Baron Fifth Avenue Growth Fund | Q2 2026

We had a great quarter.

Baron Fifth Avenue Growth Fund® (the Fund) gained 24.6% (Institutional Shares) during the second quarter, which compares to gains of 16.7% for the Russell 1000 Growth Index (R1KG) and 15.2% for the S&P 500 Index (SPX), the Fund’s benchmarks.

Year to date, the Fund is up 11.7% compared to gains of 5.3% and 10.2% for the Fund’s benchmarks, respectively.

In many ways, the first half of 2026 unfolded much the same way as the prior year. We highlighted the many similarities between the Fund’s 10.4% drawdown in the first quarter of this year, and its 13.4% decline in the first quarter of last year, which we attributed to the “tariff tantrum” and general macroeconomic unpredictability and instability. This year, it was the war with Iran leading to rising oil prices, increased risk of inflation leading to higher interest rates, and general macroeconomic unpredictability and instability. Last year, when the fears subsided and market participants decided that tariffs would be figured out and that they are unlikely to have a long-term material negative impact, stocks staged a strong recovery, and the Fund gained 24.9% in the second quarter. This year, the fighting was followed by a cease-fire with falling oil prices and a more stable outlook on inflation and interest rates, and the Fund bounced back with a 24.6% return. History may not repeat itself, but it sure does rhyme from time to time. From our perspective, the market once again over-emphasized geopolitical uncertainty, creating an attractive opportunity for long-term investors to take advantage of short-term stock price volatility.

From a performance attribution perspective, stock selection accounted for all of the outperformance contributing 940bps to relative returns, while sector allocation detracted 152bps. It was a weird quarter in terms of performance distribution as Information Technology (IT) (+21.8%) and Industrials (+21.3%) were the only two sectors in the R1KG to outperform the R1KG, while all other sectors lagged far behind. We did well in Communication Services (SpaceX and Alphabet), IT (now approximately 53% of the Fund AND 54% of the R1KG), and Health Care (Illumina and argenx), while poor stock selection in Industrials, Consumer Discretionary, and Financials detracted. We held no investments in Consumer Staples, Energy, Real Estate, Utilities, or Materials, which contributed 60bps to relative gains.

From a stock specific and absolute return perspective, the Fund’s strong performance was driven by 23 contributors against just 4 detractors. We had many big gainers in the quarter with 16 of our investments generating over 50bps each, as CrowdStrike, Alphabet, Amazon, and ASML added over 100bps each, Taiwan Semiconductor (TSMC), Datadog, and NVIDIA added over 200bps each, and SpaceX was our top contributor with 404bps. We had no material detractors this quarter.

After the indiscriminate “SaaS-pocalypse” of the first quarter, performance diverged in the second quarter based on each company’s perceived AI positioning, which made more sense to us. While high uncertainty in software remained, companies that demonstrated tangible AI-driven tailwinds, including faster revenue growth, accelerating customer spending, and stronger new-logo acquisition, outperformed. By contrast, companies reporting decelerating growth continued to struggle. In cybersecurity, for example, investors recognized that Anthropic’s Mythos-class models are likely to increase demand for security as AI makes bad actors more capable and dangerous. As earnings season began, leading cybersecurity platforms such as CrowdStrike described this as the “Mythos moment,” reporting record sales pipelines and raising full-year revenue growth guidance, which drove their stocks higher. Similarly, usage-based revenue businesses such as Datadog and Snowflake reported increased AI adoption and accelerating growth, leading to significant multiple expansion.

CrowdStrike’s Co-Founder and CEO, George Kurtz, described what he saw during the company’s first quarter earnings call:

“The discussion evolved from 'is AI going to disrupt cybersecurity' to organizations and even the frontier AI labs relying on Falcon as their AI-powered defender for the post-Mythos era. Even more consequential is how adversaries can use these new and future models to democratize destruction. Now, any human or agent can be a vibe hacker, or worse, wage serious cyber-attacks that threaten enterprise survival, nation/state continuity, and critical infrastructure operations... What I see is AI driving structural demand for cybersecurity that compounds, not decelerates. The AI enterprise is unfolding in real-time, and CrowdStrike is a necessity to secure it... It's on the backs of our strong Q1 results and the unprecedented market dynamics I see that we are raising our growth expectations for the full year net new ARR (annualized recurring revenue) by more than 500 basis points.”

