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Dating in Silicon Valley now involves spreadsheets, AI analysis, and $5,000-a-month relationship coaches

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Bottom line: This is how some of San Francisco's tech workers now date: They pipe their dating-app data into spreadsheets to track matches, while others try to game the apps' algorithms. Many also run their replies to dates through ChatGPT, and some hand the chatbot their whole dating history and ask it to find the patterns.

The industry's boom has drawn a wave of young, ambitious founders and engineers to San Francisco. Many say they date less because they work more, and when they do date, they treat it as a high-stakes decision. A first coffee can start to feel like a final-round interview.

Joyce Zhang sees this every week. A former product manager at Stripe, she now works as a dating coach in San Francisco, charges $5,000 a month and takes only...

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Benchmarking Claude Haiku, Sonnet, and Opus on 64 Broken Data Pipelines

2:07 a.m. The phone buzzes. The nightly transactions job has failed again. You open the laptop, squint at the error, find the batch that came in twice, write a quick dedupe, rerun, watch it go green, and crawl back to bed. Three days later finance asks why one

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Why Your LLM Keeps Matching the Wrong Products (And Why a Better Prompt Won't Fix It)

Imagine you have two product catalogs. One contains 10,000 items, the other 50,000. Your task is to find matching products, even though suppliers use different names, abbreviations, and formats. Sounds like a perfect job for an LLM, right? Modern language models understand context, recognize synonyms, and handle unstructured

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Google LSA Billing Is a Temporal Data Problem: Why Historical Configuration Matters

A Local Services Ads lead can be disputed days after the original customer interaction. By then, the business may have changed its opening hours, adjusted its ad schedule, modified its call-routing system, or migrated its campaign into Google Ads. The call record may still exist, but the configuration surrounding that

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Feature Theater: The AI Industry's Real Product Is Mediocrity at Scale

I've sat through a lot of sprint demos this year. And I've noticed something. The demos got better. The products didn't. Every two weeks there's a new screen, a new toggle, a new button with a little sparkle icon. Leadership claps. Then

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Benchmarking Claude Haiku, Sonnet, and Opus on 64 Broken Data Pipelines

Why Your LLM Keeps Matching the Wrong Products (And Why a Better Prompt Won't Fix It)

Google LSA Billing Is a Temporal Data Problem: Why Historical Configuration Matters

Feature Theater: The AI Industry's Real Product Is Mediocrity at Scale