This issue highlights AI-powered banking insights via Mercury Command, strategies for profitable inference pricing, and the rise of “company-building” startups. It also covers common founder missteps in early sales, tactics for poaching competitors’ users, Lambda MicroVM use cases, new AI features like Claude Tag, LinkedIn’s collaborative posts, agent product pitfalls, and why moats demand ongoing effort.

The article argues that AI “loops”—self-prompting agents using a goal, context, evaluation, and an agent—outperform single-shot prompts for long-running tasks. It outlines key components, real examples like PR babysitters and bug fixers, and explains why better models, built-in loop commands, and maturing toolchains make loops practical now.