The a16z Show

Investors should capitalize on the "SaaS-pocalypse" by targeting software companies with deep real-world moats, such as Navan, which remain defensible through complex global supply chains rather than just code. Focus on the shift from software engineering to physical infrastructure by investing in Compute (GPUs) and Energy (Electricity), as these are now the primary bottlenecks for AI growth. Avoid companies that only offer a cheaper UI or "rebuilt" versions of existing software, as AI can easily replicate these models; instead, look for "silver bricks" or niche enterprise workflows that large AI labs ignore. For long-term growth, prioritize firms and startups that centralize control to rapidly enter emerging sectors like Crypto, Bio, and American Dynamism. Monitor regulatory developments closely, as domestic investment in U.S. compute infrastructure is increasingly tied to geopolitical competition with China.

Investors should look toward Next-Gen System Integrators like Accenture (ACN) and Deloitte, which are positioned to capture a decades-long opportunity helping large enterprises modernize legacy data for AI readiness. Salesforce (CRM) remains a high-conviction play as it transitions to a "headless" architecture, turning AI agents into a massive new revenue stream through API usage and "machine user" licenses. Box (BOX) is a key beneficiary of the "agentic search" trend, enabling companies to finally extract immediate value from decades of unstructured internal documents and files. Despite fears of automation, the demand for software engineering and infrastructure is expected to explode, making GitHub (MSFT) and Anthropic-linked tools essential for managing the increasing volume of AI-generated code. To mitigate deployment risks, focus on the emerging AI Governance and Cybersecurity sectors, which provide the critical orchestration tools needed to manage "unruly" AI agents in professional environments.

Investors should prioritize Meta (META) for its superior distribution and ability to dominate the AI market by integrating "good enough" open-source models into its massive existing user base. For long-term growth, look toward the emerging Photonic Computing sector, specifically startups like Neurofos and Luminous, which offer a 1,000x performance leap over traditional silicon. Avoid the "patent cliff" risk in weight-loss leaders like Eli Lilly (LLY) and Novo Nordisk (NVO), as margins will collapse once these drugs face generic competition. Shift biotech focus toward high-value "hard pharma" targets like Rare Diseases and Alzheimer's, or high-conviction private plays like Neuralink that offer measurable economic utility. Be cautious of Apple (AAPL) and Google (GOOGL), as heavy reliance on stock buybacks and a lack of "dangerous" innovation may signal they are becoming the laggards of the tech sector.

Investors should prioritize Web3 infrastructure focusing on Identity, Authority, and Verification to combat the rise of AI-generated "slop" and misinformation.

High-conviction opportunities exist in the KYC (Know Your Customer) economy, specifically companies specializing in biometrics, digital signatures, and proof-of-personhood technologies.

Consider gaining exposure to the Farcaster ecosystem and decentralized social protocols that utilize on-chain data to provide verifiable, tamper-proof communication.

In the biotech sector, look for growth in longevity and performance-enhancing peptides, as the market shifts toward "biological optimization" and large-effect-size drugs.

For long-term infrastructure plays, monitor companies involved in subterranean construction and tunneling, as "z-axis" underground rights are projected to become as valuable as traditional real estate.

Investors should prioritize Alphabet (GOOGL) and platforms like Substack as they dominate the "Barbell" media trend, capturing both high-speed attention and high-value, ultra-long-form content. To combat the noise of the 2.5-day news cycle, professionals should integrate OpenAI’s ChatGPT or Anthropic’s Claude into their workflows to leverage "Deep Research" capabilities for a massive productivity edge. Be cautious of Legacy Media stocks, which are transitioning into declining cash-flow plays rather than growth assets as influence shifts toward decentralized "Practitioner Media." Monitor AI sentiment closely, as "Dark Money" influence operations can trigger sudden, artificial regulatory volatility that creates temporary buying or selling opportunities. Expect increased market swings driven by digital "moral panics," making sentiment analysis a critical tool for navigating the unpredictable "Current Thing" investment cycle.

