The a16z Show

Meta Platforms (META) represents a high-risk, high-reward investment based on its massive bet that AR/VR will become the next major computing platform. For a proven cryptocurrency investment, look to infrastructure providers like Coinbase (COIN) that are central to the rapidly growing stablecoin payment ecosystem. Directly investing in Bitcoin (BTC) can serve as a "digital gold" holding, while Ethereum (ETH) provides exposure to the leading smart contract platform. Chinese e-commerce companies like PDD Holdings (PDD) offer hyper-growth potential but come with significant and unpredictable geopolitical risks. As the AI sector is still in its early stages, prioritize investing in established companies that are effectively integrating AI to amplify their expert workforce.

The current AI boom is a foundational technology shift, but investors should expect volatility without a systemic collapse like the dot-com bust. Focus on the "picks and shovels" of AI, specifically companies involved in data center capacity and GPUs, which are receiving the bulk of investment. Meta Platforms (META) is a prime example of a financially strong company making a massive, long-term bet on AI, positioning it as a core holding. Adopt a long-term perspective, as this technology wave is expected to create new iconic companies, much like Amazon and Netflix emerged from the internet era. Prioritize investing in companies with strong, cash-rich balance sheets, as this fundamental strength differentiates the current cycle from past speculative bubbles.

The massive addressable market for GLP-1 drugs like Ozempic presents a significant investment opportunity, with a secondary play in companies providing protein and supplements to users. A major emerging theme is the shift to preventative healthcare, creating a bullish case for wellness brands like Peloton (PTON) that are integrating with platforms allowing pre-tax health spending. Conversely, investors should be cautious of agricultural chemical companies like Bayer due to massive and ongoing litigation risk related to its glyphosate products. This also signals long-term structural risk for "Big Food" companies heavily reliant on subsidized ingredients like high-fructose corn syrup and soybean oil. The psychedelic medicine sector is also highlighted as a potentially undervalued and high-growth area for investors focused on mental health solutions.

Consider investing in the disruptive defense theme by looking for public companies that are agile and software-focused, similar to the private innovator Anduril. Meta (META) offers a direct, high-risk investment into the future of the metaverse, with its Quest 2 sales demonstrating tangible market traction. Apple's (AAPL) high-end strategy in the VR/AR space is viewed as a promising long-term approach that validates the entire sector. Nvidia (NVDA) is presented as a core foundational investment, having proven to be the essential "picks and shovels" provider for major tech waves like AI. Finally, the insights reinforce a long-term conviction in Bitcoin (BTC) and the growing utility of stablecoins for modernizing global finance.

Consider Goldman Sachs (GS) as a long-term investment, as management has a clear strategy to scale its business and leverage AI for significant efficiency gains. Invest in the "picks and shovels" of the AI sector, such as GPU makers and cloud providers, who are poised to benefit from the industry's massive capital spending. Expect a record year for Mergers & Acquisitions (M&A), creating potential upside for well-positioned companies that could become acquisition targets. A reopening of the IPO market will also present new opportunities to invest in high-growth technology companies. For higher-risk portfolios, monitor US legislative progress on cryptocurrency, as clear regulations could serve as a massive catalyst for the asset class.

The AI revolution is creating a major "picks and shovels" investment opportunity in the software infrastructure and developer tool space. Consider Cloudflare (NET) as it is developing tools to help websites monetize the growing traffic from AI agents, creating a potential new revenue stream. Investors should also evaluate SaaS companies like HubSpot (HUBS) that are strategically focusing on "Agent Experience" (AX) to embed themselves in future AI-driven workflows. When evaluating companies, prioritize those that make their platforms easy for AI agents to use and build upon. This focus on enabling a new, broader class of AI-powered developers is a key indicator of long-term growth potential.

