
Instead of reading 500 posts a day — an agent that filters
Adopter is a Python service plus cron that listens to Telegram channels through Telethon (a Python client that speaks MTProto — the full Telegram user protocol, not the restricted Bot API), sends each post to Gemini 2.5 Flash with a classification schema (novelty × signal × actionability × risk), and stores only the top-K items in a Qdrant collection called `network_memory`. A circuit breaker caps it at 5 adoptions per day. For me it filters 500 posts a day down to 3-5 findings — for you it can point at RSS feeds, Discord channels, Reddit or Twitter forums, mailing lists, or any content firehose that needs a smart filter.
There is simply too much content. Adopter reads for you, filters it, and surfaces only what matters.
300 open Telegram channels, notifications everywhere
Adopter reads; you get 3 posts a day with a reason why
Forgetting a great tool you heard about a month ago
Qdrant remembers everything — semantic search brings it back
Endless push that wears you out and you just mute it
Autonomous filtering — only the pretend-to-matter disappears
No trace of what you did with suggested content
Audit trail: 'adopted X because Y, skipped Z because W'
Here's how:
It scans the dozens of channels you planned to follow and returns the strongest 20%.
Trends, new players, shipped features — Adopter spots and summarises them.
New tools, frameworks, models — Adopter classifies and suggests an integration.
If you track 30 channels on the AI industry, Adopter saves you roughly 5 hours a day.
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Adopter scans on your behalf, filters, and surfaces what matters — set up in 5 minutes.
Full-Stack Developer & AI Specialist
Adopter has been running on my servers for 3 months — 20 Telegram channels, roughly 500 posts scanned per day, 3-5 adoptions per day on average. It has surfaced over 30 new tools I would never have found on my own. This guide is based on real tuning of the classifier.