Zero-Maintenance Feedback: Building a Telegram + AI Vision Triage Bot

TL;DR

• Frictionless Intake: Use a Telegram group as your "Inbox". Forward any feedback or screenshot there, and let the bot handle the rest.
• AI-Powered Triage: Use LLMs (like GPT-4o or Gemini) to analyze images, extract error text, and categorize the intent (Bug, Feature, etc.).
• Jira Automation: Automatically create tickets with attachments or link to existing ones, keeping your requirement management loop clean.

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The problem? Triage is a chore. Moving that image from your phone to Jira, writing a description, and tagging it properly takes enough effort that 50% of feedback just dies in your "Saved Messages".

As an AI-augmented PM, your goal is to automate the mundane so you can focus on the product strategy. Here is how to build a Zero-Maintenance Feedback Loop.

The Workflow: From Screenshot to Structured Ticket

Instead of a complex app or a heavy SDK, we stay where the users (and your teammates) already are: Telegram.

1. The Inbox: A Telegram "Triage" Group

Create a private Telegram group and add your bot as an Administrator.

IMPORTANT: The Privacy Gotcha By default, Telegram bots cannot see group messages unless they are commands or mentions. To fix this, you must Turn Off Privacy Mode via @BotFather (under Bot Settings > Group Privacy) or ensure the bot is an Admin with "Manage Messages" permissions.

• Step: Every time you see a bug or a user sends you feedback, simply forward it to this group.
• Why: It centralizes chaos. You don't need to open your laptop; you just forward and forget.

2. The Trigger: Manual Agent vs. Automated Task

Depending on your workflow, you can handle the message ingestion in two ways:

1. Option A: Manual / Agentic (Claude Skill):

   • How: You manually trigger a task in your AI environment (like Antigravity or a CLI tool).
   • Trigger: "Claude, fetch the last 10 messages from the Triage Group and process them."
   • Benefit: High control, saves on automated API calls, and allows you to add immediate context (e.g., "This relates to the current sprint").

2. Option B: Automated / Scheduled (n8n & Cron):

   • How: Set up a recurring task using n8n or a local Cronjob.
   • Trigger: Every hour (or every message via Webhook), the system automatically sweeps the group.
   • Benefit: True "zero-maintenance". Feedback flows into Jira even while you sleep, using dedicated LLM API keys for background processing.

3. The Brain: AI Vision Analysis (GPT-5.2 / GPT-4.5 Turbo)

The bot sends the photo to a multimodal LLM. In 2026, you have two prime choices:

• GPT-5.2: The gold standard for complex reasoning. Best if you need the AI to cross-reference your specific technical specs or PRDs.
• GPT-4.5 Turbo: 70% cheaper and hyper-optimized. Perfect for simple "Is this a bug?" classifications.

The Prompt:

"Analyze this screenshot. Extract any visible error messages, identify the UI components involved, and determine if this is a Bug, Feature Request, or UX Improvement."

Structured Output Example:

{
  "triage_type": "bug",
  "priority": "P2",
  "summary": "Login page failure on mobile",
  "description": "User reported 404 error during SSO login flow. Error text: 'Service Unavailable'.",
  "components": ["Auth", "Mobile Web"],
  "suggested_action": "check_existing_ticket: AUTH-123"
}

4. The Execution: Jira Integration

Finally, the system calls the Jira API.

• New Issues: For unique bugs, it creates a ticket, uploads the original screenshot as an attachment, and sets the priority.
• Existing Tickets: If the AI detects it's a known issue, it simply adds the new screenshot as a comment to the existing tracker.

Setup Guide (Preview)

[Detailed technical steps for n8n configuration and API scripts will be expanded in the next iteration.]

Technical Stack

• Entry: Telegram Bot API (via BotFather).
• Orchestration: n8n (for low-code) or a Python script using telethon and jira-python.
• Vision: OpenAI GPT-4o or Google Gemini Pro Vision.

Conclusion

The best tools are the ones you actually use. By bridging the gap between a casual message and a formal requirement tracker, you ensure that no valuable feedback "slips through the cracks".