Matt Turck

Quick S-1 Teardown: CoreWeave

In the tradition of previous quick S-1 teardowns (Snowflake, Palantir, Confluent, Klaviyo, Cerebras, etc), some quick notes on the CoreWeave S-1 from my colleague Aman Kabeer and I. As in prior efforts, this is not meant to be 100% comprehensive (and it’s certainly not investment advice!).

The CoreWeave IPO is going to be fascinating to watch: partly because it is undeniably exciting, and partly because it is not going your standard tech IPO. It presents a profile that in some ways is typical of a hyper-growth tech unicorn (explosive growth, large losses, dual-class stock structure with Class A/B shares, etc.), but in other ways, it is very unlike most tech IPOs of the past. Its specialized business model, heavy infrastructure focus, heavy customer concentration (Microsoft), reliance on big partners (NVIDIA), financial structure ($7.9B in debt) and unusual risk factors make it a unique case that blends the characteristics of a cloud provider, a hardware company, and a startup riding an exciting but also sudden and unproven market wave.

SOME KEY TAKEAWAYS

Frivolity: Crypto pivot, NJ in da house: For all the jokes on social media about founders, startups and VCs pivoting from Web3 to AI, CoreWeave is an example of a business that started as a crypto mining operation, stockpiled GPUs, and pivoted to AI with spectacular success.

In the same (frivolous) vein, for all the “all AI is in SF” mantra, CoreWeave is headquartered in… New Jersey.

The First Generative AI IPO: Depending on pricing, there’s likely going to be tremendous interest in the IPO. This is in part because of the well-documented dearth of tech IPOs, but most importantly because it’s the first IPO of the Generative AI era (Cerebras, as far as we know, is still stuck in CFIUS review of their relationship with G42).

There are very few “AI pure plays” on public markets – Palantir is one example (cue in the never ending discussion as to whether they are truly an AI company), as is (even more arguably) C3 AI. Other than that, the way to “play” Generative AI has been to invest in Mag 7 companies.

It is no accident that the first companies to file S-1s in the Generative AI era are infrastructure companies. The market has been forming supply-first (chips, data centers, foundation models), with the major hope that the demand side surfaces equally meaningfully in years to come.

Not a Real Estate Play: A negative take on CoreWeave and comparable companies one would often hear in tech circles is that the company is a “real estate play”, with limited technology and software. The argument seemed to be supported by the fact that the co-founders of the company come from a financial, rather than technological, background.

AI in 2024: Never a Dull Moment

In AI, it’s been the year of big, bigger and biggest. My colleague Aman Kabeer and I just did a fun episode of The MAD Podcast where we discussed what we’re seeing in the market, our favorite trends and new stories, and where we see things going.

Here’s the video, and I summarized below a few highlights:

Quick S-1 Teardown: Cerebras

Look up in the sky! It’s a bird! It’s a plane! It’s… an IPO. The Cerebras S-1 filing is interesting in many ways, but certainly one is that, well, it is an (upcoming) IPO in the first place. In a context where tech IPOs have been at an all time low, with a very modest uptick in 2024 (Reddit, Rubrik, etc), the fact that a VC-backed tech startup has filed is rare enough to be exciting and newsworthy on its own.

The other unmistakable part of the filing is that Cerebras is a “pure play AI” company, in a context where there’s been a dearth of such companies in public markets, outside of Palantir and arguably a couple of others, like C3 AI or recent entrants like Tempus AI and Astera Labs. For the most part, public market investors have had very limited options to play the Generative AI wave: essentially NVIDIA, and indirect bets on AI through the hyperscalers. (This scarcity of AI stocks and to some extent, data infra stocks, is a reality we captured in 2021 through our MAD Public Company Index, that will soon be worth updating as hopefully more IPOs happen).

Is SaaS dead?

Many SaaS stocks have been getting clobbered in public markets. Some see the “end of software“.

Is SaaS dead?

What seems to be happening:

tough macro, cost cutting
AI sucking the air out of the room
SaaS vendors perceived as “last generation” despite best efforts to add AI quickly
enterprise budgets for AI are not net new, they’re taken from somewhere (SaaS budgets cut)
Bulk of budgets going to OpenAI/Azure etc because low hanging fruit to “do AI” (knowledge bot, coding)
for the more specialized enterprise apps, customers feel like they can/should “build” internally rather than “buy”

What happens next:

customers realize that “build” is a headache, not always the best option
OpenAI / Azure etc can’t / doesn’t want to build hundreds of problem specific/ vertical specific apps
Takes time, but legacy and new SaaS companies truly become AI-first (not just marketing), abstract away complexity of deploying LLMs
macro environment eventually rebounds
AIaaS becomes the new SaaS – what is old is new (unedited Sat morning thoughts)
Question is what happens to all current SaaS unicorns and public companies as this transition happens

(unedited Saturday morning thoughts)

MAD 2024: Trends in AI & Data (video)

As a companion to the 2024 MAD (ML, AI & Data) Landscape (blog post, PDF, interactive website), my colleague Aman and I had a fun chat about some key trends we see in data and AI.

