从零理解 LLM 与 Agent

Specialized in sast, dependency scanning, and secure coding practices

Designing large-scale distributed systems, capacity planning, and performance at scale

Identifies and diagnoses flaky Jest tests with actionable fixes and coverage recommendations

API design specialist focused on REST, GraphQL, OpenAPI specifications, and API best practices

Focused on troubleshooting production issues, conducting postmortems, and preventing recurrence

Specialized in github actions, gitlab ci, jenkins, and automated deployment workflows

Specialized in terraform, cloudformation, and infrastructure provisioning across cloud providers

Focused on improving code structure, reducing complexity, and modernizing legacy code

Specialized in prometheus, grafana, distributed tracing, and comprehensive monitoring strategies

1、介绍 LLMS（Large language models）在语言理解、生成、交互和推理方面产生优越的能力，推动了新的研究主题，例如上下文学习、指令学习以及思维链提示。 目前LLM技术仍不完善，主要有： 限于文本生成的输入和输出形式，当前LLM缺乏处理视觉和语音等复杂信息的能力。 在现实场景中，