting and adjusting as well. But across venture deals that are less than 100 million, which is important to call out that, you know, excluding some of the outliers, we're speaking about 10,000 of those in 26. And in IPOs, we were for we forecasted 10 IPOs in 25. We saw 21. And in 26, we're we're forecasting 30. Again, we hope that we're underestimating it. We're expecting some big ones and more capital to be recycled in the system. So, you know, there's an optimistic take here. In general, we're seeing forecasting of about two rate cuts this year. We'll see how that ends up. There's different political macro to be considered and how that plays into it. The data that we see, you know, can be questioned depending on where it's coming from. So so what it really ends up being is it's who knows. Um, I certainly do not. You know, that kind of uncertainty aside, see uh I definitely see an optimistic future for 26.

SPEAKER_08 1:28:00

And where we oh that's great to hear. You you do you have a uh you're little bullish on the IPO market for 26 compared to 25, so more could go up. This leads to this question, right? In this age of AI that we are all in, do the IPOs that could happen in 26, do you guys expect that to be a comparison for how the valuation of startups could be affected, meaning the unit economics may be known because of filings? It could be the growth could be known because of filings and disclosures. Would that affect valuations? Or do you see that in the age of AI, your the investors are valuing them for being in AI?

SPEAKER_05 1:28:52

I think what you're alluding to is that there's a premium if you're an AI company, there's a promise of a future that you're investing in that is popping up. But then when you put you know, rubber meets the road, where is that real value and what is that as a multiple of you know their actual revenue? The valuation of open AI versus its actual revenue is a very significant, it's an outlier. So the answer is yes, and I do think that there's an exuberance that went into these evaluations. And I understand part of the reason for it, where if you're have the conviction that this company that you're investing into is going to be this category-defining creating leader, then there's a premium to that. That's that's like the AIs. Then you invest in that, assuming that's the case, and still think you're getting a deal for it. Now, whether that actually pans out or not, it's just that's just part of venture. When you have one or two companies that that that make it out of your portfolio, that maybe returns the fund, and that's the model. So that's a kind of long way of saying that yes and no. And then as that plays down to the earlier stages, that that becomes more interesting. You may have more, you could have more muted uh valuations at earlier stages, but again, that's also when you're investing the most into that future dream. So it really does depend. Just a great non-answer.

SPEAKER_08 1:30:32

So but this sort of opens up, right, the question. Do you, as you look at the landscape, because you see multiple startups come through your door every day, right? Anecdotally, we hear higher levels of funding and valuation set for early stages, right? So the question is from your data, do you see that earlier stage AI startups are getting more funding or getting higher valuations than normally? That is normally as in going back a few years, where there was, if you early say there was some formula that everybody worked towards, right? There was investors either decided that I want to own this much or that much. But it seems like all that has changed. Does your data reflect that, especially for early stage companies?

SPEAKER_05 1:31:22

Yes, valuations have gone up. Yes, I that could be inflation. That could be there's there's a bit of it that was AI, but it doesn't feel that way anymore. I think um the market that we serve anyway, here in the state of Washington, there's there's a lot more groundedness to the investors and the expectations of the founders. So while you still have a few really large seed rounds, there's in general, to me, it seems that AI has reached a convergence with what would be traditionally considered just enterprise, SaaS, B2B kind of investing. And so it's it's an up it's using an application, it's using a technology, but it's the same way that you would utilize cloud or sell into that and mobile or mobile before. And I think where we are is we've got through the exuberance, and now we're in like rubber meets the road, but it's almost like everything is AI, so like just investing in AI, and then it seems to be like another word of saying enterprise SaaS or whatever that model happens to be. Then and so then you are seeing more of the traditional metrics coming through. Part of that too is VC-driven in the sense of you know, you come to a thesis, you have a check sizes that you can write for a target equity ownership, and from there you can back into the maximum that you can value a company before you're not able to write a check your update. So you kind of you you end up in this situation where depending on how you in general, in general, it you're still kind of constrained based on those expectations.

