Sticky Note Automate

Sticky Note Automate streamlines communication by filtering Slack messages and responding with a sharp AI agent. It captures conversation history, utilizes external tools for enhanced responses, and sends outputs directly to Slack, ensuring efficient and engaging interactions.

7/8/2025
14 nodes
Medium
webhookmediumsticky notelangchainnoopslackadvancedlogicconditionalcommunicationnotificationintegrationapi
Categories:
Communication & MessagingWebhook TriggeredMedium Workflow
Integrations:
Sticky NoteLangChainNoOpSlack

Target Audience

Target Audience


- Developers: Those who want to automate Slack interactions and enhance user engagement.
- Product Managers: Individuals looking to streamline communication and gather insights from team discussions.
- Support Teams: Teams needing to filter out bot messages and focus on genuine user inquiries.
- AI Enthusiasts: Users interested in implementing AI-driven responses in communication platforms.

Problem Solved

Problem Solved


This workflow addresses the challenge of managing Slack communications by filtering out bot messages and providing intelligent, context-aware responses. It enables a more efficient interaction model, ensuring that only relevant user messages are processed and responded to, thus improving overall productivity and user satisfaction.

Workflow Steps

Workflow Steps


1. Webhook Trigger: The process begins when a POST request is sent to the specified webhook path (/slack-gilfoyle), capturing incoming Slack messages.
2. Message Filtering: The workflow checks if the message is from a user and not a bot. If it's a bot message, it proceeds to a no-operation node, effectively ignoring it.
3. Memory Storage: For valid user messages, the conversation history is stored using a unique session key based on the channel ID, allowing for context retention.
4. AI Processing: The user message is then processed by an AI agent, which utilizes a specific persona (Gilfoyle from Silicon Valley) to generate a response that is blunt and to the point.
5. Language Model Integration: The AI's output is further refined using an OpenAI chat model, ensuring high-quality responses.
6. Response Delivery: Finally, the processed response is sent back to the user via Slack, completing the interaction cycle.

Customization Guide

Customization Guide


- Modify AI Persona: Change the systemMessage parameter in the AI Agent node to adjust the personality and tone of the responses.
- Adjust Memory Settings: Customize the contextWindowLength in the Simple Memory node to control how much conversation history is retained for context.
- Change Webhook Path: Update the path parameter in the Webhook node to alter the endpoint that triggers this workflow.
- Integrate Additional Tools: Add or modify existing tools like SerpAPI or Wikipedia in the workflow to enhance the capabilities of the AI agent.
- Slack Message Formatting: Customize the text parameter in the Slack node to format the outgoing messages according to your team's preferences.