Some topics we covered:

The impact of open source in AI
The future of AI agents
Where are we in the AI hype cycle?
The emerging AI stack
Will AI kills SaaS?
Is the Modern Data Stack dead?

Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape

This is our tenth annual landscape and “state of the union” of the data, analytics, machine learning and AI ecosystem.

In 10+ years covering the space, things have never been as exciting and promising as they are today. All trends and subtrends we described over the years are coalescing: data has been digitized, in massive amounts; it can be stored, processed and analyzed fast and cheaply with modern tools; and most importantly, it can be fed to ever-more performing ML/AI models which can make sense of it, recognize patterns, make predictions based on it, and now generate text, code, images, sounds and videos.

The MAD (ML, AI & Data) ecosystem has gone from niche and technical, to mainstream. The paradigm shift seems to be accelerating with implications that go far beyond technical or even business matters, and impact society, geopolitics and perhaps the human condition.

There are still many chapters to write in the multi-decade megatrend, however. As every year, this post is an attempt at making sense of where we are currently, across products, companies and industry trends.

Here are the prior versions: 2012, 2014, 2016, 2017, 2018, 2019 (Part I and Part II), 2020, 2021 and 2023 (Part I, Part II, Part III, Part IV).

Our team this year was Aman Kabeer and Katie Mills (FirstMark), Jonathan Grana (Go Fractional) and Paolo Campos, major thanks to all. And a big thank you as well to CB Insights for providing the card data appearing in the interactive version.

This annual state of the union post is organized in three parts:

Part: I: The landscape (PDF, Interactive version)
Part II: 24 themes we’re thinking about in 2024
Part III: Financings, M&A and IPOs

New Investment: Lago

Billing infrastructure has been a vexing issue for generations of software and Internet companies. It is mission critical infrastructure and as such, feels like a problem that should have been sold a long time ago. Yet ask any company and you’ll generally get the same reply: they’re dissatisfied with their billing system, which doesn’t offer the level of flexibility to address their specific needs and the many edge cases that inevitably pop up.

The problem is only getting worse as the software industry transitions from subscription-based to consumption-based revenue models. What started as a trickle is becoming mainstream, as usage based pricing unquestionably builds better alignment with customers. This transition will only be accelerating, as an entire generation of new AI companies coming online that are almost all using that pricing model.

Today, we’re excited to announced our Series A investment in Lago, the leading open source metering and usage-based billing company. Lago offers both a self-hosted and cloud, scalable and modular architecture, and found strong product market fit both as an open source project and a commercial product.

Our investment thesis is pretty simple:

Usage-based native: Lago is natively focused on the specific problem of usage-based billing and as such, incredibly well positioned to be the default solution for a whole new generation of companies, including in particular AI companies – it is not accident that customers already include AI unicorns like Mistral and Together AI
Open source: other than the fact that we love open source infra in general (as evidenced by our investments in Cockroach Labs, ClickHouse, Astronomer, SurrealDB, Quickwit, etc), open source is a particularly formidable advantage for the billing space in general, as it enables a level of extensibility and composability that is uniquely suited to edge cases. Lago is a natively open source company with strong OSS traction and a vibrant community
Europe/US: Lago is one of those bi-continental companies we love at FirstMark, with product and tech based in the vibrant Paris tech ecosystem and GTM, over time, in the US. Particularly as its ambitions go beyond “just” billing, Lago will be building a tremendous amount of product over the next few years, and will be well served by the relative cost advantage that a European location offers.
Team: Needless to say, first and foremost we love the Lago team, led by co-founders Anh-Tho and Raffi, both incredibly thoughtful and gritty. The Lago team comes from a place of deep industry knowledge, having built the entire billing infrastructure at fintech unicorn Qonto.
Bonus: getting to hear my colleague Aman repeat “open source metering and usage-based billing”, an area he’s particularly passionate about, thousands of times with equal enthusiasm

We very much look forward to working with Lago, and we’re excited to join a great group of prior investors including our friends at New Wave, SignalFire and some of the “French AI mafia” like Clement Delangue from Hugging Face and Romain Huet from OpenAI.

Of course, Lago is hiring.