The primary investment opportunity in Artificial Intelligence is not just the model builders, but the companies effectively harnessing AI to disrupt industries and boost productivity. While foundational players like Google (GOOGL) and Meta (META) are central, consider a diversified approach as competition is fierce and leadership is fluid. Be cautious of incumbent software companies like Adobe (ADBE), which face significant risk from AI-native startups creating entirely new workflows. Look for opportunities in the EdTech sector, which is set for massive disruption as AI enables personalized tutoring at scale. The long-term trend favors platforms that empower the "super-empowered individual," a concept first demonstrated by decentralized networks like Bitcoin (BTC) and Ethereum (ETH).

Consider Bitcoin (BTC) a foundational, long-term holding as it underpins the future of digital economies and network states. As AI makes online content less trustworthy, invest in "proof of human" projects like WorldCoin (WLD) that verify real identity. Key infrastructure opportunities exist in high-performance blockchains like Solana (SOL) and essential usability services like ENS. Finally, be cautious of companies incorporated in jurisdictions like Delaware, as major venture firms are citing rising legal risks and moving to pro-growth states like Nevada and **

Consider investing in pharmaceutical giants like Novo Nordisk (NVO) and Eli Lilly (LLY), as the use of GLP-1 weight-loss drugs is expected to more than double. The upcoming launch of a pill version of Wegovy is a key catalyst that could significantly accelerate adoption and growth. The diagnostics, screening, and wearables sector is another high-growth area to watch, driven by consumer demand for proactive health monitoring. A potential new FDA category for "digital health screeners" would be a massive tailwind for companies in this space. Finally, be cautious of smaller health insurance companies as consumers shift towards a cash-pay system, creating opportunities for companies that offer price transparency and direct-to-consumer services.

The massive AI infrastructure spending by tech giants like Google (GOOGL), Meta (META), Amazon (AMZN), and Microsoft (MSFT) creates a primary investment opportunity in their supply chain. Consider investing in the "picks and shovels" of this build-out, such as semiconductor and data center companies that directly benefit from this capital expenditure. The next critical bottleneck for AI growth is projected to be energy, making energy producers a compelling long-term investment. Within the energy sector, companies focused on nuclear power are highlighted as particularly well-positioned to meet the immense power demands of data centers. Another key investment theme is American Dynamism, focusing on companies like Palantir (PLTR) that are building critical technology for defense and aerospace.

The most significant investment opportunity is in the AI Infrastructure & Developer Tools space, which provides the essential "picks and shovels" for the AI revolution. Microsoft (MSFT) is a top pick due to its impressive operational speed and rapid adoption of cutting-edge AI tools, signaling strong innovation. Similarly, Coinbase (COIN) demonstrates technological leadership by embracing advanced developer platforms, indicating a competitive advantage. Conversely, investors should be cautious with incumbents like Confluent (CFLT), as it faces increasing disruption from more agile, AI-native startups. The core strategy is to favor companies building the critical infrastructure that enables AI agents to function effectively.

The most compelling investment opportunity in AI is the "picks and shovels" theme, which focuses on companies providing foundational infrastructure. NVIDIA (NVDA) is the highest conviction opportunity, as its GPUs are the essential hardware for running increasingly complex AI workloads. Major cloud providers like Amazon (AMZN) and Google (GOOGL) are also key beneficiaries, capturing the massive spending on scalable AI computing. This trend is durable because the challenges in AI are becoming more difficult, ensuring long-term demand for these core infrastructure providers. Investors should consider these companies as they are positioned to profit from the growth of the entire AI ecosystem.

The AI build-out is creating a massive, long-term demand for infrastructure, presenting a core investment opportunity in the sector's foundational layers. Nvidia (NVDA) remains a central, high-conviction investment as it directly supplies the essential hardware for this technological shift. Within software, consider ServiceNow (NOW), which is successfully adapting to the AI era and outperforming peers. Be cautious with legacy SaaS providers like Salesforce (CRM), as they face significant disruption risk if they fail to innovate their user experience. Investors should also look at companies providing essential data centers, networking, and power to support the accelerating demand for AI.

