// CONTENT INTELLIGENCE

EVERY SIGNAL.
ZERO NOISE.

AIF continuously scans Hacker News, Reddit, GitHub releases, and YouTube for developments in the agentic AI space. Every item is scored on a 100-point composite model across relevance, urgency, quality, and novelty — then bucketed into priority bands so the signal finds you. Replace the habit of checking five platforms with one feed.

Launch App Learn More
4
Platforms Monitored
100
Point Scoring Model
6+
Interest Groups
4
Content Types
// HOW IT WORKS

Signal in. Noise out. Automatically.

From four raw content platforms to one ranked intelligence feed in five steps.

01
Scan Sources
Every 15 minutes AIF queries Hacker News top stories, six targeted Reddit subreddits, GitHub release feeds, and YouTube keyword searches — pulling new items into the ingest queue.
02
Score Each Item
Each item is scored on a 100-point composite model: 40 pts relevance (keyword match against your interest groups), 30 pts urgency (recency + time decay), 20 pts quality (engagement signals), 10 pts novelty (deduplication).
03
Band & Filter
Items are bucketed into six bands: Critical (95-100), High (80-94), Notable (65-79), Informational (45-64), Low (25-44), Noise (0-24). Noise items are hidden by default — they never surface in your feed.
04
Alert & Deliver
Critical items (score ≥95) trigger an immediate Telegram push notification. High and above are included in the daily digest. Weekly summary captures Informational items for background reading.
05
Review & Act
Open the feed, filter by group, band, or platform, click any item to expand the full score breakdown. Bookmark items for later. Send high-signal items directly to NLG for the next newsletter edition with one click.

Command Center

The dashboard gives you an instant snapshot of your intelligence pipeline. Six stat tiles show total items ingested, how many have been scored, critical and high-priority counts, active interest groups, and connected sources. A platform distribution bar breaks down content volume across Hacker News, Reddit, GitHub, and YouTube. Below that, a ranked table of the top 15 items by composite score lets you triage the most important signals at a glance. Last scan metadata shows exactly when data was last refreshed.

meltuc.tech/aif/app/dashboard
847
Total Items
812
Scored
3
Critical
18
High
6
Groups
4
Sources
Platform Distribution
HN 296
Reddit 254
GitHub 169
YT 128
Top 15 by Score
# Title Score Band Source
1Claude 4 Opus released with 1M context98CriticalHN
2MCP Protocol spec v2 breaking changes96CriticalGitHub
3Anthropic Agent SDK hits 1.091HighHN
4Self-hosted LLM comparison: Llama vs Mistral87HighReddit
5Flask 3.1 release notes83HighGitHub
6Supabase edge functions now support Python78NotableHN
7Building agentic workflows with tool use72NotableYouTube
Last scan: 2 min ago · Next: in 13 min

Scored Content Stream

The main feed is a filterable data grid showing every ingested item. Each row displays a platform icon, title, composite score with color coding, priority band badge, author, and publish date. A filter bar at the top lets you search by keyword, filter by interest group, platform, or score band. Clicking any row opens a slide-out detail panel on the right with the full score breakdown (relevance, urgency, quality, novelty), matched interest groups, engagement statistics, and the full content text.

meltuc.tech/aif/app/feed
Search items...
All Groups
All Platforms
All Bands
Title Score Band Author Published
YClaude 4 Opus released with extended context98Critical@hn_top2m ago
GMCP Protocol spec v2 with breaking changes96Criticalanthropics18m ago
YAnthropic Agent SDK reaches stable 1.091High@hn_top35m ago
RSelf-hosted LLM comparison benchmark 202687Highu/localdev1h ago
GFlask 3.1.0 release with async improvements83Highpallets2h ago
YSupabase edge functions with Python support78Notable@hn_top3h ago
TDeep dive: Agentic tool use patterns72NotableAI Eng4h ago
RPython 3.13 free-threading real-world tests62Infou/pydev5h ago
ITEM DETAIL
Claude 4 Opus released with 1M context window
Score Breakdown
Relevance39/40
Urgency28/30
Quality19/20
Novelty10/10
Matched Groups
Anthropic Claude LLM Releases
Engagement
482 points · 213 comments

Bookmarked Content

Items you bookmark from the feed land here for later reference. The saved items view is a streamlined grid showing each item's source platform, title, score at time of save, and the date you bookmarked it. One-click removal keeps your collection clean.

meltuc.tech/aif/app/saved
SAVED ITEMS (12)
Search saved...
Title Score Saved
YClaude 4 Opus released with 1M context98Apr 8x
GMCP Protocol spec v2 breaking changes96Apr 8x
YAnthropic Agent SDK hits stable 1.091Apr 7x
RSelf-hosted LLM comparison 202687Apr 7x
TAgentic tool use patterns deep dive72Apr 6x
RPython 3.13 free-threading benchmarks62Apr 5x

Configuration

Settings is where you shape the feed to your needs. Manage interest groups with custom keywords and priority levels, control scan intervals, set score thresholds for critical alerts and digest cutoffs, configure your YouTube API key and Telegram bot for push notifications, and set data retention policies.

