From 733d6514b71423ab5b15d62609cb92d34dd426d3 Mon Sep 17 00:00:00 2001 From: Teleo Agents Date: Sat, 21 Mar 2026 17:15:01 +0000 Subject: [PATCH] pipeline: clean 1 stale queue duplicates Pentagon-Agent: Epimetheus <3D35839A-7722-4740-B93D-51157F7D5E70> --- ...26-03-21-research-telegram-bot-strategy.md | 52 ------------------- 1 file changed, 52 deletions(-) delete mode 100644 inbox/queue/2026-03-21-research-telegram-bot-strategy.md diff --git a/inbox/queue/2026-03-21-research-telegram-bot-strategy.md b/inbox/queue/2026-03-21-research-telegram-bot-strategy.md deleted file mode 100644 index a540b8c2..00000000 --- a/inbox/queue/2026-03-21-research-telegram-bot-strategy.md +++ /dev/null @@ -1,52 +0,0 @@ ---- -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: null-result -proposed_by: "@m3taversal" -contribution_type: research-direction -tags: [telegram-bot, community-management, knowledge-ingestion] -processed_by: theseus -processed_date: 2026-03-21 -extraction_model: "anthropic/claude-sonnet-4.5" -extraction_notes: "LLM returned 0 claims, 0 rejected by validator" ---- - -# 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) - - -## Key Facts -- Rio/@FutAIrdBot is deployed in a 3-person test group -- Rio responds to @tags with KB-grounded analysis and can search X for research -- Bot initially had conversation window auto-respond, now stripped to only @tags and reply-to-bot -- Planned deployment into MetaDAO community groups with 100+ members -- Next evolution allows users to tag bot when they see something interesting for tracking