epimetheus: queue research on telegram bot strategy
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inbox/queue/2026-03-21-research-telegram-bot-strategy.md
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---
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type: source
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source_type: research-question
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title: "Research: Telegram bot best practices for community knowledge ingestion"
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date: 2026-03-21
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domain: ai-alignment
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format: research-direction
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status: unprocessed
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proposed_by: "@m3taversal"
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contribution_type: research-direction
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tags: [telegram-bot, community-management, knowledge-ingestion]
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---
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# Research Question: Telegram Bot Best Practices for Community Knowledge Ingestion
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## What we want to learn
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Best practices and strategies for AI-powered Telegram bots that operate in crypto/web3 community groups. Specifically:
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1. How do successful community bots decide when to speak vs stay silent in group chats?
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2. What are proven patterns for bots that ingest community knowledge (claims, data points, corrections) from group conversations?
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3. How do other projects handle the "tag to get attention" vs "bot monitors passively" spectrum?
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4. What engagement patterns work for bots that recruit contributors (asking users to verify/correct/submit information)?
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5. How do projects like Community Notes, Wikipedia bots, or prediction market bots handle quality filtering on user-submitted information?
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## Context
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We have a Telegram bot (Rio/@FutAIrdBot) deployed in a 3-person test group. The bot responds to @tags with KB-grounded analysis and can search X for research. We want to deploy it into larger MetaDAO community groups (100+ members).
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Key tension: the bot needs to be useful without being noisy. In testing, it responded to messages not directed at it (conversation window auto-respond). We stripped that and now it only responds to @tags and reply-to-bot.
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The next evolution: other users can tag the bot when they see something interesting ("@FutAIrdBot this is worth tracking"). This makes the community the filter, not the bot.
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## What to search for
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- Telegram bot engagement strategies in crypto communities
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- AI agent community management best practices
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- Knowledge ingestion from group chats
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- Community-driven content moderation/curation bots
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- Prediction market community bot patterns (Polymarket, Metaculus)
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