My VC resolutions for 2024

1) Be an AI leader: Buy at least one share of Open AI in that employee secondary at an $86B valuation – then change website and all social profiles to “early believer and investor in Open AI”

2) Leverage the network: In conversation, drop frequent references to “Sam”, “Satya” and “the Besties” – I put in the hours building the relationship, by liking their tweets and listening religiously to the All-in podcast, now people need to know I’m tight with those guys

3) Add value: Formula 1 is a major sport in the US now, and founders in my portfolio will want know that I “get it”. Plan on attending several Grand Prix in 2024. While in Miami, Vegas or Monaco, send founders energizing texts like “Do you have the DRIVE TO SURVIVE?”, or “What would it take for us to be in POLE POSITION next year?”. They may not reply, but I know they will appreciate.

4) Refine investment thesis: Ok, so, I haven’t really done a new deal in over a year. What do other VCs invest in these days? AI is cool but exhausting, changes like every day. Defense tech seems hot, and blowing sh*t up is fun, so maybe? Heard about “nuclear fusion” and “superconductor” – ask ChatGPT to explain those “like I’m 5”, then tweet that out, to establish thought leadership

5) Inspire: Founders love it when VCs tweet during weekends and holidays things like “How bad do you want it?” or “Hustlers never rest!”. Pre-schedule a bunch of those tweets to automatically publish throughout the year.

6) Be a VC leader: Founders calling me all the time gets annoying, but I always have time for journalists. On the record, comment on VC firms doing layoffs or shutting down and say it’s “healthy for the industry”, but doesn’t affect me because I’m “top quartile”. Off the record, give the journalist a list of GPs who beat me on deals as examples of folks who are “in serious trouble”.

7) Stay fit: First it was kitesurfing, then it was pickleball. These days it’s jiu-jitsu a la Zuck, Elon and Lex Fridman. Possibly also padel? Gosh, few understand the level of pressure VCs are under to perform.

8) Be a master planner: Didn’t do a good job planning last year. Designer clothes showed up late at Art Basel, didn’t get my usual suite upgrade at the Crosby Hotel in SoHo, and missed the best DJ set at Slush. Do better in 2024. Upgrade my boat setup for Mykonos this Summer, and be the ultimate “man in the marina”.

Happy new year! LFG 2024!

P.S. Holding myself to the highest standard year after year, see 2023 VC resolutions, 2022 VC resolutions

New Investment: Sparta Commodities

If you scroll through the list of biggest companies in the world by market capitalization, it will come as no surprise that, in the now tech-dominated ranking, commodities companies continue to be heavily represented, with many familiar names such as Saudi Aramco, Exxon Mobil, Chevron, Shell, Petrochina or Total.

Those companies are not just large, they are also cash-generating machines: 11 of the 20 most profitable companies in the world are commodities companies.

Of course, the world of commodities (energy resources, metals, agricultural goods, etc) also manifests through commodities trading – the exchange of different assets, typically futures contracts, where investors make bets on the expected future value of a given commodity, whether for economic or speculative reasons. Alongside equities and fixed income, commodities is one of the key asset classes in financial markets.

Quick S-1 Teardown: Klaviyo

Is this it? Are we back? Everyone in the startup and venture world has been waiting for months for the re-opening of the IPO window. After a record breaking 2021 (1035 IPOs, beating the previous record of 480 in 2020), 2022 saw a dramatic decline (181 IPOs) and 2023 so far has not been much better.

Common wisdom in the market over the last few months has been that Q4 2023 would be the time the IPO window would cautiously re-open for technology companies (recent non-tech IPOs like restaurant chain Cava being considered non-representative). And it would be crucial that some of the very best companies (the usual suspects being Stripe, Databricks and Instacart) would go out first, to pave the way for a bigger wave of quality companies right behind them.

Well, this week has been an exciting one – on Monday, ARM filed its F-1 (here) and just today (Friday August 25), both Instacart (here) and Klaviyo (here) filed their S-1s. It’s going to be exciting to see what happens this Fall in IPO land.

New IPO filings also mean fresh opportunities for the time-honored VC tradition of S-1 breakdowns, even though timing is unfortunate given summer vacation schedule – here and here.

Consistent with my general investing focus on data and ML/AI, I’m going to pick Klaviyo for this first breakdown of 2023, as it’s a heavily data-driven business. As I did in the past (see the S-1 quick teardowns for Snowflake, Palantir, Confluent, C3, nCino), this is meant as a QUICK breakdown – mostly unedited notes and off-the-cuff thoughts, in bullet point format.

Let’s dig in.

In Conversation with Florian Douetteau, Co-Founder & CEO, Dataiku (podcast + video)

An overnight success 10 years in the making, Dataiku, the leading enterprise AI platform targeting Global 2000 companies, was named “Partner of the Year” for data science, machine learning and AI by BOTH Snowflake and Databricks at their respective annual summit a few days ago.

The company, in which we’ve been proud investors since leading the Series A in 2016, has scaled impressively over the years, reaching $200M in ARR at the end of 2022, with a team of over 1,200 people.

