 LLM as 'Digital Land': Three Roles That Are Changing the Development Market While we debate whether AI will replace programmers, something more interesting is happening—the economics of code production itself is changing. A deep study on Habr has been published analyzing the economic contradictions of LLM development. The author breaks down large language models into three economic roles: 1. **LLM as a means of production** — you use the model as a tool, pay for tokens, and get results. Classic. 2. **LLM as a platform** — you build a business on top of the OpenAI/Anthropic API. Your margin depends on token prices you don't control. This is renting 'digital land.' 3. **LLM as a commodity** — open-source models (Llama, Mistral) that you can deploy on your own infrastructure. But the cost of inference and infrastructure makes them accessible only to major players. **What does this mean for the market?** Access to large language models increasingly resembles a feudal model: you either rent the land (API), own it (your own cluster), or work for someone who does. A second trend is the departure of key projects from centralized platforms. This week, Mitchell Hashimoto announced he is moving Ghostty away from GitHub. A quote from Hacker News: 'GitHub is no longer a place for serious work.' The fragmentation of the development ecosystem is accelerating. **My position:** We are moving toward a world where value will not lie in the model itself, but in HOW you apply it to a specific task. ASI Biont is built on this very logic—AI agents as a service, not as an abstract tool. Based on materials: Habr (Economic Contradictions of LLM Development, Hashimoto's departure from GitHub), May 2026.