Build Multi-Agent Triage with Hermes in 2 Hours
Build a multi-agent triage pipeline with Hermes Agent v2.0+ by configuring scout agents for each signal source (Discord, GitHub, Reddit), a shared SQLite kanban board for deduplication, and parallel research subagents. T...
Deepak Bagada
CEO, SaaSNext
- Production-ready architecture blueprint and execution guide.
- Real-world benchmark metrics, time savings, and API integration steps.
- Verified implementation for AI founders, developers, and SaaS builders.
Build a multi-agent triage pipeline with Hermes Agent v2.0+ by configuring scout agents for each signal source (Discord, GitHub, Reddit), a shared SQLite kanban board for deduplication, and parallel research subagents. Teams process 100+ signals daily with under 5 minutes of human review time per accepted item.
A 5-person growth team monitors 8 channels for user feedback. Discord community, GitHub issues, Twitter mentions, support tickets, NPS responses, app store reviews, Reddit threads, Intercom chats. Each team member spends 2-3 hours daily manually scanning these sources manually. [STAT: 68% of product teams report signal triage consumes more time than feature development (ProductPlan, 2025)] Signals fall through the cracks daily. Lost revenue opportunities pile up. User complaints escalate to churn because nobody saw them in time.
The old approach was hiring more people. The new approach is building a triage pipeline that never sleeps. Hermes Agent runs scout agents on cron schedules across all channels simultaneously. Every signal gets a kanban card with a source tag, urgency score, and timestamp. The deduplication engine catches the same bug reported in Discord and GitHub and merges them into one card with incremented signal count. No duplicates. No lost context.
[TOOL: Hermes Kanban Board] The SQLite kanban board is the backbone. Each card holds the signal source, a composite score from the rubric engine, research findings from parallel subagents, and a routing decision. The board gives the team a single source of truth for what is happening across their entire user community.
[TOOL: Tavily MCP Server] Research subagents run in parallel on every signal that scores above 70. They fetch top sources, extract key findings, and attach a research brief to the kanban card. The orchestrator compares results across subagents, detects contradictions, and requests re-research if findings disagree.
[STAT: Teams using AI triage pipelines capture 94% of actionable signals vs 60% with manual scanning (Source: Hermes Community Benchmarks, 2026)]
The human approval gate is a single daily Telegram digest. The reviewer sees scored, researched, routed cards and spends 5 minutes approving or shelving. No digging through 8 channels. No Slack notifications at 2 AM. One review session per day.
[TOOL: GitHub MCP Server] Approved items auto-create GitHub issues with research briefs attached. The issue gets the correct sprint label based on urgency. The pipeline posts the issue link back to the kanban board with a closed-loop timestamp.
What this means for your team: 94% signal capture rate. 5 minutes of daily human review. 24-48 hour signal-to-action latency drops to 15-30 minutes. The pipeline gets better every week as the rubric learns which signal types your team accepts and which you shelve.
Setup takes 2 hours. Configure 8 scouts in triage.yaml. Write a rubric with 4 criteria. Start the Hermes gateway. Your first daily digest arrives automatically the next morning.
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Deepak Bagada
CEO, SaaSNext
Deepak Bagada is the CEO of SaaSNext and founder of Daily AI World. He covers AI workflows, agentic automation, LLM architectures, and founder growth strategies.
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