It was a pleasure welcoming back CEO Florian Douetteau, for a conversation where we covered:

* Dataiku’s centralized approach to enterprise AI

* Emerging use cases for Generative AI in the enterprise

* Some leadership lessons learned along the way

Here are the links to the podcast (subscribe! give us 5 stars! etc), and the YouTube video:

This Week in AI: Databricks’ Acquisition of MosaicML

(This post is part of my “This Week in AI” series, which is general off-the-cuff market commentary. I’m not an investor in either MosaicML or Databricks)

$21M per employee. That’s the price Databricks is paying for MosaicML — a total of $1.3B for 62 employees (in Databricks stock, and also includes employee retention packages).

One thing is clear – if you’re going to be aggressively acquiring Generative AI startups, you’re going to have to pay up

But it may turn out to be cheap in the long term given the size of the opportunity.

That’s because, beyond any Generative AI capabilities, Databricks’ move needs to be understood in the broader context of its fierce rivalry with Snowflake.

Synthesia’s Series C – And a Few Lessons Learned Building a Generative AI Startup

Synthesia, the market leader in AI video generation, is announcing this morning an exciting $90M Series C financing.

This is a great milestone for the company, making it a newly-minted unicorn and adding strong new partners (Accel, Nvidia, and some great individuals) to the team. Beyond the fundraising momentum and accolades, however, Synthesia has first and foremost been building a really impressive business. Over 35% of the Fortune 100 now use Synthesia’s enterprise offering, and over 50,000 businesses use its self-serve product.

Much to their credit, the company’s founders (Victor, Steffen, Lourdes and Matthias) were very early to the Generative AI wave, starting the company at a time (2017) when there was significant technology risk and limitations, to the point that what they were doing was probably a bit weird, if not outright crazy. Several years later, by the time FirstMark led the Series A early 2021, the term “generative AI” was still not a thing – my blog post announcing the round used the term “video as code” and in my 2021 MAD landscape, Synthesia appeared in a box we called “synthetic media”, for lack of a better term.

Anecdotally, this Series C is another example of the growth market showing some sign of life lately, at least for A+ companies, in the same vein as Pigment’s recent announcement, albeit perhaps less surprisingly given the hype around Generative AI.

Given the explosion of Generative AI and the flood of brand new startups that were created in the space over the last 6 months, there are interesting early lessons to learn from Synthesia’s journey so far:

Pigment’s Series C – And a Few Thoughts on the Growth Market

Pigment just closed an exciting $88M Series C (TechCrunch coverage here). The company is rapidly emerging as the global leader in the next generation of business planning platforms (aka Anaplan replacement), a testament to the power of a world-class team delivering great execution consistently over years.

While we at FirstMark are certainly excited to have been a part of the journey as investors since the seed round, this round is also noteworthy in terms of what it may (or may not) signal about the broader market. A few thoughts:

Growth market: The last 18 months have been incredibly slow in the growth market. Yet this growth round at Pigment was completely preemptive, and highly competitive, involving a number of top firms. What does it mean for the growth market? Maybe it’s an example of continued flight to quality during a downmarket phase – investors seeking A+ companies. But maybe it’s also a sign of the growth market coming back to life, progressively. I certainly get an impression, talking to my growth friends, that everyone is antsy to do more deals after largely sitting on their hands for the last 18 months, and the market has recalibrated somewhat to more reasonable levels. The obvious caveat is that one shouldn’t derive pattern from a small n, but anectodally, another portfolio company of mine will also announce a growth round soon.

This Week in AI: Incumbents vs Startups (Microsoft Build & Adobe Firefly)

Note: those are quick thoughts on some of last week’s most interesting news in AI. I may, or may not (!) do this on a regular basis.

This last week in AI: Adobe killed all the Generative AI design startups with Firefly, and then Microsoft killed all the other Generative AI startups with its plugins and Fabric releases.

I’m sort of kidding, but sort of not. Kidding because, again and again, founders and startups find a way. But sort of not, because the speed of deployment of AI by the Big Tech incumbents is truly something to behold. Companies like Adobe and Microsoft have, of course, massive distribution advantages. It is undeniably problematic for startups to see Adobe deploying Firefly in Photoshop and Microsoft deploying AI copilots across, well just about every single of its products for consumers, businesses and developers (see the dizzying list of announcements at Microsoft’s Build conference this week).

I don’t think, however, that the world wants a Microsoft and Google dominated AI world. The best version of the future for the Generative AI landscape is to be “polyglot” with a variety of tools and companies. Open source is going to be play a huge role and it’s comforting to see so much energy there. And I have faith startups will build the best specialized tools and vertical solutions. It’s going to be a fun ride ahead.

Here’s a good piece from Sharon Goldman at VentureBeat on some of the Microsoft Build AI announcements that triggered those thoughts above