Datadog’s Co-Founder and CEO, Olivier Pomel described the significant acceleration his business is seeing during its latest earnings call:

“There is no change to our overall view that digital transformation and cloud migration are long-term secular growth drivers for our business, but we now have an additional secular growth driver with AI as we help our customers deliver more value with this transformative new technology.”

And Snowflake’s CEO, Sridhar Ramaswamy, is seeing similar dynamics in his business (Q1 earnings call):

“Based on a combination of strength in our core data platform business and meaningful uplift from AI capabilities, including CoCo and Snowflake Intelligence, we are increasing our FY 2027 outlook from 27% to 31% year-over-year growth... Across our business, AI is strengthening Snowflake on multiple levels simultaneously.”

CrowdStrike, Datadog, and Snowflake continue to be core long-term holdings in the Fund.
 

Zero-sum thinking and humanity’s inability to think big enough!

Human brains tend to think linearly rather than exponentially. In addition, we often misinterpret a company’s gain as necessarily another company’s loss. As a result, investors often underappreciate the power of compounding in growing markets, mistakenly viewing them as fixed pies and overemphasizing market-share shifts within rapidly expanding categories. Amazon Web Services (AWS) is a useful case study. It began as the only major cloud provider and now competes with Azure and Google Cloud Platform, yet its revenue has grown to a $150 billion run rate as of the first quarter of 2026 as the overall cloud market expanded, making AWS a key driver of Amazon’s success. The same dynamic applies to NVIDIA. Since Google introduced its first TPU in 2016, investors have repeatedly worried that ASICs would disrupt NVIDIA. Yet NVIDIA’s data center revenue has grown 225-fold, from about $830 million in 2016 to $187 billion in 2025. Have TPUs gained share over the past decade? Sure. Has NVIDIA lost as a result? Not even close. The market expanded dramatically, and NVIDIA’s ecosystem has proven difficult to displace. It has the largest installed base, the broadest developer adoption, models are consistently optimized for its architecture, customers benefit from strong total cost of ownership and reliability, and utilization remains high because its architecture supports the widest range of use cases. Recency bias further compounds this issue by causing investors to overweight the latest data points relative to their true importance to the investment case. Google is gaining traction with TPUs, Anthropic has adopted them, Amazon is seeing growing success with Trainium, Meta is once again announcing its own ASIC, and China’s DeepSeek has announced one as well.

The current price of NVIDIA’s stock implies a terminal growth rate of 3% (GDP or less?), assuming weighted average cost of capital of 10%, starting next year. In other words, from 100%-plus growth this year, to 3% growth next year. We believe there is a disconnect between the valuation of NVIDIA, and for that matter, Broadcom and those of the AI bottleneck companies. If the market is right about NVIDIA, it is necessarily wrong about the AI bottleneck names, unless future AI demand is met by chips other than NVIDIA’s GPUs or Broadcom’s ASICs, which together effectively account for the entire market today, or unless their margins are effectively competed away. The reverse is also true. NVIDIA and Broadcom cannot trade as if AI is not real or not sustainable, while the broader AI buildout beneficiaries trade as if AI is just beginning. That said, both companies’ growth outlooks are so strong that we do not need multiple expansion, though we believe that risk is skewed to the upside.

Fundamentally, both companies continue to perform exceptionally well. NVIDIA’s Blackwell, its latest generation GPU, is the fastest ramping chip in the company's history, gaining significant share in networking, where revenues tripled year-over-year, and demand remains unprecedented, with approximately $500 billion of orders booked in roughly 4.5 months, just as AI is beginning to demonstrate real ROI with roughly $175 billion of ARR. Broadcom also reported exceptional results, with semiconductor revenues up 79% year-over-year and AI semiconductor revenues up 143%. The company signed a new long-term agreement with Alphabet, reducing the risk of Google insourcing. On the earnings call, Hock Tan, Broadcom’s CEO, described it as “a very, very strong agreement and it basically reflects the strength of the partnership we have simply because of the products we do... and any intellectual property we deploy into this whole program... it's a commitment that is very substantial in dollars. Very, very substantial amount of dollars.”

