If you run an active learning chat, you already have knowledge: mentor answers, problem breakdowns, links, decisions, and “golden” messages. The issue is that it gets buried in the feed. A knowledge base is not “a doc somewhere” — it’s a repeatable way to find and reuse the best parts of your chat history.
Step 1. Decide what must not be lost
Pick 3–5 knowledge types you want to preserve:
- answers to recurring questions (FAQ)
- homework / problem explanations
- rules, links, course guidelines
- lecture discussion summaries
- decisions and agreements
Step 2. Add lightweight “publish knowledge” rules
People need a shared format:
- ask for a single-message question (context + expected outcome)
- encourage structured answers (steps, links, examples)
- agree on a simple “mark” for valuable answers (a reaction/tag)
Step 3. Make knowledge accessible via search (not folders)
Pinned messages and manual folders don’t scale. Keyword search often misses meaning.
A scalable approach:
- search by meaning, not just words
- show quotes and links to original messages
- separate different opinions to preserve context
Step 4. Automate summaries and digests
For learning groups, context matters:
- daily/weekly digest (what changed, what to read, what to do)
- lecture recap from discussion
- common mistakes and best explanations
Step 5. Use AskMore as your knowledge layer
AskMore reads chat history, builds a secure knowledge index, and helps you:
- find past answers (with quotes and links)
- generate AI summaries
- highlight experts and prioritize their answers
Try it on Telegram: https://t.me/AskMoreBot
Next
If you’re starting a community, begin with onboarding: first 7 days plan. If repeats are your main pain, build a living FAQ: FAQ without repetition.