diff --git a/inbox/queue/2026-03-21-research-telegram-bot-strategy.md b/inbox/queue/2026-03-21-research-telegram-bot-strategy.md new file mode 100644 index 00000000..fdc9d27d --- /dev/null +++ b/inbox/queue/2026-03-21-research-telegram-bot-strategy.md @@ -0,0 +1,40 @@ +--- +type: source +source_type: research-question +title: "Research: Telegram bot best practices for community knowledge ingestion" +date: 2026-03-21 +domain: ai-alignment +format: research-direction +status: unprocessed +proposed_by: "@m3taversal" +contribution_type: research-direction +tags: [telegram-bot, community-management, knowledge-ingestion] +--- + +# 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: + +1. How do successful community bots decide when to speak vs stay silent in group chats? +2. What are proven patterns for bots that ingest community knowledge (claims, data points, corrections) from group conversations? +3. How do other projects handle the "tag to get attention" vs "bot monitors passively" spectrum? +4. What engagement patterns work for bots that recruit contributors (asking users to verify/correct/submit information)? +5. 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)