SpaceX

We had been under an NDA with SpaceX, which has prevented us in the past from fully explaining our investment thesis on the company. Now that SpaceX is public, we will attempt to explain why we are so excited about its prospects and long-term opportunities. We have often described ourselves as disruptive change investors and how disruptive change has become so critical and pervasive that we evaluate every investment opportunity through this disruptive change lens. We believe SpaceX stands at the intersection of two of the most consequential secular growth trends of our time: Artificial Intelligence and Space Economy. The company is the most likely (obvious?) beneficiary of multiple early-stage, large S-curves disruptions. SpaceX has built a set of durable, multifaceted competitive advantages that to us appear to be insurmountable and is led by one of the most accomplished entrepreneurs and operators in history whose culture continues to attract extraordinary engineering and product-building talent. From the standpoint of uniqueness and opportunity set – it has no rivals. This is THE company with N=1.

More than a decade ago, SpaceX solved a problem experts said was impossible: instead of discarding rockets after each flight, it made them reusable. Today, SpaceX can reuse a booster (the bottom portion of the rocket) up to 35 times, while the rest of the industry still discards boosters after a single use. As a result, SpaceX needs only 3 boosters for 100 launches, compared with 100 for the industry. This created significant cost, scale, reliability, and innovation advantages, supported by higher launch frequency and the data generated from landed rockets. SpaceX has built a platform business with launch at its core. As its cost and scale advantages compound, the company can bring mass to space at lower cost and higher volume than anyone else, with the gap likely to widen further as it transitions to Starship. Lower unit costs expand markets, as we have seen across other industries: Moore’s Law enabled massive growth in compute, mobile, and internet; the falling cost of genome sequencing, from millions of dollars to roughly $200 today, helped power growth in biotechnology and pharmaceuticals; and lower-cost, increasingly capable intelligence tokens have expanded the AI market. SpaceX has reduced launch costs from the industry standard of nearly $20,000 per kilogram to an order of magnitude lower with Falcon 9, while Starship targets another major reduction to below $100. Beyond the expanding ecosystem that relies on SpaceX for launch, the company’s vertically integrated connectivity business, Starlink, has further supported Falcon 9’s scale because most missions carry Starlink satellites.

Speaking of Starlink... despite already serving more than 12 million subscribers, we believe the connectivity opportunity remains quite significant. Starlink delivers faster, lower-latency connectivity that works virtually anywhere. In a market of largely undifferentiated connectivity services – where many regions still have either no service or poor, dial-up-quality service – Starlink is disrupting an approximately $1.5 trillion connectivity market. Any shareholder who has experienced a Starlink-enabled flight will appreciate the significance of this advantage. Could Starlink ultimately reach 20% market share? 50%? 80%? Each 10 percentage points of share represents roughly $150 billion of revenue opportunity, with very high incremental margins. This is a high fixed-cost business: once the satellite constellation is in orbit, the incremental costs are primarily user terminals, customer acquisition, and customer support, and SpaceX continues to improve efficiency across the value chain. Starlink also creates the potential to connect more than 3 billion people globally who remain unconnected today⁵. Competition faces a steep challenge: smaller constellations offer less bandwidth, resulting in inferior service, while competitors also lack SpaceX’s scale and reusable launch economics, making their product more expensive to deliver. In addition, we believe SpaceX is well positioned to become an important player in global defense through Starshield, its dedicated government constellation.

