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This article discusses an anti-pattern in AI agent systems where agents appear busy but fail to complete tasks. The author suggests separating responsibilities and requiring proof of completion as a solution.
Sam Altman shares his belief that clarity of thinking, speed, and quality of execution are linked, using writing as a tool to clarify thoughts.
The article argues that most AI agent startups are not true agents and will disappear within two years, as open-source tools like Claude Code enable solo developers to build what previously required full teams, shifting advantage from model size to execution and reliability.
This paper identifies two coupled scaling laws for skill libraries in LLM agent systems: routing accuracy decays logarithmically with library size, and execution dynamics show a rescue effect. The laws are validated across 15 models and over a million decisions, and law-guided optimization significantly improves performance.
Elentaria is a product launched on ProductHunt that helps with go-to-market strategy from diagnosis to execution.
In Parallel is an operating system for execution, designed to manage and coordinate parallel workflows and tasks.