Tag
Based on conversations with over 20 teams, the author identifies three recurring pain points when using LLMs in production: enterprise-only basics, lack of agent observability, and slow support for new models.
An experienced practitioner shares hard-won lessons from deploying 25+ AI agents to production, arguing that memory, orchestration, and auditability matter far more than model choice. The article details common failure modes like context loss and silent cost loops, and recommends a stack including Claude Sonnet 4, Pydantic AI, and dedicated memory layers like Octopodas.