Back Research Notes Vibecoding is the ChatGPT Moment for Code: Why the Great Software Re-Rating of 2025–2030 Has Already Begun Published on December 8, 2025 By Jordi Visser Key Executive Summary Points for Allocators Software scarcity is increasingly likely to end; code is becoming a commodity. Vibecoding and AI agents are pushing the marginal cost of software creation toward zero. The more probable regime ahead is one where scarcity and therefore value capture shifts to power, grid infrastructure, HBM, electrical parts and components, packaging, cooling, and energized land. Portfolio exposures are misaligned with the likely emerging regime. MSCI World / ACWI remain heavily concentrated in long-duration software moats built on expensive, slow-to-replicate human code. Those moats appear increasingly at risk as AI accelerates competition and shortens product cycles. The growth factor is gradually migrating from software to infrastructure. Hyperscalers are behaving more like industrial companies, driving multi-year demand for electrical equipment, advanced semiconductors, memory, thermal systems, and power generation . The balance of probability now favors growth re-attaching to atoms rather than bits. Horizontal SaaS faces a rising probability of structural margin pressure. Vibecoding erodes feature moats, AI agents replace seats, switching costs fall, and inference spend enters COGS. These forces are increasingly likely to compress margins and pull multiples toward historical software ranges. Allocation implication: Maintain exposure to durable digital franchises, but tilt allocations toward AI infrastructure bottlenecks that benefit under most forward scenarios: memory (HBM), advanced packaging, transformers/switchgear, liquid cooling, data-center REITs, and advantaged utilities/IPPs. Key falsifiers to monitor: SaaS moats remain stickier than expected; power and grid constraints ease materially; AI workload growth slows; or regulation meaningfully restricts data-center expansion. Introduction: When Human Keystrokes Stop Being Scarce On a cold February morning in 2025, Andrej Karpathy, the former Director of AI at Tesla and a founding member of OpenAI, published a short manifesto that landed like ChatGPT had in November 2022. He called the new paradigm vibecoding : you describe what you want in natural language, the machine writes the code, runs the tests, deploys it, and you “forget that the code even exists.” For the first time in history, syntax is becoming a zero-marginal-cost commodity. What ChatGPT began to do to white-collar knowledge work in 2023, vibecoding is now doing to software creation in 2025–2030. The scarcity premium that has defined global equity indices for fifteen years is collapsing. For anyone benchmarked to MSCI World or ACWI, this is not a curiosity about developer productivity tools. It is a regime shift in what the benchmark actually owns. From 2007 to 2024, cap-weighted indices became a concentrated bet on intangible software moats: high gross margins, near-zero capital intensity, and decades-long cash-flow duration. The top-10 holdings’ weight doubled to >26%, and the IT sector share rose from the mid-teens to the high-twenties while Energy and Materials shrank to historic lows. In retrospect, a large part of what we labeled American exceptionalism and dollar dominance was, at the index level, a two-decade equity moat built on the scarcity of code In my previous note, From Bits to Atoms , I argued that AI is moving from “thinking” to “acting” via Vision-Language-Action (VLA) models, shifting value to sensors and actuators. This paper tackles the other side of that coin: what happens to the software itself? As AI gains a physical body, it is simultaneously commoditizing its own digital mind. This paper’s core thesis is simple and brutal: Intangible code is becoming abundant and commoditized. Tangible infrastructure : power, transformers, cooling water, high-bandwidth memory, electrical parts and components, land, permits and many more are becoming the binding constraint on intelligence at scale. The result is the Great Software Re-Rating of 2025–2030 : multiples compress for large parts of the application layer while valuation power migrates to the physical stack that cannot be vibecoded away. The Old Regime: Bits Ate Atoms (2007–2024) From the iPhone launch through the end of 2024, the dominant equity narrative was “bits over atoms.” The benchmark math told the story in one chart: the alligator jaws between digital and physical sectors opened wider every year. MSCI World IT + Communication Services weight rose from ~20% in 2007 to >35% by late 2024. Energy fell from ~10% to <5%, Materials from ~8% to ~4%. Index concentration exploded: the top-10 constituents went from 10.5% of the index in 2017 to >26% in 2024. Investors paid 10–100× sales and 40–120× earnings for best-in-class software franchises because the underlying assumption was durable: replicating a Snowflake, ServiceNow, or CrowdStrike required armies of engineers and many years. The benchmark became implicitly long “expensive human keystrokes.” The “Growth” Trap and the Death of Asset-Light For fifteen years, “Growth Investing” was synonymous with “Asset-Light.” The algorithm was simple: avoid factories, avoid inventory, and buy zero-marginal-cost code. This created a dangerous blind spot: growth managers systematically ignored physical industries, assuming they were all “Value traps.” But the “Asset-Light” era is over, even for the Hyperscalers. The Magnificent 7 are currently engaging in the largest capital expenditure cycle in human history. Microsoft, Google, Meta, and Amazon are effectively transforming from software companies into industrial energy utilities. They are pouring hundreds of billions into copper, concrete, custom silicon, and power generation. If the kings of the asset-light era are pivoting to become “kings of concrete,” the investment framework must change. The “Growth Factor” is decoupling from “Software” and re-attaching to “Industry.” True growth, accelerating revenue and pricing power, is now found in the assets that rust and hum, not just the ones that compute. Managers who refuse to buy physical assets will be structurally short the actual growth of the next decade. Vibecoding: From Scarce Syntax to Cheap Intent Vibecoding is not just better autocomplete. It is a phase-change in the abstraction layer of programming. You now specify semantic intent (“build a warehouse inventory system with RFID integration, Stripe billing, and Slack alerts”), and multi-agent systems (Cursor, Loveable, Windsurf, Claude Code, Replit Agent, etc.) generate, test, debug, and deploy production-grade code in hours or days. The constrained resource is no longer fluency in Python or TypeScript, it is high-level architecture and product taste. Real-world evidence as of December 2025: Stack Overflow 2025 survey: 78% of professional developers use AI coding tools daily. GitHub Copilot controlled studies: 55% task completion speedup; internal Microsoft data claims 30–50% across the board. Y Combinator Summer 2025 batch: >25% of companies shipped with >90% AI-generated code. The Weekend Founder: Stories are now routine of production CRMs + Stripe + Resend + Vercel built in <60 hours for <$3,000 in compute. The economic consequence is the rise of disposable software and shadow IT 2.0 . Marketing, HR, and operations teams are vibecoding internal tools rather than paying $20–$200 per seat per month. Software is shifting from durable capital good to cheap consumable. How the Moats Actually Erode The Universal Translator Effect The single most dangerous misconception is that “data gravity” will save incumbents. It will not. Historically, migrating off Salesforce or SAP was a multi-year, eight-figure nightmare of schema mapping and data loss. AI agents now act as a universal translator : they ingest legacy exports, infer schemas, clean data, and rebuild in a new stack in h