SPEAKER_04 1:33:29

Right. Right, right.

SPEAKER_05 1:33:31

But valuations aren't going up.

SPEAKER_04 1:33:33

Well, that's that's a that's uh that's actually the the good thing.

SPEAKER_08 1:33:38

If you if you're a founder, it's worth noting the valuations are going up. This leads me to this other question, right? In this in this area, in this geographic area, in the past, we have skewed more towards enterprise SaaS or enterprise B2B startups as opposed to direct-to-consumer or B2C or any of those, right? Do you see that in from what you guys are viewing every day, AI has changed that mix in any way? Meaning because coding is not the mode anymore, getting your word out may be different than before. You could do a lot more. Do you see the area shifting away, or at least not shifting away, at least seeing any movement up in terms of consumer startups as opposed to only B2B startups?

SPEAKER_05 1:34:31

I'll speak for myself.

SPEAKER_08 1:34:32

Yeah, yeah, yeah.

SPEAKER_05 1:34:35

I think that part of the challenge AI has experienced is you can make rational arguments to enterprise and say, here's my ROI, you can create this efficiency, you can argue for why it's working for the product in behavior and with AI behavioral changes not just on a business process flow chart, but on your day-to-day behavior as a human. So that ought to be easier to rational enterprise buyers, but that's still hard. As you say, change your actual process of your job function. And for a consumer, it's another step to difficulty to change behavior. And I think ChatGPT definitely has led away. Part of it is the limitation of human imagination. Like AI can do a lot for you, but a lot of that depends on your creativity to prompt it to do something for you. So all that's back at saying that that I think that um super AI is harder for me to understand than the enterprise AI.

SPEAKER_08 1:36:10

So you uniquely you've been a founder before. So you've been you've been on that journey, and you described it that a little bit in your introduction. Put yourself, put that uh founder cap on for a second, right? And uh think you're getting started in 2026 at this point. What would be the approach that you you would say founders should take that now when they come to an institution like yours, they'll say, yep, that's uh uh that's a viable uh uh uh you know founder that we can get behind. Forget the idea itself, right? But you still need the founder to execute. So since you've been one and now you're evaluating them, uh go back to being the one you were and tell that founder that you were before what would you do differently with for the institution, given all this AI impact that we're having in day-to-day lives.

SPEAKER_05 1:37:11

Well, I this is gonna sound I I love founders that talk to their customers and get feedback, aren't afraid to launch or make a mistake, and then iterate. And uh that feedback loop is the most virtuous one that is founder left at the early stages. So when I see that I see someone that that can pivot, that can take feedback and is able to you you know you walk into to starting the startup because you have some insight or something that that you're solving for, but then that feedback only makes you better for doing that. So you already started at a place that at a place where you have a unique insight and can solve something, and then you take that to the next level. That extra level is the mo. And so that's that's what gives me the most confidence in the founder.

SPEAKER_04 1:38:03

Right, right. That that's that's good advice.

SPEAKER_08 1:38:06

Shifting back to the outlook itself, you guys uh went in, looked at 2025, and when when you said this would be what 2026 looks like. Could you specifically talk to what the region experienced in 2025 and what you guys have as your outlook for 2026? Because you have a unique regional point of view that I think would be very valuable. When I say region, I mean the Pacific Northwest region that uh that you guys serve.

SPEAKER_05 1:38:39

Absolutely. So we saw massive growth in and I feel like versus 24. It at the seed stage went from C C it stayed about the same, actually. You know, um pulling up some numbers here, about 500 in funding at seed, seed and pre-seed, and then versus 524. But in 24, I definitely have a very strong, I had a very pessimistic point of view of what 25 would look like. I thought we used the word seed apocalypse, where we thought all these companies raise a seed and everybody's gonna be trying to raise their A at the same time, and something is gonna happen. But the investors stepped up in around Washington. Series A in 24 um was 850, and in 25 was over a billion dollars in Washington. And a lot of that is because a lot of funding came from out of Washington. I'd say Washington is a net importer of investor dollars. So I you know, I would advise any startup around Seattle to talk to your local VCs, of course, they understand you and your market and what you're trying to sell the best, but also talk to VCs from outside of Seattle because they really like the talent and the opportunity that's here. So there's uh so I I would definitely say and then you know Series B similarly, um in 24 was uh 850 about, and then in 25 is is 1.26 billion.

