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Trend Radar · live · 9 sources

Finds AI topics before they hit mainstream.

Six sources. Velocity-scored, not popularity. Updated hourly.

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See today's top signal ↓Last refresh: 59m ago

Today's top hidden gem

RedditFresh & accelerating2h ago · composite 93

If you're new to coding agents: they keep a diary, and your API keys are in it

Something nobody tells you when you start using Claude Code / Cursor / Codex / any of these: every session gets saved to your disk. The whole conversation. Forever. Which is fine — until you remember that time you pasted an API key straight into the chat "just to test something." Or the agent printed your env vars while debugging. Or a stack trace with your database URL in it. All of that is sitting in plaintext files in folders like `~/.claude` right now, and it happily tags along into your Time Machine backups, your Dropbox sync, that screen share last week. Not a scary-hacker thing. It's the same as your shell history — boring housekeeping, except for a history most people don't even know exists. Go look at the folder, honestly, it's eye-opening. A friend of mine, Ishan — solid dev, better known in the Cardano world — built a tool for exactly this cleanup, just trying to give people something they can actually use. It checks the local history of ~29 different agents for a couple hundred secret patterns, runs fully offline (nothing leaves your machine), and just *scans* by default — it only redacts if you tell it to, and it makes backups you can undo from. Genuinely beginner-friendly. Two things worth doing with it: don't trust me or him — **point your own agent at the repo and ask it for a safety review** before you run anything (good habit for every tool you find on the internet, this one included). And if it misses a pattern or you want your runtime covered, **open a PR** — he's responsive. Link in the comments. Not my project, just vouching for the guy and the idea. What do you all do about old sessions — clean them, ignore them, or is this the first you're hearing that they exist?

Detected 40 min after publishbefore mainstream feeds noticed
Niche 9.5Velocity 8.6Freshness 10.0Open on Reddit

Convergence

10 cross-source signals in the last 48 hours

146

ORA – AI coding agent that blocks its own commits if security scan fails

7 signals across 3 sources · first seen 3d ago

Open top member →
100

Show HN: Make Production Ready Videos in After Effects Using Claude Code (OSS)

5 signals across 3 sources · first seen 2d ago

Open top member →
80

Show HN: Finterm.ai Bloomberg terminal for Claude Code

6 signals across 2 sources · first seen 2d ago

Open top member →
78

OpenAI Just Dropped GPT 5.6... And It's Wild 🤖

12 signals across 2 sources · first seen 3d ago

Open top member →
78

Stop Hitting Claude Usage Limits (Use M3 Inside Claude Code)

2 signals across 2 sources · first seen 3d ago

Open top member →
77

[R] Deterministic attention-transformer with measured energy savings on H100 (0.63 J/token)

5 signals across 2 sources · first seen 3d ago

Open top member →
71

AI Is a Bad Tool

4 signals across 2 sources · first seen 1d ago

Open top member →
71

Claude is just Mr. Meeseeks

2 signals across 2 sources · first seen 2h ago

Open top member →
67

Learn 97% of Claude in 60 Seconds (Beginner Tutorial)

5 signals across 2 sources · first seen 3d ago

Open top member →
66

Show HN: PlanWright – A control plane for AI coding agents

3 signals across 2 sources · first seen 2d ago

Open top member →

Full feed

29 scored signals, filterable

Tomorrow's videos

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How it works

Six sources. Velocity over popularity.

GitHub release183 (0%)

Canonical AI repos, polled every 5 min for new releases.

GitHub trending1.0k (3%)

Scraped daily; filtered by AI keyword set.

YouTube1.5k (4%)

AI-niche channel uploads, views-per-hour vs channel median.

YouTube search777 (2%)

Discovery queries to catch breakout creators.

Reddit21.8k (54%)

Tavily search restricted to chosen subreddits.

RSS3.7k (9%)

Anthropic, OpenAI, DeepMind, HN, Latent Space, and 12 more.

X0 (0%)

Keyword + from:@account watches via Apify, every 12h.

The pipeline

ingest -> SQLite raw_events (1 row per signal)
score: Gemini Flash-Lite niche 0-10, then velocity + freshness
composite = (niche × 5) + (velocity × 3) + (freshness × 2)
cluster: Gemini text-embedding-004, cosine ≥ 0.82 union-find
cluster_score = max(member composites) × ln(1 + member_count)
angle: Gemini 2.5 Pro on top 5, voice rules baked in
snapshot: SQLite -> JSON -> Vercel Blob -> this page