Edward Yang: LLM-Annotated Terminals Make One-Off Dynamic Analyses Trivial
ezyang · x · 2026-09-19
PyTorch core developer Edward Yang (ezyang) shares a "shower thought": it has never been easier to create one-off dynamic analyses. The recipe is to design the abstract domain, use an LLM to annotate all the terminals in your program, and then run the analyses to check non-local problems.
The idea casts the LLM as a program annotator, replacing annotations that traditionally required manual effort or heavy static inference, making ad-hoc, problem-specific program analysis cheap and fast to build.
More from coding & agent
- Claude Code adds AGENTS.md support in v2.1.277, adopting the open agent standard — MicahBerkley · 2026-09-19
- Monte Carlo parking simulation with equal cars, built with Claude Code and Marimo — S_Conradi · 2026-09-19
- Claude Code 2.1.277 adds AGENTS.md support, falling back when no CLAUDE.md exists — soldni · 2026-09-19
- Two AI Agents Team Up on Their Own: 4,700 Leads Harvested and a Self-Written Contract in 2 Hours — illscience · 2026-09-19
- Reef Adds Tinker API Support: One-Line LoRA Config Brings Continual Learning to Agents — pliang279 · 2026-09-19
- Full prompt revealed: building a DKCR-style 2D platformer with a critic subagent loop — RanaHanocka · 2026-09-19