What This Site Picked

What happens in a day

2026-09-13 · recorded for 37 days

1. 1,521 feed items
2. 22 last 24h
3. 19 main candidates
4. 10 published

How the 22 last-24h items split

• main-pool candidates19
• separate Korea pool2
• self-promo / discussion0
• already published0
• outside AI scope1

Checks out: 22 = 19 (main) + 2 (Korea pool) + 0 (self-promo) + 0 (duplicate) + 1 (off-scope).

The Korea pool of 2 breaks down into 2 candidates, 0 dropped as promotional, and 0 dropped as outside AI scope. Korea stories are chosen from a separate pool and never mix with the main candidates.

We could not collect from 2 of the 14 feeds: AI타임스, Hacker News (AI).

Where the 19 candidates went

• published 10
• outranked 1
• same story 4
• 3-per-outlet cap 4
• original unreadable 0

The bar above counts what happened at selection time. In practice 1 of these 10 started as different articles and were swapped for backups after we read the originals.

• The Decoder duplicate story

Across the 26 days on record we swapped 46 articles · duplicate story 35 · promotional 4 · original unreadable 4 · not news 2 · no usable facts 1.

Recent selection log

Only days with a recorded funnel. "Published" is the actual count; "swaps" is how many were replaced by backups. Days before swap-tracking show —.

Stories with a next step

On 2026-09-13 it was 2 of them, and 36 across the 18 days on record. We only write one when there is a screen to open or a setting to change today. When there is nothing to do we leave it out. Ten out of ten every day would mean writing sentences that look like actions rather than actions.

What came in, what ran: 37-day total

Across the 37 days with candidate records. Bar length is what came in; the solid part is what ran.

The "% of candidates published" is not a quality score for an outlet. It is affected by story volume, duplicate coverage, daily competition, and the per-outlet cap.

• AI Times 1228→75 6.1% AI Times, 75 of 1228 candidates published, 6.1 percent of candidates
• TechCrunch AI 260→86 33.1% TechCrunch AI, 86 of 260 candidates published, 33.1 percent of candidates
• The Decoder 152→41 27.0% The Decoder, 41 of 152 candidates published, 27.0 percent of candidates
• The Verge AI 135→37 27.4% The Verge AI, 37 of 135 candidates published, 27.4 percent of candidates
• Hacker News (AI) 99→0 0.0% Hacker News (AI), 0 of 99 candidates published, 0.0 percent of candidates
• Wired AI 90→42 46.7% Wired AI, 42 of 90 candidates published, 46.7 percent of candidates
• VentureBeat AI 70→8 11.4% VentureBeat AI, 8 of 70 candidates published, 11.4 percent of candidates
• Ars Technica AI 65→32 49.2% Ars Technica AI, 32 of 65 candidates published, 49.2 percent of candidates
• OpenAI News 43→1 2.3% OpenAI News, 1 of 43 candidates published, 2.3 percent of candidates
• SiliconANGLE AI 33→2 6.1% SiliconANGLE AI, 2 of 33 candidates published, 6.1 percent of candidates
• MIT Technology Review AI 27→18 66.7% MIT Technology Review AI, 18 of 27 candidates published, 66.7 percent of candidates
• Google AI Blog 13→10 76.9% Google AI Blog, 10 of 13 candidates published, 76.9 percent of candidates
• Google DeepMind Blog 11→9 81.8% Google DeepMind Blog, 9 of 11 candidates published, 81.8 percent of candidates
• MarkTechPost 4→2 50.0% MarkTechPost, 2 of 4 candidates published, 50.0 percent of candidates

Which outlets we ran

14 sources in total. No outlet can take more than 3 of the 10 slots in a day. Percentages are of all 519 published stories.

• TechCrunch AI 13526.0% TechCrunch AI, 135 of 519 published stories, 26.0 percent
• AI Times 8015.4% AI Times, 80 of 519 published stories, 15.4 percent
• Wired AI 5711.0% Wired AI, 57 of 519 published stories, 11.0 percent
• Ars Technica AI 5610.8% Ars Technica AI, 56 of 519 published stories, 10.8 percent
• The Verge AI 509.6% The Verge AI, 50 of 519 published stories, 9.6 percent
• The Decoder 417.9% The Decoder, 41 of 519 published stories, 7.9 percent
• VentureBeat AI 214.0% VentureBeat AI, 21 of 519 published stories, 4.0 percent
• MIT Technology Review AI 203.9% MIT Technology Review AI, 20 of 519 published stories, 3.9 percent

What the stories were about

Each percentage is the share of all 519 published stories that carry that topic. A story can have more than one topic, so the counts can exceed the story total and the percentages can add up to more than 100%.

• Business & Funding 13926.8% Business & Funding, 139 of 519 published stories, 26.8 percent
• Products & Services 12223.5% Products & Services, 122 of 519 published stories, 23.5 percent
• Safety & Alignment 11321.8% Safety & Alignment, 113 of 519 published stories, 21.8 percent
• Agents & Dev Tools 9718.7% Agents & Dev Tools, 97 of 519 published stories, 18.7 percent
• Policy & Regulation 8115.6% Policy & Regulation, 81 of 519 published stories, 15.6 percent
• Models & Research 7714.8% Models & Research, 77 of 519 published stories, 14.8 percent
• Society & Work 7213.9% Society & Work, 72 of 519 published stories, 13.9 percent
• Infrastructure & Chips 6111.8% Infrastructure & Chips, 61 of 519 published stories, 11.8 percent
• Open Source 254.8% Open Source, 25 of 519 published stories, 4.8 percent
• Generative Media 214.0% Generative Media, 21 of 519 published stories, 4.0 percent
• Robotics & Physical AI 183.5% Robotics & Physical AI, 18 of 519 published stories, 3.5 percent
• Data & Training 152.9% Data & Training, 15 of 519 published stories, 2.9 percent

Terms we explained

Each term is explained on the day it actually appeared in a briefing. We don't write a dictionary separately. Repeats across days are counted once. Browse the glossary →

How these numbers are counted

You can download this page's aggregates as machine-readable JSON: selection data (JSON)