@foxweather: 🌀 BREWING STORM: Check out satellite imagery of Hurricane Trudy as it develops off Mexico's southwestern coast this week, triggering a Hurricane Watch from Punta San Telmo to Playa Perula.

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Friday 16 October 2026 03:00:00 GMT

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98av9rwjhed2 :

Continue full drums!! 81

2026-10-16 06:53:54

1

dominick :

Dam

2026-10-16 03:02:09

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bongoguy48 :

Prayers sent

2026-10-16 04:36:22

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Yatoki :

箱推し確定✨

2026-10-16 03:53:52

2

TOPics :

huricane?

2026-10-16 03:07:34

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Linh bui van :

すごいですね！

2026-10-16 03:49:05

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FACT WORLD 🌎 :

please follow me

2026-10-16 04:40:37

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Len Clark :

焦らずゆっくり

2026-10-16 03:49:54

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eva20001228 :

😜😜

2026-10-16 07:23:22

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کبھی کبھی زندگی میں سخت فیصلے کرنے پڑتے ہیں، کہ جس کے کرنے سے ایک بار تو ہم دل و جان سے کانپ جاتے ہیں 😭 مگر وہ ضروری ہوتے ہیں 💔🥺😭🫵#fpyシ #fpy

کبھی کبھی زندگی میں سخت فیصلے کرنے پڑتے ہیں، کہ جس کے کرنے سے ایک بار تو ہم دل و جان سے کانپ جاتے ہیں 😭 مگر وہ ضروری ہوتے ہیں 💔🥺😭🫵#fpyシ #fpy

Sơn chống gỉ sét kim loại, máy móc, mái tôn siêu bám dính, độ bền tới 10 năm #cokhi #sonchonghanri #sonchongset #keochonghangi #sonchongriset

Sơn chống gỉ sét kim loại, máy móc, mái tôn siêu bám dính, độ bền tới 10 năm #cokhi #sonchonghanri #sonchongset #keochonghangi #sonchongriset

I pointed the crawler at my own prompts instead of the web. There are 195 prompts, and each one is treated as a decision point rather than plain text. Every prompt is evaluated through a structured set of questions: - Is it relevant? - Is it grounded? - Is it ambiguous? - Does it require approval? Each evaluation produces a probability score. The routing logic is intentionally deterministic—it has no opinions of its own. - p ≥ 0.95 → route directly into the execution/code path without invoking an LLM. - p < 0.95 → escalate to Claude Sonnet 5.5, the only model responsible for reasoning. - Anything that appears to require human approval is automatically handed off to me. In one execution: - 168 of 175 prompt decisions were resolved automatically. - 133 terminated within deterministic if branches. - 24 were escalated to Sonnet. - 11 ultimately required human approval. One interesting observation: the token

I pointed the crawler at my own prompts instead of the web. There are 195 prompts, and each one is treated as a decision point rather than plain text. Every prompt is evaluated through a structured set of questions: - Is it relevant? - Is it grounded? - Is it ambiguous? - Does it require approval? Each evaluation produces a probability score. The routing logic is intentionally deterministic—it has no opinions of its own. - p ≥ 0.95 → route directly into the execution/code path without invoking an LLM. - p < 0.95 → escalate to Claude Sonnet 5.5, the only model responsible for reasoning. - Anything that appears to require human approval is automatically handed off to me. In one execution: - 168 of 175 prompt decisions were resolved automatically. - 133 terminated within deterministic if branches. - 24 were escalated to Sonnet. - 11 ultimately required human approval. One interesting observation: the token "ask" received an approval-confidence score of 0.544. Since the system lacked sufficient confidence, it deferred the decision instead of hallucinating. The average confidence across the entire run was 0.925. Everyone is crawling the web for additional context. The real context has been sitting inside the prompt all along—it just hasn't been interpreted correctly. #xuhuong #AI

#🇪🇬🇵🇸 #نداء_شراره #بدون_اسباب #جديد٢٠٢٦

#🇪🇬🇵🇸 #نداء_شراره #بدون_اسباب #جديد٢٠٢٦

at some point u gotta think what am i doing

at some point u gotta think what am i doing

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