Investors should prioritize Microsoft (MSFT) as the dominant incumbent in AI-assisted coding, though they must monitor if GitHub can successfully evolve its legacy "Pull Request" architecture for autonomous agents. Look for private equity or venture opportunities in GitButler, which is positioning itself as the "Agent-Native" successor to traditional version control by enabling parallel branching and machine-optimized outputs. A high-conviction theme is the shift toward Agent-UX infrastructure, specifically tools that help humans manage and review the massive data logs generated by AI coding agents. Focus on companies building spec-centric review platforms, as the primary value in software is shifting from manual coding to high-level technical writing and specification. Avoid developer tools that lack Git compatibility, as the industry remains anchored to this protocol despite the emergence of more flexible, AI-driven workflows.

Investors should prioritize Infrastructure and Foundation Models over traditional SaaS applications, as AI-driven cloning is rapidly eroding the competitive moats of software-only companies. Keep a close watch on OpenAI and Anthropic, as industry experts predict major model-layer companies may launch IPOs within the next 12 months. In the biotech sector, focus on Eli Lilly (LLY) and companies specializing in Peptide discovery, which are using AI to develop next-generation fat loss and longevity treatments. Consider diversifying into niche Consumer Hardware startups that solve "analog" problems, as physical products currently offer more defensibility against AI commoditization than digital tools. Finally, seek out companies that own Proprietary "Dark" Data—unwritten or private information not found on the public internet—as this is becoming the most valuable asset for training specialized AI.

Investors should view Alphabet Inc. (GOOGL) as a high-conviction play on the commercialization of autonomous driving as Waymo scales from research to a global service model. The upcoming launch of Gen 6 hardware is a critical catalyst, as it significantly reduces equipment costs to levels comparable with standard consumer vehicles, paving the way for sustainable profitability. With Waymo expanding operations to London and Tokyo this year, the company is demonstrating a "platform" approach that can be integrated into various vehicle models like the Hyundai Ioniq. Beyond the software, look for secondary opportunities in Real Estate Investment Trusts (REITs) that may benefit from the reclamation of urban parking space as autonomous fleets reduce the need for city-center vehicle storage. Avoid assuming that standard driver-assist technologies will easily transition to full autonomy; instead, prioritize companies like Alphabet that utilize tri-modal sensor stacks (LiDAR, Radar, and Cameras) to achieve the safety required for true Level 4/5 driving.

Investors seeking exposure to OpenAI’s market dominance should maintain core positions in Microsoft (MSFT), which remains the primary public vehicle for capturing the growth of generative AI agents. Apple (AAPL) is a high-conviction play as it transitions from reactive chatbots to an "ambient AI layer" integrated directly into iOS, making AI a proactive, background utility for billions of users. While OpenAI leads in scale, monitor Anthropic (Claude) as it gains market share among high-intent professionals by positioning itself as the "premium" and more human-like alternative. Beyond big tech, the most significant long-term opportunity lies in "Deflationary AI," specifically companies using automation to strip administrative costs out of the Healthcare and Education sectors. Avoid "AI for the sake of AI" and instead prioritize "Vertical AI" firms that apply large language models to solve specific, high-cost problems like revenue cycle management or educational tools.

Investors should prioritize Bitcoin (BTC) as a primary long-term hedge against fiat currency depreciation, following the strategy of holding hard assets over cash. The "Democratization of Software" theme suggests shifting focus from traditional tech giants to Micro-SaaS opportunities, specifically using tools like Replit to build niche automation apps. High-conviction sectors for new startups include Vertical AI for Education and Automated Deal Desks, which are currently seeing rapid revenue growth and high valuations. To find "alpha," investors should look for companies with proprietary data moats in biotech or specialized accounting, as basic AI models are becoming commoditized. For career-minded individuals, the most lucrative move is pivoting to a "Generalist Automator" role, using AI to eliminate manual workflows between platforms like Salesforce and Excel.

