Why the AI Boom Is Just Getting Started
Investor Alex from Whale Rock Capital discusses their high-conviction investment in Anthropic, explaining why AI represents an unprecedented 'L-curve' of adoption rather than a typical S-curve. He outlines their framework of S-curves, competitive advantages, and underappreciated earnings power, while detailing the decommoditization of hardware infrastructure and concerns about traditional enterprise software companies.
Summary
The conversation centers on Whale Rock Capital's investment thesis around AI, with a particular focus on their highest-conviction position in Anthropic. After ChatGPT launched in November 2022, Whale Rock conducted a deep dive and initially focused on chips and infrastructure, reasoning that compute demand would be certain regardless of which AI companies won. Over time, they developed conviction that the foundational model layer would consolidate into an oligopoly of three players — Anthropic, OpenAI, and Google/Gemini — similar to how cloud computing consolidated around AWS, Azure, and GCP.
The key inflection point for Anthropic came with the explosion of AI coding tools in 2025. When Claude Code went largely agentic and Andrej Karpathy publicly stated that AI now writes 80% of his code (a reversal from the prior year's 20%), the investor recognized a massive market opportunity. With approximately 20 million coders worldwide potentially spending $20,000–$30,000 per year on tokens, the coding market alone represents a ~$500 billion opportunity. Whale Rock invested at a $180 billion valuation after preparing a 90-page deck using Claude Code to analyze the competitive landscape.
The S-curve framework is central to Whale Rock's investment philosophy, combined with identifying competitive advantages and underappreciated earnings power. The investor explains that technology adoption follows predictable S-curve patterns, but the key variables are: when barriers to adoption are removed (triggering the inflection), how tall the curve is (determining when to sell), and the slope of adoption (B2B is slower like a dishwasher requiring installation; consumer can be fast like radio). AI is described as an 'L-curve' — straight up — because unlike cloud/SaaS, users simply open a browser and it's there, with enterprise penetration still under 1%.
On hardware and chips, the investor argues we are in a 'renaissance of decommoditization.' AI workloads are growing 10x annually and pushing hardware to physical limits, creating innovation cycles across every layer — from high-bandwidth memory to PCBs requiring 40 layers instead of 10, to liquid cooling, to fiber optics. Companies like Celestica (AI server manufacturing), Corning (fiber), and Elite Materials (copper clad laminate) are highlighted as having transformed from commodity businesses into critical infrastructure suppliers with strong competitive positions and rapidly rising ASPs and margins.
Conversely, traditional enterprise software companies are described as being in serious trouble. Whale Rock sold almost all application software and was net short entering the year. CIO budget priorities have shifted toward AI tokens with faster ROI, seat-based software faces pressure from AI reducing headcount, and the threat of AI-native competitors building replacements is real. The one potential positive for incumbent software is if AI agents end up operating within existing systems of record (like CRM or Slack), which could reinforce their positions.
The investor also discusses how they access private markets despite being primarily a public markets firm — through deep due diligence, building relationships over time, and demonstrating long-term ownership commitment (as opposed to VC sellers). He describes the Whale Rock 'learning machine' as 2,500–3,000 face-to-face management meetings per year, compounding knowledge over 20 years, and using a scuttlebutt approach from Philip Fisher. The firm has evolved its product offerings from a long-short fund to include long-only, hybrid public/private, and a new Mega Cap Tech fund targeting the top 30 global market caps.
Key Insights
- The investor argues that enterprise AI application penetration is less than 1%, and unlike typical S-curves, AI adoption looks like an 'L-curve' — straight up — because users simply open a browser and access it, removing the integration friction that slowed cloud/SaaS adoption.
- Andrej Karpathy's public reversal — stating AI now writes 80% of his code versus 20% the prior year — is cited as a key signal that Claude Code reached true agentic capability, unlocking a ~$500 billion coding market at $20-30K per developer per year across 20 million coders.
- The investor describes AI hardware as undergoing 'decommoditization' — AI workloads growing 10x annually push every component (PCBs from 10 to 40 layers, HBM memory stacked 10 chips high, liquid cooling) to physical limits, transforming formerly commodity suppliers into critical infrastructure with multi-year design partnerships and rising ASPs.
- Whale Rock sold nearly all enterprise application software and was net short entering 2025, arguing that traditional software sits lower on CIO priority lists, faces budget pressure from AI token spending, can no longer easily raise prices annually, and risks disruption from AI-native competitors — even if full replacement takes years.
- The investor explains that B2B technology S-curves are inherently slower than consumer ones — analogized to a dishwasher needing to be 'plugged into the house' — but AI is an exception because enterprise users access it instantly through a browser, which is why adoption is accelerating faster than cloud or SaaS did.
Topics
Transcript
[0:00] When you get the right part of the S-curve, you get exponential unit growth. If you have a very strong business model, your earnings don't grow linearly, they grow exponentially. You know, the world doesn't think exponentially. Very few people believe you can accurately predict 2 3 4 years out. But if you follow and understand the Scurve and you you know the moes and you know how to model, you really can uh predict these these great things. the enterprise AI or enterprise application [0:31] AI market is less than 1% penetrated and we've never seen, you know, we talk about S-curves, we call this an L curve, just straight up. Alex, you were saying that your highest…
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