SPEAKER_04 1:40:28

Yeah.

SPEAKER_05 1:40:29

So companies are graduating. I'll say that. They are graduating, there is more funny going into it, but it is a lot more rubber needs to run. It is a lot more of like, okay, where's that revenue? And the graduation rates are still they're still kind of an gimmick. You're seeing a lot more between rounds, um a lot more extensions, which is honestly perfectly fine. And that's just part of the process. I'll also add that these numbers don't capture absolutely everything. There's a lot that are undisclosed and unannounced, and folks prefer to fly within radar, which is fine. Um, totally understandable. But the in in 20 in 21, um, if you had a series A company trying to graduate to Series B, about in 24 months, about one-fifth of them would have graduated.

SPEAKER_04 1:41:28

30%.

SPEAKER_05 1:41:29

In 20 in 24, and we this is as far as the data kind of goes for that metric because it hasn't been 24 months since 25, but in 24 it was 12%. So you'd expect in two years to graduate, but that graduation rate has been has been going down. And part of that is like, okay, the extension and you know, pivoting with your own AI and so there's there's some of that for sure. So I'm kind of interested in how the graduation rates are going to shape up through um as we look back in 25 and those that up rates.

SPEAKER_08 1:42:04

Even though there is increased dollars in 25 and A and B, which means the companies started before that, right? I mean they started in the 23, 24 time frame, etc. Um you the con it seems like there's concentration from what you just said, there's concentration in a fewer number of companies with a lot more dollars, right? Because if the total number of companies were to have come down, graduation has come down, that means the ones that survived got more, or ones who raised money, I would say survive, got raised money, got more, got more. That's a very interesting perspective, especially given that you may made the comment that uh we are a net importer of investment dollars in the area, which means others are coming and looking for things here. Extremely insightful data there. When you look at the data, are there particular verticals or vertical applications, or is there gravity towards, hey, I'm gonna go do this, or more, you know, you find a ton of them trying to solve for a vertical or a or or a particular area, sector, etc., than ever before because uh seems like in AI, this hey, I I gotta solve for this, right? Or versus that. You guys have this aggregate view compared to others.

SPEAKER_05 1:43:32

Yeah, I'll say I'm seeing a little more of like platform technologies coming out of coming out of the area. So it's the the companies that build something so you can then build over that. And that's that's been really exciting to come out. That that to me is more categoried kind of technology that you're not building, you're building to make building easier or better. So that so that's been actually kind of interesting, and I kind of expect to see more of that. The the stuff that I like to say is that uh the Seattle area has 24% of AI engine areas, and we don't have 24% of the unicorns in AI. So I do think in general that we will have that. And and that's where that's gonna kind of it's gonna come from. I think that by and large, that kind of thing takes a lot more like you're trying to hit home runs. You're trying to hit home runs when you build those kind of technologies, they work or they don't, and they take a lot of investment up front. In between, we're also a city that likes to just hit the doubles, singles and doubles. So it's like I want to solve this problem, and it's basically an enterprise company that uses AI to solve the problem. It's and that and that those companies are gonna do great. But they've always been here, we've always been that kind of town. And that's not going to be right. I'm just seeing more of like, okay, there's the there's that other category that's been growing here. And honestly, I think that's what's drawing a lot of the outside dollars.

SPEAKER_08 1:45:16

Capital, right, right. In capital formation, right, there's founders tend to move towards equity, right? They may raise through a convertible debt instrument, but the fundamental idea would be to eventually convert it into equity. As these uh A and B rounds become bigger, as you pointed out, that they're as in concentration was happening. Do you see a role for debt even in early stages at this point? Or is there an increase compared to some time before?