As the AI hardware trade evolves, investors should look beyond NVIDIA (NVDA) and pivot toward companies solving the next critical bottlenecks: high-bandwidth memory (RAM) and electrical grid infrastructure. The "AI trade" is increasingly becoming an energy play, making manufacturers of power transformers and grid modernization hardware high-conviction targets as data centers exhaust current electricity capacity. In the digital space, Bitcoin (BTC) and Ethereum (ETH) are positioned as essential infrastructure for AI agents that require "internet-native" money and cryptographic signatures to verify human identity against deepfakes. Conversely, exercise extreme caution with legacy SaaS companies that rely on customer lock-in, as AI-driven coding is eroding their competitive moats and long-term valuations. For those seeking durable software plays, prioritize companies like Navan that possess "real-world" moats, such as complex physical or legal partnerships that AI cannot easily replicate.

Investors should prioritize companies building Agentic frameworks and infrastructure, such as LangChain, which enable AI to execute autonomous tasks rather than just provide chat responses. To capitalize on the shift from human labor to "Token Budgets," look for growth in local model hosting and cost-effective hardware like the Mac Mini for "always-on" agent processing. The "Anti-Screen" movement presents a niche hardware opportunity in low-stimulation devices like the Daylight Computer or specialized E-Ink displays. In the EdTech sector, be bullish on platforms like Synthesis Math that provide "curriculum as a service" to facilitate the growing AI-enabled homeschooling market. Finally, focus on personal knowledge management tools like Obsidian that use Markdown files to provide the essential local context and privacy required for high-functioning personal agents.

Investors should maintain core positions in Apple (AAPL), as their vertical integration allows them to repurpose high-volume iPhone chips to dominate the $600–$1,000 laptop market with superior margins. Microsoft (MSFT) remains the essential "buy and hold" for enterprise stability, though its reliance on legacy compatibility creates a long-term performance gap compared to Apple’s "clean slate" ecosystem. For exposure to high-end gaming and AI development, NVIDIA (NVDA) is the high-conviction play due to the technical dominance of its CUDA APIs and the modular hardware requirements that Apple currently cannot meet. Avoid over-weighting Vision Pro or VR-specific stocks in the near term, as the market is shifting toward AR glasses which offer better mass-market utility. Monitor traditional PC manufacturers like Dell and HP, as they face increasing pressure from Apple’s ability to subsidize R&D through its massive mobile device scale.

Investors should prioritize Cybersecurity and Privacy sectors, specifically companies or protocols developing Zero-Knowledge Proofs and Fully Homomorphic Encryption (FHE) to secure decentralized data. While NVIDIA (NVDA) currently dominates, long-term growth is shifting toward "alternative hardware" and superconducting devices that offer 10,000x better energy efficiency. The increasing demand for "intelligence per watt" makes Nuclear and Fusion energy production essential long-term plays as AI scaling continues. Cryptocurrency remains the high-conviction asset for the "Web 4.0" era, serving as the native financial rail for Autonomous AI Agents to conduct commerce independently. Finally, look for opportunities in Biotechnology and AI-driven drug discovery, as the industry shifts toward a "Moore’s Law" for biology through Peptides and Life Extension technologies.

Investors should consider Box (BOX) as a foundational "system of record" play as it transitions from cloud storage to an agent-first platform that automates document processing. Focus on enterprise software leaders with deep, complex domain moats like SAP (SAP) and Workday (WDAY), as these "systems of record" are harder for AI to disrupt than simple interface-based apps. Monitor the shift from "per-seat" to usage-based pricing models across the SaaS sector, as companies move to capture value from high-frequency AI agent interactions. Anthropic is emerging as a primary challenger to OpenAI in the developer space, with its Claude tools significantly reducing the headcount required for complex engineering and marketing workflows. Prioritize investments in AI-native startups that can move faster than incumbents like J.P. Morgan, which face higher security hurdles and "prompt injection" risks during the current multi-year adoption window.

