The generative AI sector is seeing notable activity in code generation startups, with some reaching high valuations despite profitability challenges.

In May, San Francisco-based Cursor raised US$900 million, hitting a US$10 billion valuation with backing from Thrive Capital, Andreessen Horowitz, and Accel.

Windsurf, creator of the AI coding tool Codeium, is reportedly in acquisition talks with OpenAI for US$3 billion.

Both companies allow users to automate coding tasks or create software using plain language commands.

Generative AI tools are transforming software development by automating repetitive work. Google’s CEO said over 30% of its code is AI-generated, saving 4,500 developer-years, while Microsoft reports 20-30% AI-generated code.

Despite growth, most code generation startups remain unprofitable and face high costs due to reliance on AI models from OpenAI and Anthropic.

Cursor and Windsurf generate revenue but operate with negative gross margins.

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🔗 Source: Reuters

🧠 Food for thought

1️⃣ Code generation follows historical pattern of specialized AI success

The current boom in AI coding tools reflects a persistent pattern in AI history: specialized applications create value before general ones.

While companies have struggled to find ROI from generative AI broadly, code generation has emerged as a clear success case, echoing how expert systems flourished in the 1980s by focusing on specific domains like medical diagnosis 12.

This pattern dates back to the earliest AI systems like Logic Theorist (1955), which succeeded by focusing narrowly on mathematical theorem proving rather than general intelligence 3.

The rapid revenue growth of coding startups ($100M for Cursor, $50M for Windsurf) demonstrates how domain-specific AI applications can achieve product-market fit faster than broader applications.

This specialization pattern explains why code generation has attracted such significant investment despite the uncertainty surrounding general AI applications.

2️⃣ AI is restructuring the software development labor market

The rise of code generation tools is fundamentally reshaping the economics and structure of software development teams.

Entry-level coding positions are declining as AI takes over repetitive programming tasks, with Signalfire’s data showing a clear drop in new hires with less than a year of experience.

This transformation mirrors patterns seen at major tech companies, with Google claiming AI saved “the equivalent of 4,500 developer-years” and Microsoft reporting that 20-30% of their code is now AI-generated.

Microsoft’s recent layoffs of 6,000 workers—with over 40% being software developers—provides concrete evidence of this structural shift in the industry.

This suggests a future where fewer junior developers are needed, but those with system design and architecture skills become more valuable—a pattern consistent with previous waves of automation in other industries 4.

3️⃣ The foundation model dependency creates strategic vulnerability

Most code generation startups face a fundamental business challenge: they rely on AI foundation models built by potential competitors.

Cursor, Windsurf, and other coding startups primarily use models from companies like Anthropic, which has reached $3 billion in annualized revenue partly from fees paid by these same startups 5.

This dependency creates a strategic vulnerability similar to app developers who rely on mobile platforms or cloud services controlled by tech giants.

In response, we’re seeing companies like Windsurf develop their first in-house AI models and Cursor hiring researchers to build frontier-level models—expensive defensive moves that reflect this existential concern.

The acquisition talks between OpenAI and Windsurf for $3 billion highlight another common outcome: startups being absorbed by the very platform companies they depend on, further consolidating the AI ecosystem 6.

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