๐ค๐ธ๏ธ Cisco ๐๐ช๐ฉ๐จ๐๐๐๐ฉ LangChain: ๐๐๐ ๐๐๐จ๐ ๐ค๐ ๐ผ๐๐๐ฃ๐ฉ๐๐ ๐๐ฃ๐ฉ๐๐ง๐ฅ๐ง๐๐จ๐ ๐ผ๐ง๐๐๐๐ฉ๐๐๐ฉ๐ช๐ง๐๐จ ๐ธ๏ธ๐ค
#for_ai_architects
#for_solutions_architects
#for_cloud_architects
#did_you_know_that Ciscoโs Outshift team has built a full-stack, LangChain-powered multi-agent system architecture for enterprise operations using OpenAI, GitHub, PagerDuty, Atlassian Jira, and Cisco Webex?
Letโs explore how this LLM-native systemโnamed Jarvisโimplements a production-grade, agentic orchestration layer.
๐๏ธ ๐๐ช๐ก๐ฉ๐-๐ผ๐๐๐ฃ๐ฉ ๐๐๐ฅ๐๐ก๐๐ฃ๐:
Hierarchical Supervisor Agent interprets user prompts and coordinates execution across downstream agents.
Agents communicate via AGNTCY (Agent Connect Protocol), ensuring modular, scalable interaction between supervisors and tools.
Specialized agents handle incidents, GitHub repos, schedules, and Jira actions with tool-specific subagents.
๐ง ๐๐๐ฃ๐๐พ๐๐๐๐ฃ ๐๐๐ ๐๐๐ง๐ซ๐๐๐๐จ:
LLM calls (via OpenAI) provide reasoning, explanation, and action chaining.
LangSmith handles tracing and evaluation for visibility into every agent decision.
โก ๐๐ฎ๐จ๐ฉ๐๐ข ๐๐ฃ๐ฉ๐๐๐ง๐๐ฉ๐๐ค๐ฃ๐จ:
Interfaces include Webex (streaming), CLI (interactive), Jira (webhooks), and GitHub (web actions).
Reflection agents evaluate progress mid-taskโasking: โIs the task done? Should we continue?โ
๐ฏ ๐๐๐ ๐ผ๐๐๐ฃ๐ฉ๐๐ ๐๐ช๐ฉ๐ช๐ง๐ ๐ค๐ ๐๐ฃ๐ฉ๐๐ง๐ฅ๐ง๐๐จ๐:
Cisco Outshiftโs architecture shows how agent-based orchestration can deeply integrate with existing enterprise infrastructureโbringing LLM-native reasoning to DevOps, service management, and incident response.
Thanks to the LangChain team for sharing this collaboration: ๐
lnkd.in/dP4nZWD8
๐งญ Stay tuned and subscribe: ๐
lnkd.in/dSsBFgAN
#agenticai #langchain #cisco #outshift #multimodalagents #llmops #jarvis #openai #langsmith #webex #github #devopsautomation #orchestration #agentconnect #favikon #cloud #cloudcomputing #ai #cybersecurity #multicloud