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Parallel Web Systems

@p0 · San Francisco, CA · joined 30 Aug 2011

Web infrastructure for AI to search, extract, monitor, and reason over the world's information. Start here → https://t.co/0Enegj3dhv

21 577Followers
54Following
861Posts total
89.3KViews on collected posts

Latest posts

We've updated our docs with more thorough guidance on how to evaluate web search APIs: https://t.co/WQoo6SBqIc 2.1K views · 14 likes · 1 reposts · 1 replies Open on X →
September 16th, we're hosting a happy hour in San Francisco after Dreamforce. Join us @ Shoji for Japanese spirits and a gathering of the people building today's most forward-looking AI products. 5:00-7:00 PM. RSVP here: https://t.co/vPSMyxEO0l https://t.co/yTe4nah3dg
1.1K views · 9 likes · 1 reposts · 0 replies Open on X →
@p0 Understanding climate change modeling requires examining both its theoretical foundations and its practical limitations in high-risk industries. 140 views · 0 likes · 0 reposts · 0 replies Open on X →
@p0 Made this checklist a public Play: https://t.co/28FReb1uBo Init: `play run <URI> action=init project_dir=./eval`. Use `$play` in Codex; `/play` in Claude/Cursor. Validate/run the same pinned URI for one inspected contract: same Play + inputs + seed across harness 250 views · 1 likes · 0 reposts · 0 replies Open on X →
@p0 thank you 129 views · 1 likes · 0 reposts · 0 replies Open on X →
The bad news: you’re probably evaluating web search wrong. The good news: our team wrote a guide to help you and your agents do it right. Our main takeaway: don’t ask "Which search provider is best?" Ask: “Which model × search configuration is best for this task, at the cost 6K views · 46 likes · 0 reposts · 8 replies Open on X →
https://t.co/MFYDCh9i3D 50.3K views · 287 likes · 13 reposts · 9 replies Open on X →
Capable models have gotten cheaper. Search hasn’t, until now. Today we’re introducing Fast mode for Parallel Search: frontier-quality web search for AI that’s 10x cheaper than the default from model labs. - $1 per 1,000 results - 700ms p50 latency - #3 on Artificial Analysis 29.2K views · 148 likes · 10 reposts · 7 replies Open on X →

Against accounts of the same size

8 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views1 612this account924median for 10K–100K
Reach, %7.47%this account3.62%median for 10K–100K
Engagement, %0.69%this account1.52%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post1 6129241.74×
Reach (views ÷ followers)7.47%3.62%2.06×
Engagement rate0.69%1.52%0.45×

Others in this range →   Compare with another account →   How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

29.2K21 Aug
50.3K31 Aug
6K
1291 Sep
250
140
1.1K
2.1K2 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.57%21 Aug
0.62%31 Aug
0.92%
0.78%1 Sep
0.40%
0.00%
0.90%
0.76%2 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes42.3%506 in total
Reposts2.1%25 in total
Replies2.1%25 in total
Quotes0.8%9 in total
Bookmarks52.8%631 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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