Every morning at 6:30, your PC collects the last 24 hours of AI news from 16 feeds, has Claude score each story against your own rules, writes up the best ones with background and context, and emails you the briefing. This page explains what each part does and how they connect.
Horizon is a free, MIT-licensed Python project by Thysrael (about 12,800 stars on GitHub). It's a general tool for turning lots of feeds into one short daily briefing. Out of the box it's set up for general tech and finance news, with a Chinese/English focus.
Your copy has been set up for one job: a daily "what's new in AI" email in English. That meant choosing AI-specific sources, writing a custom scoring profile that drops non-AI stories, setting quotas so no one kind of source crowds out the rest, and fixing two problems that stopped it working on your machine.
Nothing runs in the cloud except the two services it calls. Collection, filtering and scheduling all happen on your PC. Claude is reached through Anthropic's API using your key, and the email goes out through your own Gmail account.
Everything inside the dashed box runs on your PC. Arrows show which way data flows.
Approximate times, based on the full run on Saturday 7 November, which took 6 minutes 26 seconds. Busier weekdays take a little longer.
It runs run-horizon.ps1 in a hidden window. If the PC was off or you weren't logged in, it runs as soon as you next log in. It only starts if there's a network connection, and it's stopped if it ever runs longer than 45 minutes.
It reads data/config.json, the two secrets in .env, and the scoring profiles. It then sets the time window to the last 24 hours.
It downloads every feed and keeps only items published in the window. On a quiet day that's about 75 items, on a busy one about 100. The Reddit feeds may be refused a few times and retried after 15, 30 and 45 seconds.
One Claude request per item, two at a time. Each item comes back with a score from 0 to 10, a one-line summary, and tags. This is the slowest step and uses most of the tokens.
Items below the score threshold are dropped. Claude merges stories that cover the same event, and quotas cap each kind of source. This takes a few seconds.
For each chosen item, one at a time, Claude writes the summary, background, impact and community-discussion sections. It searches the web and looks at earlier briefings when it needs more context.
The briefing is saved as Markdown in data/summaries/, converted to an HTML email, and sent to every address in data/subscribers.json. Right now that's only you.
Real counts from the test run on 5 November, the first run with the AI-only profile. Bars are drawn to scale.
The steps run in this order every time. They're defined in src/orchestrator.py.
Each source type has its own collector in src/scrapers/. RSS and Atom feeds are parsed with feedparser. For lab blogs and long-form feeds, the full article is also downloaded and cleaned with trafilatura, so Claude reads the whole post, not just a teaser. Hacker News comes from its official API and includes the top comments.
If the same link turns up from two sources, for example an OpenAI post that is also on Hacker News, the copies are merged into one item that keeps the discussion from both.
No AIEach item goes to Claude with its profile's rules (profiles/ai-news/analysis.md), the article text, and engagement figures such as upvotes and comment counts. Claude returns JSON with a score from 0 to 10, a reason, a one-line summary, and 3–5 tags. If the JSON is malformed it gets one retry.
Items scoring below their profile's threshold are dropped. That's 6 for AI news and 5 for the deep-dive blogs.
No AIDifferent links about the same event, such as five articles on one model launch, are grouped by Claude. Only the highest-scoring version is kept, with the others' text folded in.
Claude · 1 callItems are sorted by score, then each source category may only fill its quota (see the quota chart). The briefing is capped at 20 items. Write-ups are only done after this, so no tokens are spent on items that wouldn't make it in.
No AIClaude writes the final sections for each item. It has two tools: web_search for facts the article doesn't include, and history_search, which looks through your earlier briefings so it can say what has changed since a previous report.
Claude · ~10 calls + toolsThe items are grouped under "AI News" and "Technology Blog" and rendered as Markdown. The Markdown is saved and converted to HTML. Then it's sent with a plain-text copy through Gmail, using an encrypted SMTP connection on port 465 and your App Password.
No AIDefined under sources in data/config.json. The category decides which quota an item counts against. The profile decides which scoring rules are used.
| Source | How it's read | Category | Profile | Notes |
|---|---|---|---|---|
| Anthropic News | RSS + full text | labs | ai-news | Anthropic has no official feed, so this uses a community-maintained one (Olshansk/rss-feeds) that mirrors anthropic.com/news |
| OpenAI News | RSS + full text | labs | ai-news | openai.com/news/rss.xml |
| Google DeepMind | RSS + full text | labs | ai-news | |
| Google AI Blog | RSS | labs | ai-news | blog.google/technology/ai |
| The Verge AI | RSS | press | ai-news | |
| TechCrunch AI | RSS | press | ai-news | The busiest feed, about 18 items a day |
| Simon Willison | RSS | analysis | ai-news | Hands-on notes on new models and tools |
| Latent Space | RSS + full text | analysis | tech-blog | Engineering newsletter and podcast |
| Interconnects | RSS + full text | analysis | tech-blog | Nathan Lambert on open models and RL |
| Import AI | RSS | analysis | tech-blog | Jack Clark's weekly research roundup |
| Hugging Face Blog | RSS + full text | open-models | tech-blog | Counts towards the analysis quota |
| smol AINews | RSS | community | ai-news | Daily recap of AI Discord servers, Reddit and X |
| Reddit: r/LocalLLaMA + r/MachineLearning | RSS, top of the day, 25 posts | community | ai-news | Retried if Reddit says "too many requests" |
| Reddit: r/ClaudeAI + r/OpenAI + r/singularity | RSS, top of the day, 25 posts | community | ai-news | Same retry |
| Hacker News | Official API | community | ai-news | Top 30 stories with ≥ 100 points, plus comments. General tech, so non-AI stories are scored out |
| OSS Insight | Public API | oss-trending | ai-news | Repos gaining ≥ 50 stars in 24 h whose name or description matches llm, agent, gpt, claude, mcp, rag and similar. Up to 10 |
Why Reddit is read through RSS. Reddit now blocks most automated requests to its normal pages and its JSON listings. Horizon's built-in Reddit reader tries both and only then falls back to RSS, waiting about 20 seconds for each blocked attempt. Reading the RSS feeds directly skips those blocked attempts. Combining the subreddits into two feeds means only two requests a day. The trade-off is that comment threads aren't fetched, though they were being blocked anyway.
