Andreas Kraft
32 posts
I automated my content engine and 2 hrs/day dropped to 10 min
[ what’s new in v2 ]:
- 9 platforms scraped while I sleep → 2,000+ topics/day
- a 5-signal scoring brain that filters down to the 10 that matter
- voice DNA writer.. same tone, different structure every time
- a self-learning loop that remembers every approve and decline
- profile DNA — knows exactly what goes viral on MY account
v1 was a brain with no body
v2 has eyes, a filter, and memory + fully automated
Here’s how to build it step-by-step ↓
[ The architecture]:
/content-engine
├── scrapers/ (9 platform scrapers)
├── extension/ (chrome ext for X, linkedin, reddit)
├── ai/
│ ├── ranker.py (5-signal scoring brain)
│ ├── content_writer.py (voice DNA + structures)
│ ├── profile_analyzer.py (your positioning DNA)
│ └── sentiment_analyzer.py
├── publisher/ (export + time slot scheduling)
├── gui/dashboard.py (streamlit command center)
├── ingest_server.py (local server on localhost)
└── data/content_engine.db (everything stored locally)
let me walk you through each layer ↓
LAYER 1: Research engine
9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin)
every post you scroll past gets tagged and stored locally
LAYER 2: Scoring brain
every topic scored on 5 signals:
- freshness (0.20)
- velocity (0.25)
- virality (0.25)
- relevance (0.20)
- uniqueness (0.10)
velocity 8+ → forced min score of 7. catches late bloomers that suddenly explode
2,000 topics → top 10 ranked
LAYER 3: Voice DNA writer
not one structure every time. system picks the format:
- short take
- tactical playbook
- QT contrast
- contrarian
- resource drop
- proof post
a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words
LAYER 4: Dashboard Streamlit
dark theme. 5 tabs
review queue = tinder for content. swipe approve, swipe decline
LAYER 5: Publishing
no auto-posting. zero account risk
approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post
also auto-drafts a linkedin version of every approved tweet
LAYER 6: Self-learning loop
every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain
month 1: you approve 30%
month 3: 70% pre-filtered
month 6: 10 min/day
LAYER 7: Profile DNA
analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account
the scoring brain uses it to prioritize what already works for you
daily run: open dashboard → 10 min reviewing → post 3x → close
total cost: ~$15/month
everything else: local, sqlite, no cloud, no subscription
unfortunately I couldn’t paste in long-form format initial description which was made before
but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code
reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write)
save this so you don't lose it
Ronin@DeRonin_
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@Eddsworld @JonMastu Why’s the eggs and green bacon like that😏
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@MachiToons But aren’t the numbers 13 till 19 in English the same? And when you say for example 113 you have the same quirky shit piss in English too?
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【理芽×te'resa「IMAGINARY WORLD」】
本配信に関して、録音録画は禁止とさせていただきます。
放送画面のスクリーンショット撮影、撮影した「静止画」のアップロードを各種SNS、WEBサービスで行う事は問題ございません。
是非、一緒に盛り上げてくれたら嬉しいです。
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