Language Models are Few-Shot Learners
The 2020 paper that made prompting the new programming.
In 2020, OpenAI scaled a language model to 175 billion parameters and discovered something unexpected: at that size, the model no longer needed retraining to learn new tasks. You could just show it a few examples in the prompt — and it figured the rest out on its own. This bundle unpacks how GPT-3 shattered the fine-tuning paradigm and turned "prompt engineering" into a discipline.
Related Reads
Inside OpenAI Astra: The looped transformer
Frontier labs are trading parameter bloat for recurrent depth. The model gets deeper by running the same layers again, and the reasoning stops being readable.
Claude's Mind: J-Space
Anthropic found a small, organized workspace inside Claude where silent reasoning happens before a single word gets typed.
SkillOpt: Self-Evolving Agent Skills
Microsoft's new system lets AI agents rewrite their own tools when the world changes.