Over the past five years, we have written extensively about AI and the disruption and the opportunities that we believe it represents. Now, with NVIDIA valued at over $4.7 trillion and hyperscaler CapEx approaching $750 billion annually, we believe AI is just getting started. The first agentic use case to make AI genuinely useful at scale has been coding, and even that market is still nascent. Annualized recurring revenue (ARR) is growing rapidly, with Anthropic surpassing $47 billion in May⁶, OpenAI passing $33 billion⁷, and overall GenAI revenues reaching $175 billion⁸. The coding opportunity alone is substantial: there are approximately 45 million to 50 million developers globally⁹ and that population should expand meaningfully as AI lowers the barriers to software creation. The number of natural-language coders could ultimately be far larger than the number of developers proficient in Python, Java, or C++. According to Ramp, which observes actual enterprise spending across its customer base, a top 1% firm already spends roughly $90,000 per employee per year on AI, or about half the median developer salary. A top 10% firm spends approximately $7,300, while the median firm spends just $137 – and all of these figures are growing exponentially¹⁰. This suggests that coding alone could represent a multi-trillion dollar opportunity. If, over time, the median firm spends what today’s early adopters spend, the total addressable market could reach $4 trillion to $5 trillion. Extending that framework across roughly one billion information workers points to a potential opportunity measured in the tens of trillions of dollars. The range of outcomes is wide and will depend on the value AI creates, but the direction is clear: the more capable and lower-cost intelligence tokens become, the steeper the adoption S-curve is likely to be.

We believe SpaceX is emerging as a meaningful participant across multiple layers of the AI stack. The most immediate opportunity sits in the compute layer, where the company has recently signed its first terrestrial data center hosting agreements with Anthropic and Google, together representing $26 billion of annualized revenue. Based on our estimates, these contracts imply revenue opportunities in the mid-$20 billion per gigawatt for Anthropic and the mid-$40 billion per gigawatt for Google. If SpaceX scales to 10GW over the next several years, this could represent a $200 billion to $400 billion opportunity with very high incremental margins, assuming demand for intelligence tokens continues to exceed supply. We believe that is likely given the structural constraints around advanced chip production and memory availability.

Can SpaceX become a leader in AI hosting? We believe it already has, even with only its initial agreements with Anthropic and Google. SpaceX’s core competency is executing complex physical operations at an extraordinary scale: reasoning from first principles, eliminating bottlenecks, removing unnecessary complexity, optimizing, automating, and moving with unusual speed. The company has already demonstrated the ability to build data centers faster and at lower cost than others, including a 100,000-GPU coherent cluster in 122 days versus an industry norm closer to two years. In a market advancing this quickly, time is money! The sooner a data center comes online, the sooner it can begin producing valuable tokens and generating returns.

Still within the compute layer, SpaceX has a significant longer-term opportunity to place data centers in orbit. Picture satellites rather than buildings – powered by unlimited and free solar energy. While meaningful technical work remains, we believe SpaceX’s experience with Starlink satellites and terrestrial data centers positions it well to pursue this opportunity. Over time, as building data centers on Earth becomes more challenging and expensive because of regulation, power and cooling constraints, land scarcity, and construction costs, orbital data centers could benefit from effectively unlimited power, unlimited space, economies of scale, and a simpler regulatory framework. Starship is the prerequisite and therefore must come first. As for the scale of the opportunity, Elon has targeted 100GW per year by the end of the decade.

Over time, we believe orbital data centers could become the lowest-cost and most scalable architecture for AI inference. Their cost per gigawatt will depend on Starship reusability and the ratio of AI satellite weight to AI compute capacity. Based on the latest available information, Gen 1 satellites are designed to generate 160KW of AI compute per satellite, with the goal of increasing that capacity over time. Even at 160KW per satellite, each Starship Version 3 carrying 28 satellites would deliver 4.5MW of compute, requiring roughly 223 launches for 1GW. At SpaceX’s target of less than $100 per kilogram, a Starship launch would cost less than $10 million, implying total launch costs below $2.23 billion for 1GW of AI compute. By comparison, five-year total cost of ownership for terrestrial data centers is roughly $10 billion to $15 billion per gigawatt (excluding AI compute costs in both cases on the assumption they converge at scale). This implies that 1GW of AI satellites (roughly 6.25 thousand satellites) could cost approximately $8 billion to $13 billion and still reach breakeven versus terrestrial data centers. That comparison also excludes the fact that terrestrial data centers incur ongoing power and operating costs that orbital data centers would largely avoid because power and “land” are free in space. For a 1GW terrestrial data center, power alone can cost roughly $1 billion per year, depending on efficiency and location, and terrestrial construction costs are likely to rise over time. Over the past three years, SpaceX spent roughly $10 billion on connectivity CapEx while launching approximately 8,000 Starlink satellites, suggesting this cost envelope for AI satellites is plausible, particularly because AI satellites should be simpler to manufacture: they replace complex phased-array connectivity hardware with solar panels and radiators.

