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| type | source_type | title | date | domain | format | status | proposed_by | contribution_type | tags | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| source | research-question | Research: Telegram bot best practices for community knowledge ingestion | 2026-03-21 | ai-alignment | research-direction | unprocessed | @m3taversal | research-direction |
|
Research Question: Telegram Bot Best Practices for Community Knowledge Ingestion
What we want to learn
Best practices and strategies for AI-powered Telegram bots that operate in crypto/web3 community groups. Specifically:
- How do successful community bots decide when to speak vs stay silent in group chats?
- What are proven patterns for bots that ingest community knowledge (claims, data points, corrections) from group conversations?
- How do other projects handle the "tag to get attention" vs "bot monitors passively" spectrum?
- What engagement patterns work for bots that recruit contributors (asking users to verify/correct/submit information)?
- How do projects like Community Notes, Wikipedia bots, or prediction market bots handle quality filtering on user-submitted information?
Context
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).
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.
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.
What to search for
- Telegram bot engagement strategies in crypto communities
- AI agent community management best practices
- Knowledge ingestion from group chats
- Community-driven content moderation/curation bots
- Prediction market community bot patterns (Polymarket, Metaculus)