Investors should prioritize Zcash (ZEC) as a high-conviction play for private "digital cash," specifically monitoring the Tachyon scaling upgrade and the launch of the Zotel mobile wallet. For Bitcoin (BTC), maintain a long-term core position as it transitions into "institutional collateral," but consider diversifying into Tether Gold (XAUT) for digital exposure to physical assets. In the software sector, favor Obsidian over Notion for users seeking local data privacy, and avoid "vulnerable incumbents" like NetSuite that face disruption from AI-driven automation. Focus on the Biology and Healthcare sectors, which are poised for massive growth as AI synthesizes unstructured medical data to accelerate drug discovery. Finally, look for investment opportunities in deepfake detection and authentication services, as the market will soon place a high premium on "verified human" content.

Investors should prioritize Anthropic (Claude) over OpenAI for coding and agentic workflows, as its superior user experience and "lock-in" through customized skills are driving higher user retention. Roblox (RBLX) remains a high-conviction play in the gaming sector as it integrates AI-native creation tools that lower the barrier for user-generated content and complex experience building. Be cautious with low-end SaaS stocks like Calendly, as platforms like Replit and Lovable now allow "vibe coders" to build internal versions of these tools for free. The most significant emerging opportunity for 2025 is the Agent Stack, specifically infrastructure focusing on Model Context Protocol (MCP), agent identity, and automated payments. Look to shift capital toward high-margin, low-headcount startups, as AI agents now enable tiny teams to outperform traditional 10-person product organizations.

Investors should maintain high conviction in NVIDIA (NVDA), as hardware demand is expected to remain chronically undersupplied for the next 3–4 years while software improvements increase the value of existing chips. Focus on "Big Tech" leaders like Microsoft (MSFT), Amazon (AMZN), Google (GOOGL), and Meta (META), which are successfully converting massive GPU capital expenditures into immediate revenue. The next major growth phase lies in Agentic AI and Edge Inference, shifting value away from simple chatbots toward platforms that perform autonomous tasks on local devices. To capitalize on the "Grand Unification" of AI and crypto, look for Stablecoins and machine-to-machine payment protocols that allow AI agents to transact independently. Finally, hedge against AI-driven fraud by investing in "Proof of Human" identity technologies like World (WLD) and AI-driven cybersecurity tools designed for automated patching.

Investors should monitor World (WLD) as it shifts 90% of its operational focus to the U.S. market over the next year, transitioning from a theoretical project to a high-execution phase. The project’s "Proof of Human" iris-scanning technology creates a significant hardware moat, making it a primary play for the growing "Truth Tech" sector. Look for integration partnerships with platforms like Tinder (MTCH), Reddit, and X, as these companies will likely pay a premium for bot-filtering services to protect advertising revenue. High-value sectors like video conferencing and competitive gaming are immediate candidates for biometric verification to combat the 100x projected explosion in AI-driven fraud and deepfakes. Consider the long-term potential for World ID to modernize government social programs and Universal Basic Income (UBI) distribution by eliminating fraudulent middle layers.

Investors should consider Block, Inc. (SQ) as a high-conviction play on AI-driven margin expansion following its radical 40% workforce reduction. The company’s shift from a headcount-heavy model to an AI-agent operating system is designed to exponentially increase gross profit per employee across Square and Cash App. Monitor the rollout of MoneyBot and ManagerBot, as these autonomous tools aim to transform the user experience and create a "CFO in your pocket" for millions of users. Beyond SQ, prioritize founder-led tech companies that demonstrate the boldness to aggressively automate core engineering tasks rather than taking incremental approaches. Focus on firms with "hard moats" like physical hardware or massive distribution networks, as these remain protected from competitors who use AI to replicate software-only business models.