Moreover, as Starship reusability improves and AI satellite manufacturing scales, orbital data centers should become increasingly cost efficient. Reusability is critical not only to launch costs but also to annual deployment capacity, because it enables far higher launch cadence. At the same time, terrestrial data centers are likely to become more complex and expensive as they scale. For every 100GW added to a future constellation (SpaceX’s annual target) charging just $10 billion per gigawatt, below current market rates, would generate $1 trillion of incremental revenue, again with very high incremental margins.

Despite these advantages, we do not believe hosting is part of the endgame of SpaceX’s AI ambitions. Elon’s objective is clearly to extend much deeper into the AI stack – the model layer through Grok as a frontier model and consumer service, and the application layer through Cursor, beginning with agentic coding, and MacroHard for enterprise AI. We view terrestrial hosting as a bridge: it can lower the effective cost of building higher layers of the AI stack while helping seed the orbital data center business. If successful, orbital data centers could become the lowest-cost source of AI inference and the only viable way to build AI at truly massive scale. That, in turn, could create a new AI platform for SpaceX, analogous to the launch platform it has already built, benefiting both its vertically integrated businesses in models and applications by providing the cheapest tokens at unmatched scale, and the broader ecosystem through lower cost, far more scalable AI hosting.

In case all of this was not exciting enough… additional longer-term opportunities include TeraFab for semiconductor manufacturing, point-to-point transportation and logistics, in-space manufacturing, space mining, the lunar economy, Mars, and more. We are NOT assigning any value to these opportunities and are simply pointing out that the positive optionality imbedded in SpaceX is unlike anything we have seen before in our investment careers. This is what we mean when we say that SpaceX is N=1!

Space Exploration Technologies Corp. develops and launches advanced rockets, satellites, and spacecraft, with the long-term goal of making humanity multi-planetary. Shares rose as the company successfully completed the largest initial public offering in history, raising more than $85 billion. The proceeds are expected to accelerate growth across massive addressable markets, such as connectivity, launch, terrestrial and space infrastructure, and AI. Fundamental momentum was further reinforced by landmark compute hosting deals totaling tens of billions of dollars annually, including agreements with market leaders Anthropic and Google. SpaceX also announced its acquisition of Cursor, a premier enterprise AI-powered coding platform. Integrating Cursor’s technology, talent, and customer base provides another strategic steppingstone into the vast opportunities within AI applications and agentic systems. Lastly, the company conducted a successful test flight of the latest version of Starship, demonstrating meaningful advancements in rapid and full reusability. We believe these developments support sustained long-term revenue and profit growth well beyond current levels.

Taiwan Semiconductor Manufacturing Company Limited is the world's largest contract chipmaker and the leading manufacturer of advanced logic semiconductors used in modern AI accelerators. Shares rose 41.6% during the quarter as the company continues to report stellar financial results underpinned by AI demand with revenue growth of 35% year-on-year and EPS growth of 58%, with 66% gross margins and 58% operating margins. High-performance computing now represents the majority of TSMC's business. AI demand is consuming so much leading-edge capacity that smartphone and PC production is increasingly shifting to older technology nodes, reversing a dynamic that defined the foundry industry for much of the past decade. Management also raised its full-year outlook and increased capital spending to support demand that remains well above available supply. We retain long-term conviction in TSMC and view its leading-edge manufacturing monopoly, pricing power, and technology roadmap as durable advantages that support a long duration of growth.

