software-economics

3 items

Ramp Economics Lab · 2026-03-20 2026-03-20-w2

How Did Anthropic Do It? (Ramp AI Index + Winter 2026 Business Spending Report)

Anthropic's 24.4% enterprise adoption and 70% first-time win rate against OpenAI matter less than the mechanism behind them: the more expensive, supply-constrained option is growing fastest in a market that commoditization theory predicted would race to the bottom. The buried signal is the falsification test embedded in the data: when Anthropic's compute constraints ease, either growth sustains and it's a product moat, or it collapses and scarcity was doing the work all along. That distinction connects directly to the MIT CSAIL finding: if frontier labs can't reproduce their own compute efficiency, supply constraint isn't an accident of capacity planning; it could be a structural feature of how frontier models get built. The Morningstar review adds the third leg: CrowdStrike and Cloudflare received the week's only moat upgrades because AI expands the attack surface that security infrastructure must handle; the same logic that makes a rate-limited, reliability-signaling AI product more defensible than a cheaper, abundant one. Scarcity functioning as a luxury signal in enterprise software is genuinely new terrain, and the companies that understand it as a product design choice rather than a supply accident will compound the advantage long after the GPU shortage ends.

Anil Dash 2026-03-20-1

What Do Coders Do After AI?

AI coding tools create asymmetric displacement: they eliminate the career-coder's entire role function (paradigm replacement, not task automation) while shifting identity-coders from writing code to specifying it. But the real unexamined move is the distribution bottleneck: code getting 10,000x cheaper means surplus flows to platform gatekeepers, not indie builders. The strongest unexplored thread is the reliability counter-trend — cheap generated slop creates demand for verification and quality tooling as the new scarce layer.

Ramp Economics Lab 2026-03-20-3

How Did Anthropic Do It? (Ramp AI Index + Winter 2026 Business Spending Report)

The strongest signal in Ramp's transaction data isn't Anthropic's 24.4% adoption or the 70% first-time win rate over OpenAI: it's that the more expensive, supply-constrained product is growing fastest. Commoditization theory predicted that comparable models at falling inference costs would race to the bottom; instead, businesses are paying a premium for the rate-limited option while the cheaper alternative declines 1.5% in a single month. Scarcity functioning as a luxury signal in enterprise software is genuinely new, and the falsification test is clean: when Anthropic's compute constraints disappear, either the growth sustains (product moat) or it doesn't (scarcity moat).