Dev Firm Shares Honest Account of Running Its Own AI Systems in Production

A development company has published a candid technical series detailing the AI tools and agent systems it built and runs internally, not as marketing material but as a practical field report. The firm developed its own memory system, a self-improving agent framework called Darwin, a learning platform, and a fleet of overnight agents after encountering real-world failures no manual had covered. Key lessons emerged from recurring production problems such as storage bloat, silent token expiry failures, and models shifting behavior without warning. The company follows a firm principle that AI agents prepare and surface information while humans retain final decision-making authority over actions like sending emails or closing contracts. Several of these internally built tools have since been released publicly or offered as subscribable services.