Each item is scored using its profile's rules. Lab announcements, news, Reddit and Hacker News use the custom ai-news profile written for this setup. Long-form blogs use Horizon's built-in tech-blog profile, which rewards engineering depth and practical lessons.
The ai-news profile has one extra rule the general one lacked: an item must be mainly about AI. Non-AI items score at most 3, however important they are, and items that only mention AI in passing score at most 4. That rule is what removed the SSH security bug and the Discord desktop app story from the first test run.
Scoring bands come from profiles/ai-news/analysis.md. Thresholds are set under processing.profile_settings in config.json. Raise the AI news threshold to 7 for a shorter briefing, or lower it to 5 for a longer one.
Without quotas, a busy Reddit day could fill the whole briefing. Each source category gets a fixed number of slots, filled highest score first. Unused slots aren't passed on, and the overall cap is 20.
Slots add up to 25, so the 20-item cap only matters on unusually busy days. Quotas are set under digest.category_groups in config.json.
A real item from the 5 November test briefing, shortened. Each part on the left of the card is produced by a different piece of the profile.
A new handbook for engineers who have trained dense models explains how to train Mixture-of-Experts models with Megatron-LM, from a hardware test and dense baseline through to a first single-node MoE run. The authors say it draws on about 800k GH200 GPU-hours on the Alps cluster at CSCS.
An MoE model replaces each dense feed-forward layer with many smaller "expert" networks and a router that sends each token to only a few of them. That cuts compute per token but adds problems such as balancing load across experts.
Teams moving from dense to MoE training get a consolidated starting point: a baseline comparison, recommended flags and scripts. Teams on other hardware should validate the settings themselves.
These are set in each profile's profile.json and enrichment.md.
C:\dev\AI News\ ├─ horizon-explained.html this page ├─ run-horizon.ps1 what Task Scheduler runs; writes a log, keeps the last 30 ├─ logs\horizon-YYYY-MM-DD_HHMM.log one per run; check here first if an email doesn't arrive └─ Horizon\ clone of github.com/Thysrael/Horizon ├─ .env ANTHROPIC_API_KEY, EMAIL_PASSWORD (git-ignored, never shared) ├─ .venv\ Python 3.12 environment with Horizon installed ├─ data\ │ ├─ config.json sources, model, thresholds, quotas, email settings │ ├─ subscribers.json who gets the email (just you) │ └─ summaries\ horizon-YYYY-MM-DD-en.md, one per day ├─ profiles\ │ ├─ ai-news\ custom: AI-only scoring and write-up rules │ ├─ tech-blog\ built-in, used for long-form blogs │ └─ tech-news\ … built-in, unused ├─ docs\_posts\ copy of each briefing, formatted for a GitHub Pages site (unused) └─ src\ Horizon's code (two small local fixes)
Files in orange are the ones you're most likely to open or edit.
| Change | File | Why |
|---|---|---|
| Recognise Anthropic's new "temperature" error | src/ai/client.py | Claude's API now rejects the temperature setting with the message "Extra inputs are not permitted". Horizon is meant to retry without it but didn't recognise that wording, so every Claude call failed. Adding the phrase lets the retry work. |
| Wait and retry on "too many requests" | src/scrapers/rss.py | Reddit's RSS often answers with error 429. Horizon now retries up to three times, waiting 15, 30 and 45 seconds, instead of skipping the feed. |
| AI-only scoring profile | profiles/ai-news/ | The built-in profile is for all of tech, so half of the first briefing wasn't about AI. |
| AI sources, quotas, Gmail delivery | data/config.json | Replaces the example sources, which include Linux and finance feeds and a Chinese Telegram channel. |
| Slower pacing (2 scoring calls at a time, 1 write-up at a time) | data/config.json | One run lost all its write-ups after a burst of about 100 requests. The likely cause is the request-rate limits on new Anthropic API accounts. |
| Daily schedule and log wrapper | Task Scheduler, run-horizon.ps1 | Horizon has no scheduler of its own. |
Before updating Horizon from GitHub: the two code fixes are local edits. Updating with git pull may conflict with them or overwrite them, unless the maintainer has fixed the same problems. Your config, profile and keys are separate files and won't be touched.
ai.model to claude-haiku-5-5 makes it noticeably cheaper.C:\dev\AI News\logs. The last line shows the exit code, where 0 means success..env.rss list and change the name and URL.digest.max_items.subscribers.json.In PowerShell, from C:\dev\AI News\Horizon:
.\.venv\Scripts\horizon.exe
Add --hours 4 for a quick, cheap test over the last 4 hours. Each run sends an email, so you'll get one for every test.