Revenue Durability in the LLM World

Angular Ventures Weekly
Angular Ventures
Published in
6 min readApr 2, 2024

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Angular Ventures Weekly Issue #219: For the week ended April 2, 2024

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Revenue durability in the LLM world
Gil Dibner

My favorite podcast these days is BG2Pod, a conversation between Bill Gurley and Brad Gerstner about the technology industry. The podcast feels like eavesdropping on an intimate and very thoughtful conversation between two very experienced friends who are genuinely trying to make sense of the complex world around them. It’s brilliant.

The last eight minutes of the latest episode of BG2Pod is a fascinating discussion of the commercial implications of the rise of LLMs. It’s probably the best eight minutes on that topic I’ve spent recently. Gerstner and Gurley make a few key points, but here are the three I found most interesting:

  • Tech is deflationary and LLMs are massively deflationary. Intense competition among well-funded foundational model companies and tech giants is driving down the costs of deploying LLMs. Open-source models are nipping at the heels of even the most sophisticated proprietary models. The value of these models is going up quickly, but the ability of the companies behind those models to capture that value is increasingly in question.
  • Data gravity. The concept of “data gravity” poses a real hurdle to LLM-first challengers. It has typically been easier to move new capabilities to where masses of data reside than to move masses of data to new platforms. Even as most LLM providers pursue PaaS-like models, hoping that customers move data onto their platforms, we are seeing existing data platform companies (GCP, AWS, Azure, Snowflake, Oracle, etc) aggressively add vectorDB and LLM capabilities to their existing offerings. Business models that rely on convincing customers to move massive amounts of data to new platforms to enjoy the benefits of proprietary models face an uphill battle. It’s often easier and usually preferable to add these capabilities to existing platforms (especially if leveraging open-source tooling).
  • Revenue durability is the key challenge. LLMs are intrinsically at odds with switching costs. By their very nature, LLMs are great at ingesting and leveraging unstructured data. The wider the context window, the easier it is to add data into an LLM and — hopefully — make sense of it. These realities make switching to LLM-based solutions pretty painless, but they also make switching out of an LLM-based solution towards another (perhaps open-source, perhaps internally built) pretty painless as well. Low switching costs are great for customers, but bad for vendors.

Our search for revenue durability. The final point, on revenue durability, is the real clincher. Everything about LLMs seems to make revenue durability more challenging than ever. As VCs, our approach has been to try to focus tightly on this question as we evaluate the current generation of AI-first/LLM-powered companies, both on the infrastructure and application layers.

  • At the infrastructure layer, we are seeking companies that combine some genuine technical innovation with deep enterprise-level workflow integration. The data gravity argument coupled with the rapidly expanding capability of open source models suggests to us that most of the value in this eco-system will accrue to infrastructure companies that empower the enterprise to roll their own LLM-powered applications. We are less convinced by the straightforward PaaS models pursued by the foundational model vendors or vectorDB vendors.
  • At the application layer, we are seeking companies for whom AI/LLMs are perhaps a critical enabling technology, but not the prime value driver. The deeper the workflow integration, the greater the potential stickiness and switching costs to customers. We have begun to find a few enterprise application companies that leverage deep domain expertise to deliver high-value solutions. LLMs often play a supporting role here but rarely play the starring role. The path to value creation for these companies can accelerated by LLMs in several ways: easier interfaces, natural-language queries, quick ingest of unstructured data, and generative output. But these companies’ path to value capture usually comes from somewhere else entirely: domain-specific models, generation of novel proprietary datasets, deep integration into human enterprise workflows, etc.

LLMs and GenAI provide powerful new tools for technology vendors and customers alike. They change the playing field, but they do not change the fundamental rules of the game. Within the new (and still emerging) rules of the LLM/GenAI game, we continue to search for companies that have a path to creating significant customer value while capturing value for their shareholders.

Whether you are building on the infrastructure layer or application layer, we are eager to hear about your plans to create value for customers while capturing value for your shareholders over a long time horizon. If you have a thesis for revenue durability in this era of LLMs, we would love to have a chat — so please reach out.

Gil

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Buying with AI. Tomasz Tunguz makes the case that AI will transform buyers’ processes for evaluating offerings, as AI can not only provide a thorough breakdown comparing two products, but also issue a recommendation tailored to the buyer. Effectively AI will be “a low-budget Gartner in box”. Tomasz specifies some of the ramifications this may lead to for those selling products. “Marketers must ensure the information surfaced in these queries is accurate. SEO is no longer sufficient. AIO, (AI-optimization), will become necessary to ensure the results are accurate. The workflow to achieve this outcome isn’t yet built but will undoubtedly influence inbound-marketing efforts.”

No matter what. Israeli startups have faced incredible challenges since October 7th, from their teams being drafted into service to living and working in an active warzone. However, despite all of this, the Israeli startup ecosystem is still doing relatively well. The Startup Nation Central reported that, since the start of the war, $3.1B had been raised by Israeli companies and $3.7B in M&A has taken place. The report states “that the rate of investment in startups has stabilized at half a billion dollars per month since the war, and mergers and acquisitions reached a peak of $2.6 billion in March.”

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Back to basics. Boldstart shared a must-read post for enterprise founders covering key takeaways from their recent Founders Day. Some of the best advice for founders included are to “Sell before you build”, “Your first ten customer contracts are about more than price” and “Pricing isn’t final or monolithic”.

TeamPlan. Index has released TeamPlan, a dynamic guide benchmarking tool for rapidly scaling startups from 1–500. It’s derived from data from 200K employee profiles at 200 top tech companies to help startups make data-driven decisions about their org design. It aims to empower founders to “hire the right people, in the right roles, at the right time”. Access TeamPlan here.

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Secondaries market. Following a slow few years, the secondary market is finally showing signs of coming back to life. ““It is picking up,” said Kevin Swan, head of private markets solutions for Morgan Stanley. “There’s an increase in activity after a lull as the spread on valuations have improved.” Those who watch and invest in secondaries see little reason to expect the market to see the dip it hit in late 2022 and well into 2023 as an improving venture environment, a growing amount of dedicated secondary funds, and a plethora of strong mature companies to invest in should propel the secondary market upward.”

PORTFOLIO NEWS

Reco was selected as the Startup of the Week in the latest edition of The Innovator. “With over half of organizations experiencing at least one SaaS breach in the past two years, SaaS security is no longer a nice to have, it is of critical importance,” says Reco Co-Founder & CTO Tal Shapira. “We want to enable big companies to protect their data and be in compliance, and the only way to do that is to help them deeply understand how their organizations work.”

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