meltuc.tech/aif/app/settings
Interest Groups
Anthropic / Claude P0
Keywords: claude, anthropic, sonnet, opus, haiku, MCP
EditDelete
Agentic Workflows P1
Keywords: agent, tool use, function calling, agentic
EditDelete
Self-Hosted / Local LLMs P1
Keywords: llama, ollama, self-hosted, local, vllm
EditDelete
+ Add Interest Group
Scan Settings
Scan Interval
15 minutes
Score Thresholds
Critical Alert
95
Digest Cutoff
65
Summary Cutoff
45
Integrations
YouTube API Key
AIza***************
Telegram Bot Token
7012*****:AAH***
Data Retention
30 days
// SCORING MODEL

100-Point Composite Score

Every item ingested by AIF is scored on four weighted dimensions. The composite score determines which priority band an item falls into — from Critical (immediate attention) down to Noise (auto-filtered). Time decay ensures older items gradually lose urgency weight.

Relevance
40 pts
/ 100
Urgency
30 pts
/ 100
Quality
20 pts
/ 100
Novelty
10 pts
/ 100
Relevance (40 pts)
How closely the content matches your interest group keywords and topic priorities.
Urgency (30 pts)
Time sensitivity — breaking releases, security patches, and fast-moving discussions score highest. Decays over time.
Quality (20 pts)
Engagement signals (upvotes, stars, comments), source reputation, and content depth.
Novelty (10 pts)
Deduplication and freshness — penalizes items that repeat topics you've already seen.
Score Bands
Critical — 95-100 — Immediate attention. Pushed to Telegram.
High — 80-94 — Important. Included in daily digest.
Notable — 65-79 — Worth reviewing when you have time.
Informational — 45-64 — Background reading. Included in weekly summary.
Low — 25-44 — Marginally relevant. Available in feed but not surfaced.
Noise — 0-24 — Filtered out. Not displayed by default.
// SOURCES

Monitored Platforms

AIF pulls content from four platforms, each with targeted queries tuned for the agentic AI space and adjacent developer ecosystems.

Y
Hacker News
Top stories from the front page. Scored and filtered for AI, developer tooling, and infrastructure signals.
Top StoriesShow HN
R
Reddit
Six subreddits covering Claude, local LLMs, machine learning, AI research, Python, and self-hosted infrastructure.
r/ClaudeAI r/LocalLLaMA r/MachineLearning r/artificial r/Python r/selfhosted
G
GitHub Releases
Tracking new releases from key repositories in the Anthropic, Flask, Supabase, and MCP ecosystems.
anthropics/* pallets/flask supabase/* modelcontextprotocol/*
T
YouTube
Keyword-based search for tutorials, announcements, and deep dives on agentic AI topics and developer tooling.
Keyword SearchNew Uploads
// NEW CAPABILITIES

Recent Additions

The latest release adds cross-app publishing and 30-day trend visibility directly on the dashboard.

📤
Send to NLG
A 📤 button on each feed item sends it directly to the NLG content pool with one click. The item is immediately available as source material for the next newsletter draft — no manual copy-paste between apps required.
POST /api/item/<id>/send-to-nlg NLG Integration One Click
📊
30-Day Topic Trend Chart
A Chart.js bar chart on the dashboard shows content volume by type over the trailing 30 days. See at a glance whether HN, Reddit, GitHub, or YouTube is driving the most signal this month — and whether overall volume is trending up or down.
Chart.js 30-Day Window By Content Type
// FEATURES

One Feed. Every Signal That Matters.

Every feature in AIF is built around a single goal: getting the right signal to you before it's old news.

📡
Multi-Platform Ingestion
Pulls from Hacker News top stories, six AI-focused subreddits, tracked GitHub release repos, and YouTube keyword searches — all on a 15-minute scan cycle.
📊
100-Point Composite Score
Four weighted dimensions: Relevance (40 pts), Urgency (30 pts), Quality (20 pts), Novelty (10 pts). Time decay is applied automatically so older items don't crowd out breaking news.
Priority Bands
Six bands from Critical down to Noise. Noise is hidden by default. Critical items fire Telegram alerts immediately. High and above surface in the daily digest.
🔍
Interest Groups
Create named groups with custom keywords and priority levels. Every item is scored against all your groups — the highest-scoring group match determines relevance weight.
📊
30-Day Trend Chart
Dashboard bar chart shows content volume by source type over the trailing 30 days. See at a glance whether HN, Reddit, GitHub, or YouTube is driving the signal this month.
📤
Send to NLG
A single button on any feed item ships it straight to the NLG content pool for inclusion in the next newsletter edition — no manual copy-paste between apps.
Saved Items
Bookmark any item from the feed for later reference. The saved items view keeps a clean archive with source, score at time of save, and one-click removal.
🔁
NLG Feedback Loop
After a newsletter runs, NLG writes back onto each item: content it used floats to the top of your score-sorted feed, and items it rejected as duplicates are hidden automatically — so the feed keeps learning what you actually act on.
🧭
Source Recommendations
Claude suggests new subreddits, channels, and repos to follow based on your interest-group keywords, so your coverage grows with your focus areas.
// GET STARTED

Stop Checking. Start Knowing.

Four platforms. One scored feed. Every signal that matters in the agentic AI space, ranked and ready.

Launch Agentic Intelligence Feed

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