References
Food for thought
The articles, research, and engineering work that shape how we think. Not an exhaustive list — a curated one.
Articles
On building with AI as infrastructure
On the infrastructure layer that emerges when AI becomes the default execution surface.
Services: The New Software
The thesis that the next trillion-dollar companies will deliver outcomes, not tools. Services as the new software.
How I think about LLM prompt engineering
A precise reframing: LLMs as databases of vector programs, and prompt engineering as a search through that space.
The Scaling Hypothesis
The foundational case for why scaling neural networks produces qualitative leaps, not just incremental gains.
Projects & Labs
ARC Prize
The benchmark that keeps the field honest about what intelligence actually requires beyond pattern matching.
Anthropic Research
Frontier work on interpretability and alignment — understanding what models actually learn.
OpenAI Engineering
The engineering discipline behind deploying intelligence at scale.
jxnl.co
Practitioner-grade thinking on structured outputs, retrieval, and making LLMs reliable in production.