Brainforge Knowledge

deployment-workflow

2 min read

Deployment Workflow

Purpose: Multi-worker workflow to deploy new agents/tools and announce to team
Workers Used: [Agent Worker] → Slack Deployment → Feedback Loop
Status: Active

Overview

When a new agent/tool/process is deployed, this workflow ensures it’s announced to the team, documented, and wired into the feedback loop system.

Workers in This Workflow

  1. Any Agent Worker (the deployed agent)

    • Runs and generates output
    • Triggers feedback loop

  2. Slack Deployment Worker (workers/content-generation/slack-deployment/)

    • Generates deployment win message
    • Includes demo, PRD highlights, process changes, context graph evolution

  3. Feedback Loop System (shared/feedback-loop/)

    • Prompts for feedback after deployment
    • Logs run → analyzes patterns → shows impact

Flow Diagram

New Agent/Tool Deployed
    ↓
[Agent Worker] runs
    → Generates output
    ↓
[Slack Deployment Worker]
    → Creates deployment message
    ↓
[Feedback Loop System]
    → Prompts for feedback
    → Logs run
    → Analyzes patterns
    ↓
Agent Improved Over Time

Inputs

  • Deployed agent/tool/process
  • Demo link (or placeholder)
  • PRD highlights
  • Process changes

Outputs

  • Slack deployment message
  • Feedback session logged
  • Pattern analysis (after multiple runs)

Execution

Step 1: Agent runs and generates output

Step 2: Slack Deployment Worker creates announcement message

Step 3: Feedback Loop prompts for feedback (2-3 min)

Step 4: System logs run and analyzes patterns

Step 5: Patterns inform agent improvements (when MEDIUM confidence reached)

Example Run

Input: Automated Feedback Loop System deployed

Output:

  • Slack message announcing system
  • Feedback session: slack-deployment-2026-02-05-automated-feedback-loop.md
  • Run logged to shared/feedback-loop/RUN_LOG.md
  • Patterns tracked in shared/patterns/PATTERNS.md

Graph View