Observability and cloud monitoring platform Datadog, Inc. contributed to performance with the stock up 121.3% during the quarter after reporting its strongest results in years. Revenue accelerated to 32% year-over-year growth, marking the fourth consecutive quarter of acceleration and meaningfully exceeding consensus estimates. Operating margins and free cash flow also surpassed expectations. Management raised full-year revenue guidance by roughly $240 million against a $50 million beat, with next-quarter guidance implying continued strength. Critically, the strength was broad-based: non-AI core customer revenue growth accelerated into the mid-20% range at scale, while Datadog's AI-native customer cohort diversified and expanded to 22 customers spending more than $1 million annually. Net revenue retention reaccelerated into the low-120% range, and unit economics remained best-in-class with 80% gross margins and high-20% free cash flow margins. We view observability as a structural beneficiary of the AI buildout through cloud migration, faster application deployment, and an increasingly complex technology stack. These broadening growth drivers reinforce our conviction in the long-term thesis.

Intuitive Surgical, Inc. sells robotic-assisted surgical systems. Shares declined 13.7% after the company's first-quarter U.S. system placements came in below investor expectations. Medical device stocks also broadly underperformed the market amid concerns that health care utilization trends could decelerate following the expiration of Affordable Care Act subsidies. Concerns were further compounded by the potential impact of Medicaid work requirements expected to take effect in 2027. Despite these headwinds, which we view as short-term in nature, we believe Intuitive can continue to grow revenue at a mid-teens rate for many years and remain positive on the company's long-term growth outlook.

Shopify Inc., a leading global commerce platform serving merchants across online and offline channels, detracted from performance in the second quarter with the stock down 3.7%. The decline was driven by multiple compression (its P/E was down 8.5%¹¹) rather than any deterioration in the underlying business or fundamental outlook. Shopify continued to post healthy growth in gross merchandise volume and revenue, which were up 30% and 32% year-on-year, respectively. Instead, the pressure reflected investor concerns about the company's long-term positioning in a future state of e-commerce that may rely more heavily on AI-driven applications than traditional websites. We view those concerns as misplaced and see Shopify as an AI winner. Two decades of proprietary data across millions of merchants provide Shopify with a strong foundation for AI tools that improve merchant outcomes. Recent product releases also embed the platform more deeply within the emerging agentic commerce ecosystem while creating new monetization opportunities. We continue to believe that Shopify is the category-defining platform for modern commerce, benefiting from durable secular growth in digital retail, an expanding suite of merchant solutions, improving free cash flow, and a widening competitive moat.

Coupang, Inc., Korea's largest e-commerce platform, detracted from performance with shares down 7.7%. The stock came under pressure following first-quarter results, where in-line revenue was overshadowed by softer second-quarter guidance as capacity and supply chain investments made ahead of Coupang’s 2025 data breach weighed on margins while customer volumes recovered. Sentiment was further weighed down by a record KRW 624.7 billion (about US $430 million) privacy fine stemming from an investigation into the breach, while a rotation of fast money into AI and semiconductor names added to the weakness. Despite these headwinds, our conviction remains intact. We view the margin pressure as temporary, and the fine removes a key overhang and reinforces our belief that the breach does not reflect a structural loss of market share. By the end of April, Coupang recovered roughly 80% of the post-breach decline in WOW Membership (its paid subscription program), with returning members resuming prior spending levels. We continue to view Coupang as a competitively advantaged e-commerce business gaining share in its core market while scaling Taiwan operations.

The Fund is constructed on a bottom-up basis with the quality of ideas and level of conviction playing the most significant role in determining the size of each investment. Sector weights tend to be an outcome of the portfolio construction process and are not meant to indicate a positive or a negative view.

As of June 30, 2026, the top 10 holdings represented 67.5% of the Fund’s net assets, and the top 20 represented 93.1%. We exited the quarter with 27 investments, one more than we had at the end of last quarter.

IT and Communication Services represented 75.0% of the Fund’s net assets, while the remaining 25.0% was invested in Consumer Discretionary, Health Care, and Financials.

During the second quarter, we initiated a new investment in the fast-inference semiconductor company, Cerebras. We also took advantage of stock price volatility to continue adding to our newer position in the electrical component supplier Amphenol, and also added to the pharmaceutical giant Eli Lilly.

To fund these purchases, we slightly reduced 12 existing positions.