SPEAKER_05 1:45:49

I'll answer this in a couple ways because it it changes when they're talking about AI or when you're talking about another if you're talking about frontier tech or space tech, something that has physical capital requirements, then you want to augment and really think about your capital stack. So part of what's unspoken is how Space Tech has and Frontier Tech around Seattle has just exploded. There's a lot of really notable companies based out here, whether it's like Stokespace, BarCloud, Starfitch, these companies that have you know raised significant funding, but they have a lot of capital requirements. You want to think about um that these things start coming more to mind on how you use equity dollars. So if you're buying a CNC machine or you're buying like a piece of equipment, then you probably want to finance that simply because you want to spend your equity dollars to build the IP, the real value drivers of the enterprise. So from that perspective, yeah, you definitely want to think about that. But primarily what we're seeing, like when we think about AI, we think about you know, how does the bank help in terms of venture debt? So coming alongside a venture round, extending runway. But the reason to extend runway is because you're doing you're you're you're adding gasoline to the fire. If you hit the investors say, we want you to hit, you know, two million dollars of ARR so that you can get to the next round, financing yourself another six months to in order to grow that to two and a half or three will get you a much better valuation at the next round, which saves off dilution and equity costs and all that. The cost of it is it's just it's just debt pricing, which is bank pricing, which is super cheap. So relative anyway to to equity. So we are seeing we are seeing that. And I honestly am excited about it. The main thing is that you don't, you know, we want to be cognizant on the use of debt and the VCs want to know the bank being around for 40 years and knowing exactly how we operate uh is super helpful. Yeah, but really you don't want to use debt if just to to extend runway if it's not working, because then you belong in the inevitable and your time is better spent with a new enterprise. So uh so it's understanding what the what the new what the nuances there are, and when it comes to uh AI being capital efficient means that you get to think about it more in terms of the true runaway extension for for your evaluation and timing on the next round.

SPEAKER_08 1:48:31

Awesome. So all our guests uh make predictions for 2026 for this particular episode. I'd like for you to make two predictions. You're the only one who's gonna get two. One, your personal prediction, because you've been an entrepreneur, so I'm very interested in understanding your personal prediction, and then a prediction based on the data that you see as an institution, right? Those those are two different things because you I'd like to get both of those, and so you've got to make two predictions, then we'll come back at the end of the year and record another one and and and see how those came out.

SPEAKER_05 1:49:08

Okay. There's going to be a muted AI bubble pop. And that's my personal prediction. I think that I mean, I keep saying rubber meets the road, like there's an exuberance on technology and what it can do. But it's not gonna be super impactful. It's just going to be something that happens, a minor correction here or there, but it's not going to be category destructive. So that's that's one prediction. That puts us on the right path, ultimately. Then my second predict, there there's been a lot of talk. This one, this one's spicy.

SPEAKER_04 1:49:48

Mm-hmm. That's good. That's good. That's what we want. Hot takes.

SPEAKER_05 1:49:54

I think that there's been an over-exuberance on like dual-use investing, and a lot of folks are gonna get burned on what that means. That's I and I think that will start to to temper down. And VC investing will focus on what it should always be focusing on, which is building generational changing technologies versus selling to government.

SPEAKER_08 1:50:17

Very good. Well, first of all, thank you very much for participating and enlightening us on your role with Silicon Valley Bank and also Silicon Valley Bank's role in our region. And thank you very much for both. And we look forward to more of uh your bank participating in in our ecosystem every day. Thank you very much.

SPEAKER_05 1:50:44

My pleasure, Gary. Thank you so much for having me. Thank you.

SPEAKER_08 1:50:47

Yeah.

SPEAKER_07 1:50:48

Thank you for listening to our podcast from Startup Big brought to you by DIC Seattle. Assisting in production today are Isha Jain and Mini Varma. Please subscribe to our podcast and rate our podcast wherever you listen to them. Hope you enjoyed it.