The LLM Landscape
The current state and future trajectory of LLMs.
The Benchmark and Evaluation Landscape
The evolution of LLM benchmarks from MMLU through SWE-bench and Chatbot Arena reflects a recurring cycle — new benchmark, rapid progress, saturation, replacement — exposing fundamental tensions between measurability and meaningful evaluation.
The API Economy: How LLMs Are Commercialized
The LLM API economy — pioneered by OpenAI in 2020 and transformed by DeepSeek’s cost revolution in 2025 — created a multi-billion-dollar industry where the fundamental business dynamics are shaped by relentless price deflation, tiered model strategies, and the competitive pressure of free open-weight alternatives.
AI Safety and Governance
The rapid scaling of LLM capabilities from 2023 to 2025 outpaced governance frameworks, producing a patchwork of legislation (EU AI Act), voluntary commitments (Responsible Scaling Policies), and technical safety measures (red-teaming, model evaluations) that reflect deep disagreements about how to balance innovation with risk.
The Open-Source Ecosystem
The open-source AI ecosystem — from Hugging Face’s model hub to llama.cpp’s local inference to vLLM’s production serving — created the infrastructure that turned open model weights into a global innovation engine, enabling anyone to run, modify, and build on frontier AI.
Where LLMs Are Heading
The trajectory of LLMs points toward a convergence of agentic autonomy, efficient reasoning, multimodal integration, and open-weight parity — raising fundamental questions about the nature of understanding, the economics of knowledge work, and the alignment of increasingly capable systems.