After following Cerebras Systems Inc. for years, meeting management several times, and touring its facility during our most recent Baron research trip to Silicon Valley, we participated in the company’s IPO during the quarter. Cerebras is a semiconductor company focused on fast AI inference – i.e., producing fast tokens. As inference evolves from one-shot responses to reasoning and agentic workflows, many internal tokens are generated for every external, customer-facing token. This shifts the primary bottleneck from raw compute, measured in FLOPs, to AI-factory throughput: the total number of tokens produced per second and the speed delivered to each user. Speed matters because latency compounds at every step of an agentic workflow; the faster tokens are generated, the more useful and attractive the AI agent becomes. As discussed earlier in the letter, we believe the AI inference S-curve remains very early. Founded in 2016 by Andrew Feldman, Cerebras is built specifically to address this fast-inference opportunity.

Cerebras’ Wafer-Scale Engine (WSE) is an AI accelerator the size of an entire silicon wafer, with substantial area dedicated to SRAM – the fastest available memory. The architecture is designed to keep as many calculations on-wafer as possible, going off-wafer only when necessary, which enables much higher bandwidth and as a result – faster token generation. The WSE-3 is 58 times larger than a leading GPU chip and, by keeping the model on-chip, can deliver inference up to 15 times faster than leading GPU-based solutions across various open-source models. Commercial validation includes a multi-year, 750MW agreement with OpenAI valued at more than $20 billion, with optionality for an additional 1.25GW; a partnership with Amazon to bring Cerebras’ fast inference to AWS; and a second-quarter IPO that raised $6.4 billion. We believe Cerebras’ moat is durable because wafer-scale computing is difficult to replicate: the company has spent nearly a decade solving architecture, packaging, yield, and software-engineering challenges and remains the only company to commercialize this approach at scale. As agentic AI adoption grows and latency becomes increasingly important, Cerebras’ solution should become more valuable to customers.

We continued building our Amphenol Corporation position in the second quarter after initiating it in the first quarter (see the Q1 letter for a full write-up). As a reminder, Amphenol is a leading provider of mission critical interconnect, sensor, and antenna solutions across a diverse set of end markets. The stock continues to be volatile as investor narratives shift around the relative value of copper versus optical architectures for AI. We continue to believe the market underestimates Amphenol’s long-standing ability to innovate and adapt across cycles and end markets. Fundamentally, the company reported strong first quarter results, with 33% year-over-year organic growth and record orders of $9.4 billion. With book-to-bill well above 1.0 times, these results suggest a clear growth trajectory ahead.

We added to Eli Lilly & Company in the second quarter as we believe it remains a compelling big idea. Eli Lilly is best known for its GIP/GLP-1 medications for diabetes and obesity. Although awareness and adoption of these medications has grown rapidly in the past few years, the market remains vastly underpenetrated. In the U.S. alone, there are roughly 135 million obese or diabetic patients who would qualify for GLP-1 drugs, yet less than 15% are on a GLP-1 drug today. Globally, over one billion people could benefit from GLP-1 therapy, and international markets are even less penetrated. We think these drugs will continue to launch well as awareness and insurance coverage grows, and as Lilly generates more data to show the dramatic impact GLP-1 drugs can have on other medical comorbidities. We think that these drugs will become the standard of care and a $180 billion-plus category.

We view Lilly as a clear leader in GLP-1s. Zepbound/Mounjaro appears to be the most effective injectable treatment currently available, while Orforglipron is positioned as the most convenient oral option. Lilly’s U.S. market share has risen from below 50% at the start of 2025 to more than 60% today. Beyond Zepbound and Orforglipron, we believe Lilly has the strongest next-generation obesity pipeline, led by Retatrutide, a high-efficacy triple-agonist injectable, and Eloralintide, an amylin agonist that demonstrated Zepbound-like efficacy with excellent tolerability and could likely be combined with Zepbound. Lilly’s incretin franchise also has meaningful optionality beyond obesity and type 2 diabetes. Zepbound has already shown efficacy in obstructive sleep apnea and heart failure, and we believe it could also prove useful in fatty liver disease and cardiovascular disease. Lilly is also studying brenipatide, a brain-penetrant GIP/GLP-1 agonist, in alcohol use disorder, major depressive disorder, opioid use disorder, schizophrenia, tobacco use disorder, bipolar disorder, and asthma. We also see potential use cases across autoimmune conditions and even in preventing inflammation-related cancers.