The most significant growth in AI may come from the application layer and developer tooling that enable new agent-based workflows, rather than from the large model creators alone. Investors should focus on companies building sophisticated agent architectures that can intelligently route tasks to the most efficient AI model for the job. Be aware that current US policy is creating a dependency risk on foreign open-source models, presenting a headwind for domestic innovation. A key catalyst would be any new legal safe harbors for US open-source AI development, which could unlock substantial value. In the meantime, large incumbents with deep legal resources may hold a competitive advantage in navigating the complex regulatory landscape.

Focus on the AI application layer, where software solves specific business problems, as this is where the most durable investment opportunities lie. Consider investing in established software leaders like Microsoft (MSFT), Adobe (ADBE), and Workday (WDAY), which are poised to grow by upselling AI features to their massive customer bases. Intuit (INTU) is particularly well-positioned to monetize its QuickBooks users with new AI-powered services. Conversely, be cautious with traditional automation companies like UiPath (PATH), as they face significant disruption risk from newer AI-native competitors. The biggest long-term theme to watch is "Software Eating Labor", where AI begins to perform the jobs of human workers.

The most foundational AI investment is in the semiconductor companies designing the GPUs and specialized chips that power the entire industry's growth. A significant secondary opportunity exists in the "picks and shovels" of AI, which are the software tools and frameworks developers use to build applications. Prioritize companies creating this essential AI software stack, as they provide the structure needed to make powerful models from labs like OpenAI useful and reliable. This strategy focuses on the enabling infrastructure that captures value from the entire AI ecosystem's expansion. Ultimately, this approach benefits from overall AI adoption, regardless of which specific model or application wins in the long run.

The AI revolution is a long-term, generational investment theme, with a core focus on companies providing essential hardware like NVIDIA (NVDA). A key strategy is to invest in dominant, cloud-native software leaders such as Salesforce (CRM) and Workday (WDAY). These modern platforms are often projected to grow up to 10 times larger than the legacy companies they are displacing. This trend creates a significant long-term headwind for older tech giants like Oracle (ORCL) as they lose market share. The underlying thesis is that new technologies create their own demand, making their true market potential far larger than current models predict.

Consider investing in Toast (TOST), which is viewed as a top business due to its powerful model of bundling restaurant software with financial services. A bearish outlook is presented for Lending Club (LC), as it has been significantly outcompeted by its founder's new, more innovative company. When investing in the AI application layer, prioritize companies that have a proprietary data moat, as this is a more durable advantage than technology alone. This "walled garden" strategy is crucial because AI software without a data advantage can be easily replicated. While stable incumbents like Salesforce (CRM) and Workday (WDAY) benefit from high switching costs, they are vulnerable to losing new customers to more agile, AI-native startups.

The long-term artificial intelligence trend is justified by intense demand, with the best opportunities found in companies building specialized AI applications rather than just the largest foundation models. Despite its run-up, NVIDIA (NVDA) is viewed as having a justified valuation due to the real-world growth and strong demand for its hardware. Consider long-term investments in the American Dynamism theme, which targets technology companies modernizing critical sectors like defense, energy, and supply chains. A potential strategy is to invest in a portfolio of smaller, innovative AI companies, as they are prime acquisition targets for larger corporations seeking to adapt.

Focus on investing in software companies that create "hostages, not customers" by becoming deeply embedded in a business's operations. Vertical SaaS companies like Toast (TOST) are a prime example, serving as the indispensable operating system for the restaurant industry. Similarly, established "systems of record" like Workday (WDAY) are attractive due to their high switching costs, making them more resilient to AI disruption. The key is to find businesses whose products are so integrated into customer workflows that leaving is prohibitively expensive and risky. Be cautious of AI application companies that are merely "thin wrappers" over foundational models, as they lack a durable competitive advantage.