DailyDawn · Daily AI brief for indie builders

🌐 English · 中文

30 minutes every morning to see what to ship, what to skip, who's eating whose lunch.

Latest 3 issues

• 2026-11-02 · T3 stack code generation tool / T3 dev tool search surge / AI dev tool trending cluster

  Two today_window GitHub AI dev tools hit 4620 combined raw stars

• 2026-11-01 · Cross-agent memory tool surge / Local LLM speed gains / Local-first dev tool traction

  Two new GitHub trending AI dev tools hit 3061 combined raw stars in today_window

• 2026-10-31 · Local dev security scanning / Open source AI tutoring / LLM jailbreak testing

  Three distinct security-focused GitHub repos top today_window trending with 6637 combined raw scores

Full archive →

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Why read it daily

You probably bounce between HN, Product Hunt, Reddit, HuggingFace, and GitHub Trending every morning, manually piecing together "what actually happened today." LLMs do this faster and more thoroughly than humans can.

DailyDawn handles it for you: every day at UTC 00:00 it pulls 150+ raw signals from 7 sources, dedupes across them, sorts them into 5 dimensions (Launch discoveries / Tech stack / Competitive intel / Demand radar / Trend verdict), spins up one agent per dimension for deep analysis, and has an editor-in-chief synthesize a structured bilingual report.

Each issue is around 5,000 Chinese characters / 5,500 English words and contains:

• 20 today-specific deep sub-sections — questions are dynamically generated from today's actual signals; they change every day
• Three-tier build advice — today's 2-hour build / weekend extension / this week's longer bet / weekly risk
• Cross-source keyword growth — Google Trends 7-day rising queries that surface buyer intent
• Everything organized around "what should an indie builder do this week" — not news regurgitation

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Read now

• 📖 Today: English · 中文
• 📦 Full archive: English · 中文
• 🌐 Web: https://dailydawn.dev
• 📬 Email subscription: https://dailydawn.dev (bilingual, 1-click language switch)
• 📡 RSS / JSON Feed: https://dailydawn.dev/en.json · https://dailydawn.dev/zh.json

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What every issue looks like

# DailyDawn · 2026-04-18

> 📍 Top 3 signals
> 1. High confidence: …1937 votes / 1425 comments…
> 2. External find: …"agent memory" search +120% in 7d…
> 3. Double validation: …HN + PH + HuggingFace cross-source overlap…

## 🗣 Editor's take (600+ word POV opener)
## 🎯 Today's 2-hour build (one concrete actionable idea)

## Launch discoveries  (4 today-specific sub-questions)
## Tech stack          (4)
## Competitive intel   (4)
## Demand radar        (4)
## Trend verdict       (4, with keyword growth)

## 🔥 Action triggers
### Weekend extension build
### Longer bet this week
### Biggest risk / trap this week

5 sections × 4 today-specific sub-questions = 20 deep angles, all dynamically generated from today's actual signals (so the questions change daily). Every sub-section comes with a Key call and a Counterpoint.

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Data sources

Source	Method	Notes
Hacker News	Algolia API	Stories from last 24h with points>20
GitHub Trending	HTML scrape	Top 25 trending repos today
Product Hunt	GraphQL API	Top 20 by votes today
Reddit	Public JSON	12 subreddits incl. r/indiehackers, r/SideProject
HuggingFace	Public API	Models + datasets sorted by 7-day likes
V2EX	Public API	Chinese tech community heat
Google Trends	pytrends	20 indie-builder keywords' 7-day growth

Any source failure auto-skips without blocking the pipeline.

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How it works

GitHub Actions cron · daily at UTC 00:00
    │
    ├─ fetchers/*       Concurrently pull 150+ raw signals (~30s)
    ├─ aggregator       Cross-source dedup · Top 60 + all Trends preserved
    │
    ├─ classifier               Sort signals into 5 buckets
    ├─ question_generator       Generate 20 today-specific questions (zh + en)
    ├─ source_digest            Per-source cluster summary
    │
    ├─ experts × 5 × 2 lang     5 experts × 4 sub-section deep analysis
    └─ editor × 2 lang          POV opener + Top 3 + 3-tier build synthesis
        │
        ├─ renderer  → zh/YYYY/YYYY-MM-DD.md + en/...
        ├─ git push
        └─ webhook   → Web layer batch-sends email

About 18 LLM calls per day, against any OpenAI-compatible gateway (DeepSeek / OpenAI / Doubao all work).

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Tech stack

• Python 3.12 · httpx · asyncio (fully async)
• OpenAI SDK against any OpenAI-compatible LLM gateway
• GitHub Actions for scheduling + commit + webhook
• pytrends for Google Trends keyword growth
• tenacity for exponential backoff + graceful degradation
• ~1500 lines of Python, no database

The Web layer (subscriptions, email distribution) lives in a separate private repo — Cloudflare Workers + D1 + Queues + Resend.

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Run locally

git clone https://github.com/TangSY/dailydawn
cd dailydawn
pip install -r requirements.txt
cp .env.example .env  # Fill in LLM_API_KEY / LLM_BASE_URL / LLM_MODEL
python scripts/main.py  # One run produces zh/2026/today.md + en/2026/today.md

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License

MIT

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Links

• LINUX DO