Beyond obesity and GLP-1s, Lilly is building a highly diversified portfolio, reinforcing its position as one of the fastest-growing pharmaceutical companies even excluding its GLP-1 franchise. The company has made meaningful pipeline progress, with promising programs in early Alzheimer’s, breast cancer, and cardiology that could each become $10 billion-plus opportunities over time. Management is also using Lilly’s substantial cash flow to pursue aggressive, strategic business development that can further extend long-term growth. Year to date, Lilly has announced more than 10 strategic deals totaling over $25 billion in value. While most target early-stage platforms for long-term pipeline growth, the Centessa acquisition stands out as a nearer-term opportunity. The $6.3 billion upfront deal secures a de-risked potential blockbuster therapy for sleep and wake disorders slated for a 2028 launch, with additional upside in sleep apnea. We would also highlight Lilly’s landmark $1 billion co-innovation lab with NVIDIA, which is designed to virtually simulate complex molecular dynamics in silico before beginning physical trials and should help accelerate early-stage drug discovery.

“It’s tough to make predictions, especially about the future.” 
Yogi Berra

As we begin the second half of 2026, we find ourselves in an environment where headlines are dominated by geopolitics, shifting regulatory tides, fear and excitement about AI, and Truth Social posts. However, as long-term investors, we remain purposefully indifferent to the prognostications that occupy so much of the financial media’s attention. We do not know where or how the market will trade a month or a quarter from now, nor do we believe that such knowledge is necessary to achieve our long-term goals. Our focus remains squarely on identifying and investing in high quality, competitively advantaged, well-managed businesses for the long term.

Rumors and noise are constant – copper will be disrupted by optics! Amphenol’s stock falls 20% in the first three weeks of May. Wait... actually, CPO (co-packaged optics) is delayed. The stock bounces back 48% in the last 10 days of May and June! NVIDIA’s next generation architecture is delayed, data centers are delayed, tokenmaxxing¹², Lilly’s scripts have declined last week, Meta is building a cloud business. AI stocks sell off. Then IBM pre-releases earnings disclosing customer budgets have shifted to server purchases related to AI – and the AI trade is back on! And so it goes...

We laser focus on understanding the drivers of businesses’ economic value creation and on separating the signal from the noise. Understanding companies’ competitive positioning and duration of growth is the key to our process and our ability to generate alpha over long periods of time.

Each quarter, we analyze changes in the Fund’s weighted average multiple and consensus expectations for 2026 revenues and operating income¹³. In the second quarter, the Fund’s weighted average multiple expanded by 12.2%, though it remains down 4.9% year to date. Fundamentals also improved as weighted average revenue expectations rose 3.5% during the quarter and 8.7% year to date, while operating income expectations increased 5.1% in the quarter and 9.8% year to date. As a result, more than 100% of the Fund’s year-to-date return has been driven by growth in fundamentals rather than multiple expansion, which bodes well for prospective returns. We also compared current valuation multiples for our companies with their average multiples over the past five years. At quarter-end, the portfolio’s weighted average multiple was 10.5% below its five-year average.

Every day we live and invest in an uncertain world. Well-known conditions and widely anticipated events, such as Federal Reserve rate changes, ongoing trade disputes, government shutdowns, and the unpredictable behavior of important politicians the world over, are shrugged off by the financial markets one day and seem to drive them up or down the next. We often find it difficult to know why market participants do what they do over the short term. The constant challenges we face are real and serious, with clearly uncertain outcomes. History would suggest that most will prove passing or manageable. The business of capital allocation (or investing) is the business of taking risk, managing uncertainty, and taking advantage of the long-term opportunities that those risks and uncertainties create.

We are optimistic about the long-term prospects of the companies in which we are invested and continue to search for new ideas and investment opportunities while remaining patient and investing only when we believe target companies are trading at attractive prices relative to their intrinsic values.

We thank you for your continued trust and for being our partners on this journey.

Sincerely,